{"data":[{"active":true,"blog_title":null,"blog_url":null,"feature_description":"Fabric feature store is a centralized system that manages the data inputs, called features, that power machine learning models. It bridges raw data and ML models, giving teams one place to define, store, serve, and discover features instead of each team building its own pipelines.","feature_name":"Feature Store","last_modified":"2026-08-11","product_id":"0522b590-dcd6-ee11-9079-000d3a310f67","product_name":"Data Science","release_date":"Q4 2026","release_item_id":"75004e12-2158-f111-bec7-6045bd00f798","release_status":"Planned","release_type":"Public preview"},{"active":true,"blog_title":null,"blog_url":null,"feature_description":"Quickly identify when and where throttling is occurring across your Eventhouse system. This feature highlights recent throttling events, helping you diagnose performance bottlenecks and take corrective action before they impact users.","feature_name":"show Throttling events of eventhouse at Eventhouse WS monitoring","last_modified":"2026-08-05","product_id":"58cb90aa-4203-ef11-a1fd-000d3a36eea4","product_name":"Real-Time Intelligence","release_date":"Q4 2026","release_item_id":"2d60a7e8-b555-f011-877a-00224804ca88","release_status":"Planned","release_type":"Public preview"},{"active":true,"blog_title":"Introducing the HTTP and MongoDB CDC Connectors for Eventstream \u2014 Inspired by You","blog_url":"https://blog.fabric.microsoft.com/en-us/blog/introducing-the-http-and-mongodb-cdc-connectors-for-eventstream-inspired-by-you","feature_description":"This feature enables customers to develop or reuse their own Kafka connectors, or open-source Kafka connectors, when no pre-built streaming connector is available.With this capability, you can:- Customize your own connector at your own pace.- Run with no infrastructure to manage.- Reuse open-source connectors directly.","feature_name":"Eventstream supports customers to upload own connector","last_modified":"2026-08-05","product_id":"58cb90aa-4203-ef11-a1fd-000d3a36eea4","product_name":"Real-Time Intelligence","release_date":"Q3 2026","release_item_id":"60246c0e-762f-f011-8c4d-000d3a34671f","release_status":"Planned","release_type":"Public preview"},{"active":true,"blog_title":null,"blog_url":null,"feature_description":"Identify how applications like Activator and QuerySet contribute to Eventhouse activity. Analyze query volume and activity by application and identify unusual spikes to support informed capacity management.","feature_name":"Monitor Eventhouse activity by application","last_modified":"2026-08-05","product_id":"58cb90aa-4203-ef11-a1fd-000d3a36eea4","product_name":"Real-Time Intelligence","release_date":"Q2 2026","release_item_id":"38e581bb-4541-f111-88b5-6045bd0a8ec1","release_status":"Shipped","release_type":"General availability"},{"active":true,"blog_title":"Eventhouse Accelerated OneLake Table Shortcuts (Generally Available)","blog_url":"https://blog.fabric.microsoft.com/en-us/blog/eventhouse-accelerated-onelake-table-shortcuts-generally-available","feature_description":"You can now join data from OneLake shortcuts in update policies. Use this for dimension lookups, such as enriching ingested fact events with customer, device, or product attributes stored in OneLake shortcut data.The shortcut-backed external table must have Query Acceleration Policy enabled, and Hot duration must cover all data.","feature_name":"Eventhouse Update Policies referencing Accelerated Shortcuts","last_modified":"2026-08-04","product_id":"58cb90aa-4203-ef11-a1fd-000d3a36eea4","product_name":"Real-Time Intelligence","release_date":"Q3 2026","release_item_id":"a144449e-0780-f111-ab0f-6045bd0a8ec1","release_status":"Shipped","release_type":"General availability"},{"active":true,"blog_title":null,"blog_url":null,"feature_description":"Branch workspace admin profile (aka. admin delegation) lets developers use the branch-out experience without needing create-workspace or assign-capacity permissions. Workspace admins keep full control through pre-configured guardrails while unblocking developer workflows. Capabilities:  - Developers without create-workspace or assign-capacity permissions can perform branch-out seamlessly  - Admins pre-configure profile to ensure guardrails for branch workspaces: developer role, capacity assignment and admin list.","feature_name":"Git Integration - Branch workspace admin profile","last_modified":"2026-08-03","product_id":"c6da6b3b-ded6-ee11-9079-000d3a310f67","product_name":"Fabric Developer Experiences","release_date":"Q3 2026","release_item_id":"79538350-662c-f111-88b4-6045bd0a886d","release_status":"Planned","release_type":"Public