What's new in Azure Synapse Analytics?
This page is continuously updated with a recent review of what's new in Azure Synapse Analytics, and also what features are currently in preview. To follow the latest in Azure Synapse news and features, see the Azure Synapse Analytics Blog and companion videos on YouTube.
For older updates, review past Azure Synapse Analytics Blog posts or previous updates in Azure Synapse Analytics.
Features currently in preview
The following table lists the features of Azure Synapse Analytics that are currently in preview. Preview features are sorted alphabetically.
Note
Features currently in preview are available under supplemental terms of use, review for legal terms that apply to Azure features that are in beta, preview, or otherwise not yet released into general availability. Azure Synapse Analytics provides previews to give you a chance to evaluate and share feedback with the product group on features before they become generally available (GA).
| Feature | Learn more |
|---|---|
| Spark Advisor for Azure Synapse Notebook | The Spark Advisor for Azure Synapse Notebook analyzes code run by Spark and displays real-time advice for Notebooks. The Spark advisor offers recommendations for code optimization based on built-in common patterns, performs error analysis, and locates the root cause of failures. |
| Apache Spark Delta Lake tables in serverless SQL pools | The ability to for serverless SQL pools to access Delta Lake tables created in Spark databases is in preview. For more information, see Azure Synapse Analytics shared metadata tables. |
| Apache Spark elastic pool storage | Azure Synapse Analytics Spark pools now support elastic pool storage in preview. Elastic pool storage allows the Spark engine to monitor worker node temporary storage and attach more disks if needed. No action is required, and you should see fewer job failures as a result. For more information, see Blog: Azure Synapse Analytics Spark elastic pool storage is available for public preview. |
| Apache Spark Optimized Write | Optimize Write is a Delta Lake on Azure Synapse feature reduces the number of files written by Apache Spark 3 (3.1 and 3.2) and aims to increase individual file size of the written data. |
| Apache Spark R language support | Built-in R support for Apache Spark is now in preview. |
| Azure Synapse Data Explorer | The Azure Synapse Data Explorer provides an interactive query experience to unlock insights from log and telemetry data. Connectors for Azure Data Explorer are available for Synapse Data Explorer. For more news, see Azure Synapse Data Explorer (preview). |
| Browse ADLS Gen2 folders in the Azure Synapse Analytics workspace | You can now browse an Azure Data Lake Storage Gen2 (ADLS Gen2) container or folder in your Azure Synapse Analytics workspace in Synapse Studio. To learn more, see Browse an ADLS Gen2 folder with ACLs in Azure Synapse Analytics. |
| Cosmos DB Synapse Link for Azure Data Explorer preview | Azure Data Explorer supports fully managed data ingestion from Azure Cosmos DB using a change feed. For more information, see Ingest data from Azure Cosmos DB into Azure Data Explorer (Preview). |
| Data flow improvements to Data Preview | To learn more, see Data Preview and debug improvements in Mapping Data Flows. |
| Distribution Advisor | The Distribution Advisor is a new preview feature in Azure Synapse dedicated SQL pools Gen2 that analyzes queries and recommends the best distribution strategies for tables to improve query performance. For more information, see Distribution Advisor in Azure Synapse SQL. |
| Distributed Deep Neural Network Training | Learn more about new distributed training libraries like Horovod, Petastorm, TensorFlow, and PyTorch in Deep learning tutorials. |
| Embed ADX dashboards | Azure Data Explorer dashboards be embedded in an IFrame and hosted in third party apps. |
| Multi-column distribution in dedicated SQL pools | You can now Hash Distribute tables on multiple columns for a more even distribution of the base table, reducing data skew over time and improving query performance. For more information on opting-in to the preview, see CREATE TABLE distribution options or CREATE TABLE AS SELECT distribution options. |
| Reject options for delimited text files | Reject options for CREATE EXTERNAL TABLE on delimited files is in preview. |
| Time-To-Live in managed virtual network (VNet) | Reserve compute for the time-to-live (TTL) in managed virtual network TTL period, saving time and improving efficiency. For more information on this preview, see Announcing public preview of Time-To-Live (TTL) in managed virtual network. |
| User-Assigned managed identities | Now you can use user-assigned managed identities in linked services for authentication in Synapse Pipelines and Dataflows.To learn more, see Credentials in Azure Data Factory and Azure Synapse. |
Generally available features
The following table lists the features of Azure Synapse Analytics that have transitioned from preview to general availability (GA) within the last 12 months.
| Month | Feature | Learn more |
|---|---|---|
| March 2023 | Deploying Synapse SQL serverless using SSDT | SqlPackage's long-awaited support for Azure Synapse Analytics serverless SQL pools is now available starting with the 161.8089.0 SqlPackage. Serverless SQL pools are supported for both the extract and publish actions. |
| February 2023 | UTF-8 and Japanese collations support for dedicated SQL pools | Both UTF-8 support and Japanese collations are now generally available for dedicated SQL pools. |
| February 2023 | Azure Synapse Runtime for Apache Spark 3.3 | The Azure Synapse Runtime for Apache Spark 3.3 is now generall available. Based on our testing using the 1TB TPC-H industry benchmark, you're likely to see up to 77% increased performance. |
| December 2022 | SSIS IR Express virtual network injection | Both the standard and express methods to inject your SSIS Integration Runtime (IR) into a VNet are generally available now. For more information, see General Availability of Express Virtual Network injection for SSIS in Azure Data Factory. |
| November 2022 | Ingest data from Azure Stream Analytics into Synapse Data Explorer | The ability to use a Streaming Analytics job to collect data from an event hub and send it to your Azure Data Explorer cluster is now generally available. For more information, see Ingest data from Azure Stream Analytics into Azure Data Explorer and ADX output from Azure Stream Analytics. |
| November 2022 | Azure Synapse Link for SQL | Azure Synapse Link for SQL is now generally available for both SQL Server 2022 and Azure SQL Database. The Azure Synapse Link for SQL feature provides low- and no-code, near real-time data replication from your SQL-based operational stores into Azure Synapse Analytics. Provide BI reporting on operational data in near real-time, with minimal impact on your operational store. To learn more, visit What is Azure Synapse Link for SQL? |
| October 2022 | SAP CDC connector GA | The data connector for SAP Change Data Capture (CDC) is now GA. For more information, see Announcing Public Preview of the SAP CDC solution in Azure Data Factory and Azure Synapse Analytics and SAP CDC solution in Azure Data Factory. |
