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Eventhouses provide a solution for handling and analyzing large volumes of data, particularly in scenarios requiring real-time analytics and exploration. They're designed to handle real-time data streams efficiently, which lets organizations ingest, process, and analyze data in near real-time. These aspects make eventhouses useful for scenarios where timely insights are crucial. Eventhouses provide a scalable infrastructure that allows organizations to handle growing volumes of data, ensuring optimal performance and resource use. Eventhouses are the preferred engine for semistructured and free text analysis. An eventhouse is a workspace of databases, which might be shared across a certain project. It allows you to manage multiple databases at once, sharing capacity and resources to optimize performance and cost. Eventhouses provide unified monitoring and management across all databases and per database.
Eventhouses are tailored to time-based, streaming events with structured, semistructured, and unstructured data. You can get data from multiple sources, in multiple pipelines (For example, Eventstream, SDKs, Kafka, Logstash, data flows, and more) and multiple data formats. This data is automatically indexed and partitioned based on ingestion time.
Use an eventhouse for any scenario that includes event-based data, for example, telemetry and log data, time series and IoT data, security and compliance logs, or financial records.
You can create a KQL database within an eventhouse. The KQL database can either be a standard database, or a database shortcut. An exploratory query environment is created for each KQL Database, which can be used for exploration and data management. Data availability in OneLake can be enabled on a database or table level.
The system overview page of an eventhouse shows you the following information:
For more information, see View system overview details for an eventhouse.
The databases page of an eventhouse shows you database information either in list or tile view. The following information about each database is displayed in tile view:
Your eventhouse is designed to optimize cost by suspending the service when not in use. When reactivating the service, you might encounter a latency of a few seconds. If you have highly time-sensitive systems that can't tolerate this latency, use Minimum consumption. This setting enables the service to be always available, but at a selected minimum level. You pay for the minimum compute level you select, or your actual consumption when your compute level is above the minimum set. The specified compute is available to all the databases within the eventhouse. A limited premium storage is included in the service, and corresponds to the minimum consumption levels shown in the following table:
Name | Minimum CUs | SSD capacity (GB) of free storage |
---|---|---|
Extra extra extra small | 2.25 | 25 |
Extra extra small | 4.25 | 50 |
Extra small | 8.5 | 200 |
Small | 13 | 800 |
Medium | 18 | 3500-4000 |
Large | 26 | 5250-6000 |
Extra large | 34 | 7000-8000 |
Extra extra large | 50 | 10500-12000 |
Custom | 51 | 14680-3666330 |
For instructions on how to enable minimum consumption, see Enable minimum consumption.
Įvykiai
03-31 23 - 04-02 23
Didžiausias "Fabric", Power BI ir SQL mokymosi įvykis. Kovo 31 d. – balandžio 2 d. Naudokite kodą FABINSIDER, kad įrašytumėte $400.
Registruokitės šiandienMokymas
Modulis
Work with real-time data in a Microsoft Fabric eventhouse - Training
Microsoft Fabric provides a scalable and flexible store for real-time data.
Sertifikatas
Microsoft Certified: Azure Database Administrator Associate - Certifications
Administer an SQL Server database infrastructure for cloud, on-premises and hybrid relational databases using the Microsoft PaaS relational database offerings.