preview"},{"active":true,"blog_title":null,"blog_url":null,"feature_description":"List slicer with drop down mode and advanced search options.","feature_name":"List slicer with dropdown mode","last_modified":"2026-07-31","product_id":"642a8375-05fc-ee11-a1ff-000d3a341a60","product_name":"Power BI","release_date":"Q4 2026","release_item_id":"ba851f2d-d21f-f111-8341-6045bd0a8ec1","release_status":"Planned","release_type":"General availability"},{"active":true,"blog_title":null,"blog_url":null,"feature_description":"Conditional formatting to be available for series in Power BI visuals. This includes lines, markers, and legends.","feature_name":"Conditional formatting for lines and series/labels in Power BI visuals","last_modified":"2026-07-31","product_id":"642a8375-05fc-ee11-a1ff-000d3a341a60","product_name":"Power BI","release_date":"Q3 2026","release_item_id":"853c11fa-d11f-f111-8341-6045bd0a8ec1","release_status":"Shipped","release_type":"General availability"},{"active":true,"blog_title":"Announcing Data Clustering in Fabric Data Warehouse (Preview)","blog_url":"https://blog.fabric.microsoft.com/en-us/blog/announcing-data-clustering-in-fabric-data-warehouse-preview","feature_description":"Data Clustering enables faster read performance by allowing users to specify columns for co-locating data on ingestion and perform file skipping on read.","feature_name":"Data Clustering","last_modified":"2026-07-30","product_id":"fa3a73cd-dcd6-ee11-9079-000d3a310f67","product_name":"Data Warehouse","release_date":"Q4 2026","release_item_id":"5cd4b9a0-1322-f011-998a-0022480939f0","release_status":"Planned","release_type":"General availability"},{"active":true,"blog_title":"Introducing support for Workspace Identity Authentication in Fabric Connectors","blog_url":"https://blog.fabric.microsoft.com/en-us/blog/announcing-support-for-workspace-identity-authentication-in-new-fabric-connectors-and-for-dataflow-gen2","feature_description":"Workspace identity auth support for Eventstream Event hub source. Customers can use workspace identity to do the authentication between Eventstream and their event hub source.","feature_name":"Workspace identity auth support for Eventstream Event hub source","last_modified":"2026-07-30","product_id":"58cb90aa-4203-ef11-a1fd-000d3a36eea4","product_name":"Real-Time Intelligence","release_date":"Q3 2026","release_item_id":"246e8c98-903f-f111-88b5-6045bd00f798","release_status":"Shipped","release_type":"Public preview"},{"active":true,"blog_title":"Mastering Declarative Data Transformations with Materialized Lake Views","blog_url":"https://blog.fabric.microsoft.com/en-us/blog/mastering-declarative-data-transformations-with-materialized-lake-views","feature_description":"Fabric data engineers today write 80-100+ lines of boilerplate PySpark to ingest CSV and Parquet files into Delta tables - handling file discovery, schema inference, incremental refresh, schema drift, and error recovery manually. This feature introduces a simple Spark SQL DDL surface (CREATE MATERIALIZED LAKE VIEW ... FROM OneLake_Files OPTIONS (...)) that declaratively handles all of this. It includes automatic schema evolution (or strict fixed-schema mode), three refresh modes (append_only, mirror, full), built-in error handling, structured user telemetry on files and lakehouse-level DAG lineage.","feature_name":"Declarative file data ingestion experience in Fabric Materialized Lake Views","last_modified":"2026-07-30","product_id":"a731518f-36ca-ee11-9079-000d3a341a60","product_name":"Data Engineering","release_date":"Q3 2026","release_item_id":"14254506-0f3f-f111-88b5-6045bd00f798","release_status":"Planned","release_type":"Public preview"},{"active":true,"blog_title":"Time-Travelling through data: The Magic of Table clones","blog_url":"https://blog.fabric.microsoft.com/en-us/blog/time-travelling-through-data-the-magic-of-table-clones","feature_description":"Ability to clone warehouse across workspaces","feature_name":"Warehouse Clones","last_modified":"2026-07-29","product_id":"fa3a73cd-dcd6-ee11-9079-000d3a310f67","product_name":"Data Warehouse","release_date":"Q1 2027","release_item_id":"e240d768-fc21-f011-998a-0022480939f0","release_status":"Planned","release_type":"Public preview"},{"active":true,"blog_title":"Introducing the New Deployment Pipelines design: A leap forward in deployment Efficiency","blog_url":"https://blog.fabric.microsoft.com/en-us/blog/introducing-the-new-deployment-pipelines-design-a-leap-forward-in-deployment-efficiency","feature_description":"**Release:** Public Preview  |  **Product area:** Fabric CI/CD**Deployment plan** is a new first-class Fabric workspace item that lets you **define, order, and automate** how your content is