| September 2022 | MERGE T-SQL syntax | MERGE T-SQL syntax has been a highly requested addition to the Synapse T-SQL library. As in SQL Server, the MERGE syntax encapsulates INSERTs/UPDATEs/DELETEs into a single high-performance statement. Available in dedicated SQL pools in version 10.0.17829 and above. For more, see the MERGE T-SQL announcement blog. |
| July 2022 | Apache Spark™ 3.2 for Synapse Analytics | Apache Spark™ 3.2 for Synapse Analytics is now generally available. Review the official release notes and migration guidelines between Spark 3.1 and 3.2 to assess potential changes to your applications. For more details, read Apache Spark version support and Azure Synapse Runtime for Apache Spark 3.2. Highlights of what got better in Spark 3.2 in the Azure Synapse Analytics July Update 2022. |
| July 2022 | Apache Spark in Azure Synapse Intelligent Cache feature | Intelligent Cache for Spark automatically stores each read within the allocated cache storage space, detecting underlying file changes and refreshing the files to provide the most recent data. To learn more, see how to Enable/Disable the cache for your Apache Spark pool. |
| June 2022 | Map Data tool | The Map Data tool is a guided process to help you create ETL mappings and mapping data flows from your source data to Synapse without writing code. To learn more about the Map Data tool, read Map Data in Azure Synapse Analytics. |
| June 2022 | User Defined Functions | User defined functions (UDFs) are now generally available. To learn more, read User defined functions in mapping data flows. |
| May 2022 | Azure Synapse Data Explorer connector for Power Automate, Logic Apps, and Power Apps | The Azure Data Explorer connector for Power Automate enables you to orchestrate and schedule flows, send notifications, and alerts, as part of a scheduled or triggered task. To learn more, read Azure Data Explorer connector for Microsoft Power Automate and Usage examples for Azure Data Explorer connector to Power Automate. |
| April 2022 | Cross-subscription restore for Azure Synapse SQL | With the PowerShell Az.Sql module 3.8 update, the Restore-AzSqlDatabase cmdlet can be used for cross-subscription restore of dedicated SQL pools. To learn more, see Blog: Restore a dedicated SQL pool (formerly SQL DW) to a different subscription. This feature is now generally available for dedicated SQL pools (formerly SQL DW) and dedicated SQL pools in a Synapse workspace. What's the difference? |
| April 2022 | Database Designer | The database designer allows users to visually create databases within Synapse Studio without writing a single line of code. For more information, see Announcing General Availability of Database Designer. Read more about lake databases and learn How to modify an existing lake database using the database designer. |
| April 2022 | Database Templates | New industry-specific database templates were introduced in the Synapse Database Templates General Availability blog. Learn more about Database templates and the improved exploration experience. |
| April 2022 | Synapse Monitoring Operator RBAC role | The Synapse Monitoring Operator RBAC (role-based access control) role allows a user persona to monitor the execution of Synapse Pipelines and Spark applications without having the ability to run or cancel the execution of these applications. For more information, review the Synapse RBAC Roles. |
| March 2022 | Flowlets | Flowlets help you design portions of new data flow logic, or to extract portions of an existing data flow, and save them as separate artifact inside your Synapse workspace. Then, you can reuse these Flowlets can inside other data flows. To learn more, review the Flowlets GA announcement blog post and read Flowlets in mapping data flow. |
| March 2022 | Change Feed connectors | Changed data capture (CDC) feed data flow source transformations for Azure Cosmos DB, Azure Blob Storage, ADLS Gen1, ADLS Gen2, and Common Data Model (CDM) are now generally available. By simply checking a box, you can tell ADF to manage a checkpoint automatically for you and only read the latest rows that were updated or inserted since the last pipeline run. To learn more, review the Change Feed connectors GA preview blog post and read Copy and transform data in Azure Data Lake Storage Gen2 using Azure Data Factory or Azure Synapse Analytics. |
| March 2022 | Column level encryption for dedicated SQL pools | Column level encryption is now generally available for use on new and existing Azure SQL logical servers with Azure Synapse dedicated SQL pools and dedicated SQL pools in Azure Synapse workspaces. SQL Server Data Tools (SSDT) support for column level encryption for the dedicated SQL pools is available starting with the 17.2 Preview 2 build of Visual Studio 2022. |
| March 2022 | Synapse Spark Common Data Model (CDM) connector | The CDM format reader/writer enables a Spark program to read and write CDM entities in a CDM folder via Spark dataframes. To learn more, see how the CDM connector supports reading, writing data, examples, & known issues. |
Community
This section summarizes new Azure Synapse Analytics community opportunities and the Azure Synapse Influencer program from Microsoft.
| Month | Feature | Learn more |
|---|---|---|
| January 2023 | Azure Synapse MVP Corner | December highlights from the Microsoft Azure Synapse MVP blog series Azure Synapse MVP Corner. |
| December 2022 | Azure Synapse MVP Corner | November highlights from the Microsoft Azure Synapse MVP blog series in this month's Azure Synapse MVP Corner. |
| November 2022 | Azure Synapse Influencer program | The Azure Synapse Influencer program provides exclusive events and Q&A sessions like Ask the Experts with the Microsoft product team, where members can interact directly with product experts by asking any questions on various rotating topics. Get feedback from members of Azure Synapse Analytics influencer community. |
| October 2022 | Azure Synapse MVP Corner | October highlights from the Microsoft Azure Synapse MVP blog series in this month's Azure Synapse MVP Corner. |
| September 2022 | Azure Synapse MVP Corner | September highlights from the Microsoft Azure Synapse MVP blog series in this month's Azure Synapse MVP Corner. |
| May 2022 | Azure Synapse Influencer program | Sign up for our free Azure Synapse Influencer program and get connected with a community of Synapse-users who are dedicated to helping others achieve more with cloud analytics. Register now for our next Synapse Influencer Ask the Experts session. It's free to attend and everyone is welcome to participate and join the discussion on Synapse-related topics. You can watch past recorded Ask the Experts events on the Azure Synapse YouTube channel. |
| March 2022 | Azure Synapse Analytics and Microsoft MVP YouTube video series | A joint activity with the Azure Synapse product team and the Microsoft MVP community, a new YouTube MVP Video Series about the Azure Synapse features has launched. See more at the Azure Synapse Analytics YouTube channel. |
Apache Spark for Azure Synapse Analytics
This section summarizes recent new features and capabilities of Apache Spark for Azure Synapse Analytics.
