Analytics

View the entities of all accessible cluster databases with the new `.show databases entities` command for Kusto, and customize the output with various options.

Analyze networks, connected assets and more with Kusto's graph semantics extension to the Kusto Query Language (KQL). Find out how to contextualize your time series data in KQL, and how…

The no-code editor is now available in Azure Stream Analytics portal to enable building your Stream Analytics jobs effortlessly, no coding required.

Azure Data Explorer has released three new types of external tables: PostgrSQL, MySQL, and CosmosDB SQL. These new external tables allow users to query data from these sources directly within…

Azure Data Explorer has added a new capability called "DropMappedField" to its data mappings. This feature allows users to map an object in a JSON document to a column while…

Now generally available: managed ingestion from Azure Cosmos DB to Azure Data Explorer in near real time.

The new Azure Event Hubs SDK is now generally available for Go, allowing developers to build Go apps that send and receive events from Azure Event Hubs.

Azure HDInsight has made notable improvements in stability and latency on Autoscale.

Apache Spark™ 3.3 on HDInsight is now in preview.

HDInsight is now generally available in Poland Central. 

Azure HDInsight for Apache Spark 2.4 will be retired as of February 10, 2024.

KQL introduces a new function to retrieve country, state, city, and coordinates from IP addresses using GeoLite2 data. Find out how to use geo_info_from_ip_address() and what it can do for…

The Kusto Emulator is now available as a Linux Docker Container!

Azure Data Explorer now supports ingestion of data from .NET Applications via the NLog Sink.

Are you using GitHub for managing your Stream Analytics project and looking to leverage GitHub's powerful CI/CD pipeline? Follow this comprehensive guide and learn to set up a CI/CD pipeline…

Users now can utilize MirrorMaker2 for effortless data replication from their on-premises or managed Kafka cluster directly to Event Hubs. 

With Kafka Connect support GA, users can seamlessly and reliably stream data between Azure Event Hubs and external systems such as databases, key-value stores, file systems and other data sources.

Users now can use managed identities when capturing event streams to storage services such as Azure Storage Services or Azure Data Lake storage 2.

Log compaction in Event Hubs introduces a key-based retention mechanism where the most recent value associated with each event key in an event hub or Kafka topic is retained.

Azure Stream Analytics supports for end-to-end exactly once semantics when writing to Azure Data Lake Storage Gen2.

You can connect directly to Kafka to ingest from Kafka clusters or output data to Kafka clusters in your Azure Stream Analytics (ASA) job.

Stream Analytics now supports end-to-end exactly once semantics when writing to Event Hub output.

Azure Stream Analytics can now fetch schema from the Schema Registry and deserialize data from Event Hub inputs for Avro format.

Users can now select AMD-based confidential VMs for their Azure Databricks cluster driver node and cluster worker nodes.

Users can now run their most sensitive data workloads in ADX clusters on AMD-based confidential VM SKUs.

Azure Monitor Log Alerts is expanding to support monitoring based on data that stored in Azure Data Explorer (ADX) tables, empowering customers to leverage ADX without compromising their service monitoring.

Azure Data Explorer now supports geospatial analysis with three new functions: geo_point_buffer, geo_line_buffer, and geo_polygon_buffer. These functions let you create polygonal buffers around points, lines, or polygons.

Serverless SQL for Azure Databricks is now generally available. This capability provides instant compute to users for their BI and SQL workloads, with minimal management required.

Run you mission critical Kafka, AMQP and HTTPS event streaming workloads with consitenct low latency.

You can connect your Azure Stream Analytics job to Azure Data Explorer / Kusto clusters using managed private endpoints

Use Stream Analytics to process exported data from Application Insights

Azure HDInsight for Apache Kafka 3.2.0 now available for public preview and ready for production workloads.

Multi-Column Distribution (MCD) is highly desirable for easing migrations, promotes faster query performance and reduces data skew.

Azure HDInsight for Apache HBase 2.4.11 now available for public preview and ready for production workloads.

Independently throttle your event streaming workloads using application groups and client applications information at namespace or event hub/Kafka topic level.

Azure Data Explorer now supports ingestion of data from .NET Applications via the Serilog Sink.

Data Sharing Lineage is now available in Microsoft Purview for Azure Data Lake Storage (ADLS) Gen2 and Azure Blob (Blob) Storage in public preview. Data Sharing Lineage is aimed to…

Model Serving on Azure Databricks is now generally available

New features are now available in Stream Analytics no-code editor GA including Power BI output support, and data preview optimization. Power BI output feature enables you to build real-time dashboard…

We are thrilled to announce the much-anticipated General Availability of ADX Dashboards!

Azure Private Link for Azure Databricks

Find partners for Azure Data Explorer. Our new partner program aims to connect customers and partners with ease.

Azure Databricks is now generally available in China North 3. 

Stream Analytics no-code editor now supports capturing Event Hubs data into ADLS gen2 with Delta Lake format.

Azure Data Explorer now supports ingestion of data from Apache Log4j 2.

New features are now available in Stream Analytics no-code editor GA including multiple parameter built-in functions support, Delta Lake format support in ADLS Gen2 output sink.

The processor diagram in physical job diagram provides you further insights within the streaming nodes of your stream analytics jobs.

Faster Azure Synapse Analytics Spark performance at no cost.

Beginning in November, Azure Databricks customers have an additional option for SQL compute, with Azure Databricks SQL Pro, which provides enhanced performance and integration features.

Runs insert, update, or delete operations on a target table from the results of a join with a source table.