deployed across environments.Instead of relying on system-inferred lineage order, you author a plan on a **visual canvas** (with **YAML as the source of truth**) to:- **Declare the exact sequence** in which items deploy- **Add pre and post deployment steps** -- for example, running a Notebook to hydrate a Lakehouse, or a Data Pipeline before dependent items go liveDeployment plans **attach to the deployment operations available in Fabric**, including **Git** (branch-out, initial sync, update from Git), **Deployment Pipelines**, **Bulk Import**, and the **CI/CD library**, and are **honored at deploy time**.The result: every promotion follows your intended orchestration and produces a **working, reproducible solution**, not just a set of deployed definitions.","feature_name":"Deployment Plan","last_modified":"2026-07-29","product_id":"c6da6b3b-ded6-ee11-9079-000d3a310f67","product_name":"Fabric Developer Experiences","release_date":"Q4 2026","release_item_id":"fbee65ff-2b8b-f111-ab0f-6045bd03ee11","release_status":"Planned","release_type":"Public preview"},{"active":true,"blog_title":"Configurable Data Retention in Microsoft Fabric Warehouse (Preview)","blog_url":"https://community.fabric.microsoft.com/t5/Fabric-Updates-Blog/Configurable-Data-Retention-in-Microsoft-Fabric-Warehouse/ba-p/5181211","feature_description":"Ability to configure the data warehouse retention between 1 to 120 days;","feature_name":"Configurable Retention between 1-120 days","last_modified":"2026-07-29","product_id":"fa3a73cd-dcd6-ee11-9079-000d3a310f67","product_name":"Data Warehouse","release_date":"Q4 2026","release_item_id":"dfb17dba-0d22-f011-998a-0022480939f0","release_status":"Planned","release_type":"General availability"},{"active":true,"blog_title":"Data Warehouse Utilization Reporting in Fabric Capacity Metrics App","blog_url":"https://blog.fabric.microsoft.com/en-us/blog/data-warehouse-utilization-reporting-in-fabric-capacity-metrics-app","feature_description":"Shortcuts in Fabric DW allow users to directly access and query data that is present in internal and external data sources, without loading them into Fabric DW. 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More precise than table-level detection (which blocks any concurrent changes to the same table).What It Does?Scope: Operates at the file level (e.g., Parquet files in Fabric DW), rather than at the table or row level.Goal: Detect overlapping changes (updates, deletes) to the same file during concurrent transactions.Trigger: When a transaction tries to commit changes, the system checks if any newer manifests indicate modifications to the same file since the transaction started.Lays groundwork for even finer-grained detection (row-level) in later releases.","feature_name":"File-Level write-write conflict detection (Generally Available)","last_modified":"2026-07-29","product_id":"fa3a73cd-dcd6-ee11-9079-000d3a310f67","product_name":"Data Warehouse","release_date":"Q4 2026","release_item_id":"b7e155c6-94bf-f011-bbd3-000d3a5b0efa","release_status":"Planned","release_type":"General availability"},{"active":true,"blog_title":"Large string and binary values in Fabric Data Warehouse and SQL analytics endpoint for mirrored items (Generally Available)","blog_url":"https://blog.fabric.microsoft.com/en-us/blog/large-string-and-binary-values-in-fabric-data-warehouse-and-sql-analytics-endpoint-for-mirrored-items-general-availability","feature_description":"SQL analytics endpoints of Lakehouses will support large string and binary data using VARCHAR(MAX) and VARBINARY(MAX) types up to 16 MB.","feature_name":"VARCHAR(MAX) support in SQL analytics endpoint of Lakehouses","last_modified":"2026-07-29","product_id":"fa3a73cd-dcd6-ee11-9079-000d3a310f67","product_name":"Data Warehouse","release_date":"Q3 2026","release_item_id":"f4c0ce02-2e61-f011-bec2-000d3a302e4a","release_status":"Planned","release_type":"General availability"},{"active":true,"blog_title":"New Features and Enhancements for Virtual Network Data Gateway","blog_url":"https://blog.fabric.microsoft.com/en-us/blog/new-features-and-enhancements-for-virtual-network-data-gateway","feature_description":"For VNet data gateways, the fixed node setup can be inefficient during high-demand periods. To improve this, we're introducing auto-scaling, which dynamically adjusts the number of nodes based on demand.","feature_name":"Gateways - Autoscaling gateway clusters for VNet Gateway","last_modified":"2026-07-29","product_id":"a821f83f-dbd6-ee11-9079-000d3a310f67","product_name":"Data Factory","release_date":"Q3 2026","release_item_id":"78dc21fc-7420-f011-998a-0022480939f0","release_status":"Shipped","release_type":"Public