| Month | Feature | Learn more |
|---|---|---|
| March 2023 | Increasing Azure Synapse Analytics Spark performance up to 77% | More regions are receiving the performance increase for Azure Synapse Spark workloads, including most recently Korea Central, Central India, and Australia Southeast. |
| March 2023 | Azure Synapse Spark Notebook – Unit Testing | Learn how to test and create unit test cases for Spark jobs developed using Synapse Notebook. |
| March 2023 | Apache Spark 2.4 and 3.1 retirement cycle | The Azure Synapse runtime for Apache Spark 2.4 and 3.1 have entered the retirement cycle. Apache Spark 2.4 will be retired September 29, 2023, and Apache Spark 3.1 will be retired as of January 26, 2024. You should relocate your workloads to a newer Apache Spark runtime within this period. Read more at Apache Spark runtimes in Azure Synapse and view the Spark migration guide. |
| February 2023 | Azure Synapse Runtime for Apache Spark 3.3 | The Azure Synapse Runtime for Apache Spark 3.3 is now generally available. Based on our testing using the 1TB TPC-H industry benchmark, you're likely to see up to 77% increased performance. |
| January 2023 | Spark Advisor for Azure Synapse Notebook | The Spark Advisor for Azure Synapse Notebook analyzes code run by Spark and displays real-time advice for Notebooks. The Spark advisor offers recommendations for code optimization based on built-in common patterns, performs error analysis, and locates the root cause of failures. |
| January 2023 | Improve Spark pool utilization with Synapse Genie | The Synapse Genie Framework improves Spark pool utilization by executing multiple Synapse notebooks on the same Spark pool instance. Read more about this metadata-driven utility written in Python. |
| November 2022 | Azure Synapse Runtime for Apache Spark 3.3 | The Azure Synapse Runtime for Apache Spark 3.3 is currently in preview. For more information, see the Apache Spark 3.3 preview blog post. Based on our testing using the 1TB TPC-H industry benchmark, you're likely to see up to 77% increased performance. |
| September 2022 | New informative Livy error codes | More precise error codes describe the cause of failure and replaces the previous generic error codes. Previously, all errors in failing Spark jobs surfaced with a generic error code displaying LIVY_JOB_STATE_DEAD. |
| September 2022 | New query optimization techniques in Apache Spark for Azure Synapse Analytics | Read the findings from Microsoft's work to gain considerable performance benefits across the board on the reference TPC-DS workload as well as a significant reduction in query plan generation time. |
| August 2022 | Apache Spark elastic pool storage | Azure Synapse Analytics Spark pools now support elastic pool storage in preview. Elastic pool storage allows the Spark engine to monitor worker nodes temporary storage and attach additional disks if needed. No action is required, and you should see fewer job failures as a result. For more information, see Blog: Azure Synapse Analytics Spark elastic pool storage is available for public preview. |
| August 2022 | Apache Spark Optimized Write | Optimize Write is a Delta Lake on Synapse preview feature that reduces the number of files written by Apache Spark 3 (3.1 and 3.2) and aims to increase individual file size of the written data. To learn more, see The need for optimize write on Apache Spark. |
| May 2022 | Azure Synapse dedicated SQL pool connector for Apache Spark now available in Python | Previously, the Azure Synapse Dedicated SQL Pool Connector for Apache Spark was only available using Scala. Now, the dedicated SQL pool connector for Apache Spark can be used with Python on Spark 3. |
| May 2022 | Manage Azure Synapse Apache Spark configuration | With the new Apache Spark configurations feature, you can create a standalone Spark configuration artifact with auto-suggestions and built-in validation rules. The Spark configuration artifact allows you to share your Spark configuration within and across Azure Synapse workspaces. You can also easily associate your Spark configuration with a Spark pool, a Notebook, and a Spark job definition for reuse and minimize the need to copy the Spark configuration in multiple places. |
| April 2022 | Apache Spark 3.2 for Synapse Analytics | Apache Spark 3.2 for Synapse Analytics with preview availability. Review the official Spark 3.2 release notes and migration guidelines between Spark 3.1 and 3.2 to assess potential changes to your applications. For more details, read Apache Spark version support and Azure Synapse Runtime for Apache Spark 3.2. |
| April 2022 | Parameterization for Spark job definition | You can now assign parameters dynamically based on variables, metadata, or specifying Pipeline specific parameters for the Spark job definition activity. For more details, read Transform data using Apache Spark job definition. |
| April 2022 | Apache Spark notebook snapshot | You can access a snapshot of the Notebook when there's a Pipeline Notebook run failure or when there's a long-running Notebook job. To learn more, read Transform data by running a Synapse notebook and Introduction to Microsoft Spark utilities. |
| March 2022 | Synapse Spark Common Data Model (CDM) connector | The CDM format reader/writer enables a Spark program to read and write CDM entities in a CDM folder via Spark dataframes. To learn more, see how the CDM connector supports reading, writing data, examples, & known issues. |
| March 2022 | Performance optimization for Synapse Spark dedicated SQL pool connector | New improvements to the Azure Synapse Dedicated SQL Pool Connector for Apache Spark reduce data movement and leverage COPY INTO. Performance tests indicated at least ~5x improvement over the previous version. No action is required from the user to leverage these enhancements. For more information, see Blog: Synapse Spark Dedicated SQL Pool (DW) Connector: Performance Improvements. |
| March 2022 | Support for all Spark Dataframe SaveMode choices | The Azure Synapse Dedicated SQL Pool Connector for Apache Spark now supports all four Spark Dataframe SaveMode choices: Append, Overwrite, ErrorIfExists, Ignore. For more information on Spark SaveMode, read the official Apache Spark documentation. |
| March 2022 | Apache Spark in Azure Synapse Analytics Intelligent Cache feature | Intelligent Cache for Spark automatically stores each read within the allocated cache storage space, detecting underlying file changes and refreshing the files to provide the most recent data. To learn more on this preview feature, see how to Enable/Disable the cache for your Apache Spark pool or see the blog post. |
Data integration
This section summarizes recent new features and capabilities of Azure Synapse Analytics data integration. Learn how to Load data into Azure Synapse Analytics using Azure Data Factory (ADF) or a Synapse pipeline.
