What's new and planned for Synapse Data Warehouse in Microsoft Fabric
Important
The release plans describe functionality that may or may not have been released yet. The delivery timelines and projected functionality may change or may not ship. Refer to Microsoft policy for more information.
Synapse Data Warehouse in Microsoft Fabric is the first data warehouse that supports multi-table transactions and natively embraces an open data format. The warehouse is built on the robust SQL Server query optimizer and an enterprise grade distributed query processing engine that eliminates the need for configuration and management. Synapse Data Warehouse in Microsoft Fabric seamlessly integrates with Data Factory for data ingestion, Power BI for analysis and reporting, and Synapse Spark for data science and machine learning. It streamlines an organization's analytics investments by converging data lakes and warehouses.
Data warehousing workloads benefit from the rich capabilities of the SQL engine over an open data format, enabling customers to focus on analysis and reporting. They also benefit from accessing data from OneLake, a data lake storage virtualization service.
To learn more, see the documentation.
Investment areas
| Feature | Estimated release timeline |
|---|---|
| VARCHAR(MAX)/VARBINARY(MAX) types | Q4 2024 |
| String performance improvements | Q4 2024 |
| Case insensitive collation support (Warehouse only) | Shipped (Q4 2024) |
| Nested CTE | Shipped (Q4 2024) |
| T-SQL Notebook integration | Shipped (Q3 2024) |
| TRUNCATE | Shipped (Q3 2024) |
| ALTER TABLE - Add nullable column | Shipped (Q3 2024) |
| Query insights updates | Shipped (Q3 2024) |
| In-place restore within warehouse editor | Shipped (Q2 2024) |
| COPY INTO support for secure storage | Shipped (Q2 2024) |
| Copilot | Shipped (Q2 2024) |
| Time travel | Shipped (Q2 2024) |
| Warehouse monitoring experience | Shipped (Q2 2024) |
VARCHAR(MAX)/VARBINARY(MAX) types
Estimated release timeline: Q4 2024
Release Type: Public preview
Users can define columns with VARCHAR(MAX)/VARBINARY(MAX) types in Data warehouse to store string or binary data up to 1 MB. In SQL endpoint for the Lakehouse, the string types in Delta tables are represented as VARCHAR(MAX) without truncation to 8 KB. The performance differences between the queries that are working with VARCHAR(MAX) and VARCHAR(8000) types are minimized, which enables users to use large types without significant performance penalty.
String performance improvements
Estimated release timeline: Q4 2024
Release Type: General availability
Operations on strings (VARCHAR(N)) are common in T-SQL queries. Performance improvements on string functions and operators that are working with strings boosts the performance of the queries that use LIKE predicates, string functions and comparison operators in WHERE predicates, and operators like GROUP BY, ORDER BY, JOIN that are working with string types.
Shipped feature(s)
Case insensitive collation support (Warehouse only)
Shipped (Q4 2024)
Release Type: General availability
Using the public REST APIs to create a Data Warehouse includes a new option to set the default collation. This can be used to set a new Case Insensitive Collation default. The two supported collations are Latin1_General_100_CI_AS_KS_WS_SC_UTF8 (which is Case Insensitive) and Latin1_General_100_BIN2_UTF8 (which is Case Sensitive) and continues to be our default.
COLLATE T-SQL clause support is coming soon. This will enable you to utilize the COLLATE command with CREATE or ALTER TABLE to directly specify the collation for your VARCHAR fields.
Nested CTE
Shipped (Q4 2024)
Common Table Expressions (CTE) increases the readability and simplification for complex queries by deconstructing ordinarily complex queries into simple blocks to be used and reused if necessary, instead of rewriting the query. A nested CTE is defined with the definition of another CTE.
T-SQL Notebook integration
Shipped (Q3 2024)
Release Type: Public preview
You can start using T-SQL language support within Notebooks which combines the power of Notebooks and SQL within the same experience - enabling intellisense, autocomplete, cross database queries, richer visualizations and the ability to easily collaborate and share using Notebooks.
TRUNCATE
Shipped (Q3 2024)
The TRUNCATE command quickly removes all rows of data from a table.
ALTER TABLE - Add nullable column
Shipped (Q3 2024)
Support for ALTER TABLE ADD COLUMN to be able to extend already existing tables with new columns that allow NULL values.
Query insights updates
Shipped (Q3 2024)
A historic view of your closed sessions will be made available via Query Insights. This addition it helps you analyze traffic, load, and usage of your DW.
In-place restore within warehouse editor
Shipped (Q2 2024)
You can now easily create restore points and restore the warehouse to a known good state in the event of accidental corruption, using the Warehouse editor experience.
COPY INTO support for secure storage
Shipped (Q2 2024)
Release Type: Public preview
You can now ingest data into your Warehouse using COPY INTO from an external Azure storage account that is protected behind a Firewall.
Copilot
Shipped (Q2 2024)
Release Type: Public preview
Copilot enables developers of any skill level to quickly build and query a warehouse in Fabric. Copilot offers advice and best practices, autocomplete code, help fix and document code, and offer assistance with data prep, modeling, and analysis.
Time travel
Shipped (Q2 2024)
The ability to time travel at the T-SQL statement level empowers users to query historical data from various past timeframes by specifying the timestamp only once for the entire query. Time travel helps save significantly on storage costs by using single copy of data present in One Lake for conducting historical trend analysis, troubleshooting, and data reconciliation. Additionally, it also facilitates achieving stable reporting by upholding the data integrity across various tables within the data warehouse.
Warehouse monitoring experience
Shipped (Q2 2024)
Using the built-in warehouse monitoring experience, you can view both live queries and historical queries, monitor, and troubleshoot performance of their end-to-end solution.