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General availability: Copy data to/from Azure Data Explorer using Azure Data Factory or Synapse Analytics
Mapping Data Flows provides scale-out data transformation in the cloud in Azure Data Factory and Azure Synapse Analytics. With these additional connectors, you can build ETL patterns at Spark scale in a code-free design environment without ever touching the Spark compute. Azure Integration Runtimes allow you to define the Spark environment and provide a serverless Spark compute for your data transformation pipelines.
Azure Data Explorer always supported to cache the latest ingested data for best performance. It now supports selectively caching older data which is ideal when auditing a given time period.
We are announcing that Azure Stream Analytics can directly output data to Azure Data Explorer, simplifying architecture where you need both hot and warm path analytics on streaming data. This feature will be added to all Stream Analytics regions progressively.
This new output plugin allows you to write telemetry collected by any of the input plugins of Telegraf directly into Azure Data Explorer e.g. it makes SQL monitoring at scale better and affordable.
Azure Synapse data explorer is optimized for efficient log analytics, using powerful indexing technology to automatically index structured, semi-structured, and free-text data commonly found in telemetry data.
Azure Data Explorer Insights provides comprehensive monitoring of your clusters by delivering a unified view of your cluster performance, usage, ingestion operations, cache, and more.
Azure Advisor analyzes the Azure Data Explorer cluster configurations and usage telemetry and offers personalized and actionable recommendations to help you optimize your cluster. Advisor is designed to help you save you time on the cluster optimization. The recommendations include suggested actions you can take right away, postpone, or dismiss.
You can now write cross service queries between Azure Monitor and Azure Data Explorer, to access relevant data where you need it.
Adding context to IoT data just became easier. Azure Digital Twins and Azure Data Explorer now seamlessly integrate, allowing you to allow you to contextualize time-series IoT data.
The new support for H3 based geospatial clustering in KQL enables users to visualize and explore spatial data stored in Azure Data Explorer.
Injecting an Azure Data Explorer cluster into a virtual network has never been easier.
Create an external table located in Azure Blob Storage, Azure Data Lake Store Gen1, or Azure Data Lake Store Gen2 to analyze and query your data.
Azure Data Explorer (Kusto) is announcing the general availability of it's performance update (EngineV3) which provides unprecedented performance in Big Data Logs and telemetry scenarios.
The next version of Azure Data Explorer (ADX) with performance updates is now available.
Azure Data Explorer ingestion wizard allows you to automatically create a table and ingest data from up to 10 files or blobs.
Azure Monitor for Azure Data Explorer (public preview) provides comprehensive monitoring of your Azure Data Explorer clusters by delivering a unified view of the performance, operations, and usage.
Azure Monitor cross resource query enables you to run cross-resource queries by using client tools that support Kusto queries.
With the new Grafana query builder, it is now possible to build dashboards in just a few clicks using a simple graphical experience.
Azure Data Explorer dashboards keeps evolving constantly. In this update we cover cascading filters, clickable URLs in tables, multi-stat cards, and text font size control in stat cards.
New ingestion feature intelligently suggests relevant table schema and mapping definitions to Event Hubs source
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