| Month | Feature | Learn more |
|---|---|---|
| January 2023 | SQL CDC incremental extract now supports numeric columns | Enabling incremental extract from SQL Server CDC in dataflows allows you to only process rows that have changed since the last time that pipeline was executed. Supported incremental column types now include date/time and numeric columns. |
| December 2022 | Express virtual network injection | Both the standard and express methods to inject your SSIS Integration Runtime (IR) into a VNet are generally available now. For more information, see General Availability of Express Virtual Network injection for SSIS in Azure Data Factory. |
| October 2022 | SAP CDC connector GA | The data connector for SAP Change Data Capture (CDC) is now GA. For more information, see Announcing Public Preview of the SAP CDC solution in Azure Data Factory and Azure Synapse Analytics and SAP CDC solution in Azure Data Factory. |
| September 2022 | Gantt chart view | You can now view your activity runs with a Gantt chart in Azure Data Factory Integration Runtime monitoring. |
| September 2022 | Monitoring improvements | We've released a new bundle of improvements to the monitoring experience based on community feedback. |
| September 2022 | Maximum column optimization in mapping dataflow | For delimited text data sources such as CSVs, a new maximum columns setting allows you to set the maximum number of columns. |
| September 2022 | NUMBER to integer conversion in Oracle data source connector | New property to convert Oracle NUMBER type to a corresponding integer type in source via the new property convertDecimalToInteger. For more information, see the Oracle source connector. |
| September 2022 | Support for sending a body with HTTP request DELETE method in Web activity | New support for sending a body (optional) when using the DELETE method in Web activity. For more information, see the available Type properties for the Web activity. |
| August 2022 | Mapping data flows now support visual Cast transformation | You can use the cast transformation to easily modify the data types of individual columns in a data flow. |
| August 2022 | Default activity timeout changed to 12 hours | The default activity timeout is now 12 hours. |
| August 2022 | Pipeline expression builder ease-of-use enhancements | We've updated our expression builder UI to make pipeline designing easier. |
| August 2022 | New UI for mapping dataflow inline dataset types | We've updated our data flow source UI to make it easier to find your inline dataset type. |
| July 2022 | Time-To-Live in managed virtual network (VNet) | Reserve compute for the time-to-live (TTL) in managed virtual network TTL period, saving time and improving efficiency. For more information on this preview, see Announcing public preview of Time-To-Live (TTL) in managed virtual network. |
| June 2022 | SAP CDC connector preview | A new data connector for SAP Change Data Capture (CDC) is now available in preview. For more information, see Announcing Public Preview of the SAP CDC solution in Azure Data Factory and Azure Synapse Analytics and SAP CDC solution in Azure Data Factory. |
| June 2022 | Fuzzy join option in Join Transformation | Use fuzzy matching with a similarity threshold score slider has been added to the Join transformation in Mapping Data Flows. |
| June 2022 | Map Data tool GA | We're excited to announce that the Map Data tool is now Generally Available. The Map Data tool is a guided process to help you create ETL mappings and mapping data flows from your source data to Synapse without writing code. |
| June 2022 | Rerun pipeline with new parameters | You can now change pipeline parameters when rerunning a pipeline from the Monitoring page without having to return to the pipeline editor. To learn more, read Rerun pipelines and activities. |
| June 2022 | User Defined Functions GA | User defined functions (UDFs) in mapping data flows are now generally available (GA). |
| May 2022 | Export pipeline monitoring as a CSV | The ability to export pipeline monitoring to CSV and other monitoring improvements have been introduced to ADF. |
| May 2022 | Automatic incremental source data loading from PostgreSQL and MySQL | Automatic incremental source data loading from PostgreSQL and MySQL to Synapse SQL and Azure Database is now natively available in ADF. |
| May 2022 | Assert transformation error handling | Error handling has now been added to sinks following an assert transformation in mapping data flow. You can now choose whether to output the failed rows to the selected sink or to a separate file. |
| May 2022 | Mapping data flows projection editing | In mapping data flows, you can now update source projection column names and column types. |
| April 2022 | Dataverse connector for Synapse Data Flows | Dataverse is now a source and sink connector to Synapse Data Flows. You can Copy and transform data from Dynamics 365 (Microsoft Dataverse) or Dynamics CRM using Azure Data Factory or Azure Synapse Analytics. |
| April 2022 | Configurable Synapse Pipelines Web activity response timeout | With the response timeout property httpRequestTimeout, you can define a timeout for the HTTP request up to 10 minutes. Web activities work exceptionally well with APIs that follow the asynchronous request-reply pattern, a suggested approach for building scalable web APIs/services. |
| March 2022 | sFTP connector for Synapse data flows | A native sftp connector in Synapse data flows is supported to read and write data from sFTP using the visual low-code data flows interface in Synapse. To learn more, see Copy and transform data in SFTP server using Azure Data Factory or Azure Synapse Analytics. |
| March 2022 | Data flow improvements to Data Preview | Review features added to the Data Preview and debug improvements in Mapping Data Flows. |
| March 2022 | Pipeline script activity | You can now Transform data by using the Script activity to invoke SQL commands to perform both DDL and DML. |
Database Templates & Database Designer
This section summarizes recent new features and capabilities of database templates and the database designer.
| Month | Feature | Learn more |
|---|---|---|
| July 2022 | Browse industry templates | Browse industry templates and add tables to create your own lake database. Learn more about ways you can browse industry templates and get started with Quickstart: Create a new lake database leveraging database templates. |
| April 2022 | Database Designer | The database designer allows users to visually create databases within Synapse Studio without writing a single line of code. For more information, see Announcing General Availability of Database Designer. Read more about lake databases and learn How to modify an existing lake database using the database designer. |
| April 2022 | Database Templates | New industry-specific database templates were introduced in the Synapse Database Templates General Availability blog. Learn more about Database templates and the improved exploration experience. |
| April 2022 | Clone lake database | In Synapse Studio, you can now clone a database using the action menu available on the lake database. To learn more, read How-to: Clone a lake database. |
| April 2022 | Use wildcards to specify custom folder hierarchies | Lake databases sit on top of data that is in the lake and this data can live in nested folders that don't fit into clean partition patterns. You can now use wildcards to specify custom folder hierarchies. To learn more, read How-to: Modify a datalake. |
| January 2022 | New database templates | Learn more about new industry-specific Automotive, Genomics, Manufacturing, and Pharmaceuticals templates and get started with database templates in the Synapse Studio gallery. |
Developer experience
This section summarizes recent new quality of life and feature improvements for developers in Azure Synapse Analytics.
| Month | Feature | Learn more |
|---|---|---|
| December 2022 | MSSparkUtils is the Swiss Army knife inside Synapse Spark | MSSparkUtils is a built-in package to help you easily perform common tasks called Microsoft Spark utilities, including the ability to share results between notebooks. |
| September 2022 | Synapse CICD for publishing workspace artifacts | Integrating Synapse Studio with a Source Control System such as Azure DevOps Git or GitHub has been shown as one of Synapse Studio's preferred features to collaborate and provide source control for Azure Synapse. The Visual Studio marketplace has a Synapse workspace deployment task to automate publishing. |
| July 2022 | Synapse Notebooks compatibility with IPython | The official kernel for Jupyter notebooks is IPython and it's now supported in Synapse Notebooks. For more information, see Synapse Notebooks is now fully compatible with IPython. |
| July 2022 | Mssparkutils now has spark.stop() method | A new API mssparkutils.session.stop() has been added to the mssparkutils package. This feature becomes handy when there are multiple sessions running against the same Spark pool. The new API is available for Scala and Python. To learn more, see Stop an interactive session. |
| May 2022 | Updated Azure Synapse Analyzer Report | Learn about the new features in version 2.0 of the Synapse Analyzer report. |
| April 2022 | Azure Synapse Analyzer Report | The Azure Synapse Analyzer Report helps you identify common issues that may be present in your database that can lead to performance issues. |
| April 2022 | Reference unpublished notebooks | Now, when using %run notebooks, you can enable 'unpublished notebook reference', which will allow you to reference unpublished notebooks. When enabled, the notebook fetches the current contents in the notebook web cache, meaning other notebooks can immediately reference the changes in your notebook editor, without having to be publish (Live mode) or commit (Git mode). |
| March 2022 | Code cells with exception to show standard output | Now in Synapse notebooks, both standard output and exception messages are shown when a code statement fails for Python and Scala languages. For examples, see Synapse notebooks: Code cells with exception to show standard output. |
| March 2022 | Partial output is available for running notebook code cells | Now in Synapse notebooks, you can see anything you write (with println commands, for example) as the cell executes, instead of waiting until it ends. For examples, see Synapse notebooks: Partial output is available for running notebook code cells . |
| March 2022 | Dynamically control your Spark session configuration with pipeline parameters | Now in Synapse notebooks, you can use pipeline parameters to configure the session with the notebook %%configure magic. For examples, see Synapse notebooks: Dynamically control your Spark session configuration with pipeline parameters. |
| March 2022 | Reuse and manage notebook sessions | Now in Synapse notebooks, it's easy to reuse an active session conveniently without having to start a new one and to see and manage your active sessions in the Active sessions list. To view your sessions, select the 3 dots in the notebook and select Manage sessions. For examples, see Synapse notebooks: Reuse and manage notebook sessions. |
| March 2022 | Support for Python logging | Now in Synapse notebooks, anything written through the Python logging module is captured, in addition to the driver logs. For examples, see Synapse notebooks: Support for Python logging. |
Machine Learning
This section summarizes recent new features and improvements to machine learning models in Azure Synapse Analytics.
| Month | Feature | Learn more |
|---|---|---|
| March 2023 | Using OpenAI GPT in Synapse Analytics | Microsoft offers Azure OpenAI as an Azure Cognitive Service, and you can access Azure OpenAI's GPT models from within Synapse Spark. |
| November 2022 | R Support (preview) | Azure Synapse Analytics now provides built-in R support for Apache Spark, currently in preview. For an example, install an R library from CRAN and CRAN snapshots. |
| August 2022 | SynapseML v.0.10.0 | New release of SynapseML v0.10.0 (previously MMLSpark), an open-source library that aims to simplify the creation of massively scalable machine learning pipelines. Learn more about the latest additions to SynapseML and get started with SynapseML. |
| August 2022 | .NET support | SynapseML v0.10 adds full support for .NET languages like C# and F#. For a .NET SynapseML example, see .NET Example with LightGBMClassifier. |
| August 2022 | Azure Open AI Service support | SynapseML now allows users to tap into 175-Billion parameter language models (GPT-3) from OpenAI that can generate and complete text and code near human parity. For more information, see Azure OpenAI for Big Data. |
| August 2022 | MLflow platform support | SynapseML models now integrate with MLflow with full support for saving, loading, deployment, and autologging. |
| August 2022 | SynapseML in Binder | We know that Spark can be intimidating for first users but fear not because with the technology Binder, you can explore and experiment with SynapseML in Binder with zero setup, install, infrastructure, or Azure account required. |
| June 2022 | Distributed Deep Neural Network Training (preview) | The Azure Synapse runtime also includes supporting libraries like Petastorm and Horovod, which are commonly used for distributed training. This feature is currently available in preview. The Azure Synapse Analytics runtime for Apache Spark 3.1 and 3.2 also now includes support for the most common deep learning libraries like TensorFlow and PyTorch. To learn more about how to leverage these libraries within your Azure Synapse Analytics GPU-accelerated pools, read the Deep learning tutorials. |
Samples and guidance
This section summarizes new guidance and sample project resources for Azure Synapse Analytics.
| Month | Feature | Learn more |
|---|---|---|
| March 2023 | Creating a custom disaster recovery plan for your Synapse workspace | A multi-part blog series on creating a disaster recovery plan for their Synapse Workspace. |
| March 2023 | Azure Synapse connectivity: public endpoints, private endpoints, managed VNet and managed private endpoints | A three-part expert-written blog series on Azure Synapse connectivity for the various networking options, including inbound dedicated pool public endpoint connectivity, Azure Synapse private endpoints, and managed VNet and managed private endpoints. |
| February 2023 | Historical monitoring dashboards for Azure Synapse dedicated SQL pools | A walkthrough of the steps to enable historical monitoring using Azure Monitor Workbook templates on top of Azure Metrics and Azure Log Analytics. |
| January 2023 | Read Data Lake with Synapse Serverless pools | A two-part guide on how to use OPENROWSET to query a path within the lake or use an external table to query a path within the lake. |
| January 2023 | Structured streaming in Synapse Spark | A detailed example of streaming IoT temperature data from IoT devices into Synapse Spark. |
| January 2023 | Create DNS alias for dedicated SQL pool in Synapse workspace for disaster recovery | A custom DNS for dedicated SQL pools (formerly SQL DW) can provide redirect to client programs during a disaster. |
| December 2022 | Azure Synapse - Data Lake vs. Delta Lake vs. Data Lakehouse | Read a new Success Engineering blog post demystifying the terms Data Lake, Delta Lake, and Data Lakehouse. |
| November 2022 | How Data Exfiltration Protection (DEP) impacts Azure Synapse Analytics Pipelines | Data Exfiltration Protection (DEP) is a feature that enables additional restrictions on the ability of Azure Synapse Analytics to connect to other services. |
| November 2022 | Getting started with REST APIs for Azure Synapse Analytics - Apache Spark Pool | We provide instructions on how to setup and use Synapse REST endpoints and describe the Apache Spark Pool operations supported by REST APIs. |
| November 2022 | Demystifying Azure Synapse Data Explorer | A two-part explainer demystify Data Explorer in Azure Synapse and data ingestion with Azure Synapse Data Explorer. |
| November 2022 | Synapse Spark Delta Time Travel | Delta Lake time travel enables point-in-time query snapshots or even rolls back erroneous updates. |
| September 2022 | What is the difference between Synapse dedicated SQL pool (formerly SQL DW) and Serverless SQL pool? | Understand dedicated vs serverless pools and their concurrency. Read more at basic concepts of dedicated SQL pools and serverless SQL pools. |
| September 2022 | Reading Delta Lake in dedicated SQL Pool | Sample script to import Delta Lake files directly into the dedicated SQL Pool and support features like time-travel. For an explanation, see Reading Delta Lake in dedicated SQL Pool. |
| September 2022 | Azure Synapse Customer Success Engineering blog series | The new Azure Synapse Customer Success Engineering blog series launches with a detailed introduction to Building the Lakehouse - Implementing a Data Lake Strategy with Azure Synapse. |
| June 2022 | Azure Orbital analytics with Synapse Analytics | We now offer an Azure Orbital analytics sample solution showing an end-to-end implementation of extracting, loading, transforming, and analyzing spaceborne data by using geospatial libraries and AI models with Azure Synapse Analytics. The sample solution also demonstrates how to integrate geospatial-specific Azure Cognitive Services models, AI models from partners, and bring-your-own-data models. |
| June 2022 | Migration guides for Oracle | A new Microsoft-authored migration guide for Oracle to Azure Synapse Analytics is now available. Design and performance for Oracle migrations. |
| June 2022 | Azure Synapse success by design | The Azure Synapse proof of concept playbook provides a guide to scope, design, execute, and evaluate a proof of concept for SQL or Spark workloads. |
| June 2022 | Migration guides for Teradata | A new Microsoft-authored migration guide for Teradata to Azure Synapse Analytics is now available. Design and performance for Teradata migrations. |
| June 2022 | Migration guides for IBM Netezza | A new Microsoft-authored migration guide for IBM Netezza to Azure Synapse Analytics is now available. Design and performance for IBM Netezza migrations. |
Security
This section summarizes recent new security features and settings in Azure Synapse Analytics.
| Month | Feature | Learn more |
|---|---|---|
| December 2022 | How Data Exfiltration Protection (DEP) impacts Azure Synapse Analytics Pipelines | Data Exfiltration Protection (DEP) is a feature that enables additional restrictions on the ability of Azure Synapse Analytics to connect to other services. |
| August 2022 | Execute Azure Synapse Spark Notebooks with system-assigned managed identity | You can now execute Spark Notebooks with the system-assigned managed identity (or workspace managed identity) by enabling Run as managed identity from the Configure session menu. With this feature, you are able to validate that your notebook works as expected when using the system-assigned managed identity, before using the notebook in a pipeline. For more information, see Managed identity for Azure Synapse. |
| July 2022 | Changes to permissions needed for publishing to Git | Now, only Git permissions and the Synapse Artifact Publisher (Synapse RBAC) role are needed to commit changes in Git-mode. For more information, see Access control enforcement in Synapse Studio. |
| April 2022 | Synapse Monitoring Operator RBAC role | The Synapse Monitoring Operator role-based access control (RBAC) role allows a user persona to monitor the execution of Synapse Pipelines and Spark applications without having the ability to run or cancel the execution of these applications. For more information, review the Synapse RBAC Roles. |
| March 2022 | Enforce minimal TLS version | You can now raise or lower the minimum TLS version for dedicated SQL pools in Synapse workspaces. To learn more, see Azure SQL connectivity settings. The workspace managed SQL API can be used to modify the minimum TLS settings. |
| March 2022 | Azure Synapse Analytics now supports Azure Active Directory (Azure AD) only authentication | You can now use Azure Active Directory authentication to centrally manage access to all Azure Synapse resources, including SQL pools. You can disable local authentication upon creation or after a workspace is created through the Azure portal. |
Azure Synapse Data Explorer (preview)
Azure Data Explorer (ADX) is a fast and highly scalable data exploration service for log and telemetry data. It offers ingestion from Event Hubs, IoT Hubs, blobs written to blob containers, and Azure Stream Analytics jobs. This section summarizes recent new features and capabilities of the Azure Synapse Data Explorer and the Kusto Query Language (KQL). Read more about What is the difference between Azure Synapse Data Explorer and Azure Data Explorer? (Preview)
| Month | Feature | Learn more |
|---|---|---|
| February 2023 | ADX file ingestion supports up to 1000 files | The ADX ingestion wizard now supports up to 1000 files (previously 10) at once. |
| January 2023 | Apache Log4j 2 connector for Azure Data Explorer | The Apache Log4J 2 sink for Azure Data Explorer was developed to easily stream your Log4j 2 log data to Azure Data Explorer, where you can analyze, visualize, and alert on your logs in real-time. For more information, see Getting started with Apache Log4j and Azure Data Explorer. |
| January 2023 | Ingest preexisting Event Hub events to ADX | ADX can now ingest Event Hubs data that existed before the creation of an Event Hubs data connection in your ADX cluster via the Event retrieval start date. |
| January 2023 | Multivariate Anomaly Detection | ADX contains native support for detecting anomalies over multiple time series by using the function series_decompose_anomalies(). For more information, see Multivariate Anomaly Detection. |
| January 2023 | Improved conditional formatting in dashboard | Conditional formatting helps in surfacing anomalies or outlier data points visually. Now you can either format a visual by using conditions or by applying themes to numeric columns or discrete values to non-numeric ones. |
| January 2023 | New display options for pie chart displays | Focus on the data you care about with new display options for pie chart visualizations in Dashboards. |
| December 2022 | ADX Kusto Web Explorer (KWE) JPath viewer | JPath notation describes the path to one or more elements in a JSON document. Use the new expanded view to quickly get a specific element of a JSON text, and easily copy its path expression. For an example, see JPath viewer. |
| December 2022 | Demystifying data consumption using Azure Synapse Data Explorer | A guide to the various ways of retrieving, consuming and visualizing data from Azure Synapse Data Explorer. |
| November 2022 | Table Level Sharing support via Azure Data Share | We have now added Table level sharing support via the Azure Data Share interface where you can share specific tables in the database. This allows you to easily and securely share your data with people in your company or external partners. |
| November 2022 | Ingest data from Azure Stream Analytics into Synapse Data Explorer | The ability to use a Streaming Analytics job to collect data from an event hub and send it to your Azure Data Explorer cluster is now generally available. For more information, see Ingest data from Azure Stream Analytics into Azure Data Explorer and ADX output from Azure Stream Analytics. |
| November 2022 | Parse-kv operator | The new parse-kv operator extracts structured information from a string expression and represents the information in a key/value form. You can use a specified delimeter, a non-specified delimeter, or Regex via a RE2 regular expression. |
| October 2022 | Leaders and followers in ADX clusters | Use the database page in the Azure portal to easily identify all the follower databases following a leader, and the leader for a given follower. |
| October 2022 | Aliasing follower databases | The follower database feature allows you to attach a database located in a different cluster to your Azure Data Explorer cluster. Now you can override the database name while establishing a follower relationship. |
| October 2022 | Ingest data from OpenTelemetry | OpenTelemetry (OTel) is a vendor-neutral open-source application observability framework. The OpenTelemetry exporter supports ingestion of data from many receivers into Azure Data Explorer. |
| October 2022 | Ingest data from Telegraf | Telegraf is an open source, lightweight, minimal memory footprint agent for collecting, processing, and writing telemetry data including logs, metrics, and IoT data. The Azure Data Explorer output plugin serves as the connector from Telegraf and supports ingestion of data from many types of input plugins into Azure Data Explorer. |
| September 2022 | Azure Data Explorer Kusto emulator | The ADX Emulator is a Docker Image exposing an ADX Query Engine endpoint. You can use it to create databases and ingest and query data. The emulator understands Kusto Query Language (KQL) the same way the Azure Service does. |
| September 2022 | Logstash connector proxy configuration | The Azure Data Explorer (ADX) Logstash plugin enables you to process events from Logstash into an ADX database for analysis. Version 1.0.5 now supports HTTP/HTTPS proxies. |
| September 2022 | Kafka support for Protobuf format | The ADX Kafka sink connector leverages the Kafka Connect framework and provides an adapter to ingest data from Kafka in JSON, Avro, String, and now the Protobuf format in the latest update. Read more about Ingesting Protobuf data from Kafka to Azure Data Explorer. |
| September 2022 | Funnel visuals | Funnel is the latest visual we added to Azure Data Explorer dashboards following the feedback we received from customers. |
| September 2022 | .NET and Node.js support in Sample App Generator | The Azure Data Explorer (ADX) sample app generator wizard is a tool that allows you to create a working app to ingest and query your data in your preferred programming language. Now, generating sample apps in .NET and Node.js is supported along with the previously available options Java and Python. |
| August 2022 | Protobuf support in Kafka sink | Azure Data Explorer Kafka sink - a gold certified Confluent connector - helps ingest data from Kafka to Azure Data Explorer. We have added Protobuf support in the connector to help customers bring Protobuf data into ADX. |
| August 2022 | Native support for Amazon S3 | The .ingest into ADX command ingests data into a table by "pulling" the data from one or more cloud storage files. The command now supports Amazon S3 URLs. For an example, read the blog post announcing Continuous data ingestion from S3. |
| August 2022 | Embed ADX dashboards | The ADX web UI and dashboards be embedded in an IFrame and hosted in third party apps. |
| August 2022 | Free cluster upgrade option | You can now upgrade your Azure Data Explorer free cluster to a full cluster that removes the storage limitation allowing you more capacity to grow your data. |
| August 2022 | Analyze fresh ADX data from Excel pivot table | Now you can Use fresh and unlimited volume of ADX data (Kusto) from your favorite analytic tool, Excel pivot tables. MDX queries generated by the Pivot code, will find their way to the Kusto backend as KQL statements that aggregate the data as needed by the pivot and back to Excel. |
| August 2022 | Query results - color by value | Highlight unique data at-a-glance in query results to visually group rows that share identical values for a specific column. Use Explore results and Color by value to apply color to rows based on the selected column. |
| August 2022 | Web explorer - crosshair support for charts | The ysplit property now supports the crosshair visual (vertical lines that move along the mouse pointer) for many charts. |
| July 2022 | Scan operator | The powerful scan operator enables efficient and scalable process mining and sequence analytics and user analytics in ADX. Common scenarios for using scan include preventive maintenance for IoT devices, funnel analysis, recursive calculation, security scenarios looking for known attack steps, and more. |
| July 2022 | Ingest data from Azure Stream Analytics into Synapse Data Explorer (Preview) | You can now use a Streaming Analytics job to collect data from an event hub and send it to your Azure Data Explorer cluster using the Azure portal or an ARM template. For more information, see Ingest data from Azure Stream Analytics into Azure Data Explorer. |
| July 2022 | Render charts for each y column | Synapse Web Data Explorer now supports rendering charts for each y column. For an example, see the Azure Synapse Analytics July Update 2022. |
| June 2022 | Web Explorer new homepage | The new Azure Synapse Web Explorer homepage makes it even easier to get started with Synapse Web Explorer. |
| June 2022 | Web Explorer sample gallery | The [Web Explorer sample gallery]((https://techcommunity.microsoft.com/t5/azure-data-explorer-blog/azure-data-explorer-in-60-minutes-with-the-new-samples-gallery/ba-p/3447552) provides end-to-end samples of how customers leverage Synapse Data Explorer popular use cases such as Logs Data, Metrics Data, IoT data and Basic big data examples. |
| June 2022 | Web Explorer dashboards drill through capabilities | You can now use drillthroughs as parameters in your Synapse Web Explorer dashboards. |
| June 2022 | Time Zone settings for Web Explorer | The Time Zone settings of the Web Explorer now apply to both the Query results and to the Dashboard. By changing the time zone, the dashboards are automatically refreshed to present the data with the selected time zone. |
| May 2022 | Synapse Data Explorer live query in Excel | Using the new Data Explorer web experience Open in Excel feature, you can now provide access to live results of your query by sharing the connected Excel Workbook with colleagues and team members. You can open the live query in an Excel Workbook and refresh it directly from Excel to get the most up to date query results. To create an Excel Workbook connected to Synapse Data Explorer, start by running a query in the Web experience. |
| May 2022 | Use Managed Identities for external SQL Server tables | With Managed Identity support, Synapse Data Explorer table definition is now simpler and more secure. You can now use managed identities instead of entering in your credentials. To learn more about external tables, read Create and alter SQL Server external tables. |
| May 2022 | Azure Synapse Data Explorer connector for Microsoft Power Automate, Logic Apps, and Power Apps | New Azure Data Explorer connectors for Power Automate are generally available (GA). To learn more, read Azure Data Explorer connector for Microsoft Power Automate, the Microsoft Logic App and Azure Data Explorer, and the ability to Create Power Apps application to query data in Azure Data Explorer. |
| May 2022 | Dynamic events routing from event hub to multiple databases | We now support routing events data from Azure Event Hub/Azure IoT Hub/Azure Event Grid to multiple databases hosted in a single ADX cluster. To learn more about dynamic routing, read Ingest from event hub. |
| May 2022 | Configure a database using a KQL inline script as part of JSON ARM deployment template | Running a Kusto Query Language (KQL) script to configure your database can now be done using an inline script provided inline as a parameter to a JSON ARM template. |
Azure Synapse Link
Azure Synapse Link is an automated system for replicating data from SQL Server or Azure SQL Database, Azure Cosmos DB, or Dataverse into Azure Synapse Analytics. This section summarizes recent news about the Azure Synapse Link feature.
| Month | Feature | Learn more |
|---|---|---|
| January 2023 | Cosmos DB Synapse Link for Azure Data Explorer preview | Azure Data Explorer supports fully managed data ingestion from Azure Cosmos DB using a change feed. For more information, see Ingest data from Azure Cosmos DB into Azure Data Explorer (Preview). |
| November 2022 | Azure Synapse Link for SQL | Azure Synapse Link for SQL is now generally available for both SQL Server 2022 and Azure SQL Database. The Azure Synapse Link for SQL feature provides low- and no-code, near real-time data replication from your SQL-based operational stores into Azure Synapse Analytics. Provide BI reporting on operational data in near real-time, with minimal impact on your operational store. For more information, see What is Azure Synapse Link for SQL? |
| July 2022 | Batch mode | Decide between cost and latency in Azure Synapse Link for SQL by selecting continuous or batch mode to replicate your data. Batch mode allows you to save even more on costs by only paying for ingestion service during the batch loads instead of it being continuously on. You can select between 20 and 60 minutes for batch processing. |
| May 2022 | Azure Synapse Link for SQL preview | Azure Synapse Link for SQL is in preview for both SQL Server 2022 and Azure SQL Database. The Azure Synapse Link feature provides low- and no-code, near real-time data replication from your SQL-based operational stores into Azure Synapse Analytics. Provide BI reporting on operational data in near real-time, with minimal impact on your operational store. The Azure Synapse Link for SQL preview has been announced. For more information, see Blog: Azure Synapse Link for SQL Deep Dive. |
Synapse SQL
This section summarizes recent improvements and features in SQL pools in Azure Synapse Analytics.
| Month | Feature | Learn more |
|---|---|---|
| March 2023 | Deploying Synapse SQL serverless using SSDT | SqlPackage's long-awaited support for Azure Synapse Analytics serverless SQL pools is now available starting with the 161.8089.0 SqlPackage. Serverless SQL pools are supported for both the extract and publish actions. |
| February 2023 | UTF-8 and Japanese collations support for dedicated SQL pools | Both UTF-8 support and Japanese collations are now generally available for dedicated SQL pools. |
| September 2022 | Auto-statistics for OPENROWSET in CSV datasets | Serverless SQL pool will automatically create statistics for CSV datasets when needed to ensure an optimal query execution plan for OPENROWSET queries. |
| September 2022 | MERGE T-SQL syntax | T-SQL MERGE syntax has been a highly requested addition to the Synapse T-SQL library. MERGE encapsulates INSERTs/UPDATEs/DELETEs into a single statement. Available in dedicated SQL pools in version 10.0.17829 and above. For more, see the MERGE T-SQL announcement blog. |
| August 2022 | Apache Spark Delta Lake tables in serverless SQL pools | The ability to for serverless SQL pools to access Delta Lake tables created in Spark databases is in preview. For more information, see Azure Synapse Analytics shared metadata tables. |
| August 2022 | Multi-column distribution in dedicated SQL pools | You can now Hash Distribute tables on multiple columns for a more even distribution of the base table, reducing data skew over time and improving query performance. For more information on opting-in to the preview, see CREATE TABLE distribution options or CREATE TABLE AS SELECT distribution options. |
| August 2022 | Distribution Advisor | The Distribution Advisor is a new preview feature in Azure Synapse dedicated SQL pools Gen2 that analyzes queries and recommends the best distribution strategies for tables to improve query performance. For more information, see Distribution Advisor in Azure Synapse SQL. |
| August 2022 | Add SQL objects and users in Lake databases | New capabilities announced for lake databases in serverless SQL pools: create schemas, views, procedures, inline table-valued functions. You can also database users from your Azure Active Directory domain and assign them to the db_datareader role. For more information, see Access lake databases using serverless SQL pool in Azure Synapse Analytics and Create and use native external tables using SQL pools in Azure Synapse Analytics. |
| June 2022 | Result set size limit increase | The maximum size of query result sets in serverless SQL pools has been increased from 200 GB to 400 GB. |
| May 2022 | Automatic character column length calculation for serverless SQL pools | It's no longer necessary to define character column lengths for serverless SQL pools in the data lake. You can get optimal query performance without having to define the schema, because the serverless SQL pool uses automatically calculated average column lengths and cardinality estimation. |
| April 2022 | Cross-subscription restore for Azure Synapse SQL GA | With the PowerShell Az.Sql module 3.8 update, the Restore-AzSqlDatabase cmdlet can be used for cross-subscription restore of dedicated SQL pools. To learn more, see Restore a dedicated SQL pool to a different subscription. This feature is now generally available for dedicated SQL pools (formerly SQL DW) and dedicated SQL pools in a Synapse workspace. What's the difference? |
| April 2022 | Recover SQL pool from dropped server or workspace | With the PowerShell Restore cmdlets in Az.Sql and Az.Synapse modules, you can now restore from a deleted server or workspace without filing a support ticket. For more information, see Restore a dedicated SQL pool from a deleted Azure Synapse workspace or Restore a standalone dedicated SQL pools (formerly SQL DW) from a deleted server, depending on your scenario. |
| March 2022 | Column level encryption for dedicated SQL pools | Column level encryption is now generally available for use on new and existing Azure SQL logical servers with Azure Synapse dedicated SQL pools and dedicated SQL pools in Azure Synapse workspaces. SQL Server Data Tools (SSDT) support for column level encryption for the dedicated SQL pools is available starting with the 17.2 Preview 2 build of Visual Studio 2022. |
| March 2022 | Parallel execution for CETAS | Better performance for CREATE TABLE AS SELECT (CETAS) and subsequent SELECT statements now made possible by use of parallel execution plans. For examples, see Better performance for CETAS and subsequent SELECTs. |
Learn more
For older updates, review past Azure Synapse Analytics Blog posts or previous updates in Azure Synapse Analytics.
- Get started with Azure Synapse Analytics
- Introduction to Azure Synapse Analytics
- Realize Integrated Analytical Solutions with Azure Synapse Analytics
- Data integration at scale with Azure Data Factory or Azure Synapse Pipeline
- Microsoft Training Learning Paths for Azure Synapse
- Azure Synapse Analytics in Microsoft Q&A
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