preview"},{"active":true,"blog_title":"New Dataflow Gen2 data destinations and experience improvements","blog_url":"https://blog.fabric.microsoft.com/en-us/blog/new-dataflow-gen2-data-destinations-and-experience-improvements","feature_description":"We are introducing PostgreSQL as a new data destination for Dataflow Gen2, enabling customers to publish transformed data from Microsoft Fabric directly into PostgreSQL databases using Dataflow Gen2's low-code Power Query experience.This release expands Dataflow Gen2's destination ecosystem to better support operational, analytical, and application integration scenarios, giving customers a simple and flexible way to operationalize Fabric-based data transformations in PostgreSQL environments.Key benefits and scenarios:* Publish curated outputs from Dataflow Gen2 directly into PostgreSQL databases and tables* Support operational reporting, application integration, and downstream analytics scenarios using PostgreSQL as a serving layer* Enable teams to prepare, standardize, and reshape data in Fabric before delivering it to PostgreSQL-based applications, services, or analytics workloadsThe PostgreSQL data destination helps customers simplify data movement and reduce the need for custom pipelines by combining Fabric's scalable transformation capabilities with PostgreSQL's broad ecosystem compatibility and adoption.This release is part of our broader effort to make Dataflow Gen2 a flexible, low-code transformation layer across data platforms, with continued investments planned to expand destination support and simplify end-to-end data integration experiences in Fabric.","feature_name":"Dataflows - New Destination: PostgreSQL","last_modified":"2026-07-29","product_id":"a821f83f-dbd6-ee11-9079-000d3a310f67","product_name":"Data Factory","release_date":"Q3 2026","release_item_id":"78a9449f-c85e-f111-a826-000d3a366c85","release_status":"Shipped","release_type":"Public preview"},{"active":true,"blog_title":"Workspace-Level Private Link in Microsoft Fabric (Generally Available)","blog_url":"https://blog.fabric.microsoft.com/en-us/blog/announcing-general-availability-of-workspace-level-private-link-in-microsoft-fabric","feature_description":"Private link allows customers to connect to their SQL DBs via a private endpoint from the customer's virtual network. Workspace level private links will give customers the flexibility to use private link connection to specific workspace(s) which have high security requirements and contain sensitive data while their other workspace can be open to public.","feature_name":"Workspace level Private Link for SQL database","last_modified":"2026-07-29","product_id":"347da228-ea54-ef11-a317-0022480a694f","product_name":"SQL database","release_date":"Q3 2026","release_item_id":"744ac485-321d-f011-9989-000d3a302e4a","release_status":"Planned","release_type":"Public preview"},{"active":true,"blog_title":"Introducing Planning in Microsoft Fabric IQ: From historical data to forecasting the future","blog_url":"https://blog.fabric.microsoft.com/en-US/blog/introducing-planning-in-microsoft-fabric-iq-from-historical-data-to-forecasting-the-future","feature_description":"Planning in Microsoft Fabric is a native enterprise planning capability that brings budgeting, forecasting, and scenario modeling directly into your data platform--eliminating silos between planning, analytics, and AI.Built into Microsoft Fabric, Planning enables business and data teams to collaboratively create, manage, and refine plans on top of governed, real-time data--powering faster, more informed decision-making across the organization.","feature_name":"Fabric Planning","last_modified":"2026-07-29","product_id":"cef5a30d-562f-f011-8c4d-6045bd096d8f","product_name":"IQ","release_date":"Q3 2026","release_item_id":"69db5ef2-7f01-f111-8406-000d3a36696c","release_status":"Shipped","release_type":"General availability"},{"active":true,"blog_title":"Outbound access protection for Data Factory (Generally Available)","blog_url":"https://blog.fabric.microsoft.com/en-US/blog/outbound-access-protection-for-data-factory-generally-available","feature_description":"We are delivering Outbound Access Protection for Operations Agent in Microsoft Fabric, enabling administrators to enforce workspace-level security controls on all outbound actions performed by AI-driven automation.With this capability, you canEnsure all outbound actions such as triggering Power Automate flows, executing Fabric jobs, or sending Teams notifications are governed by administrator-defined connection rules.Block outbound connections by default when OAP is enabled, permitting traffic only through approved endpoints to prevent unauthorized data movement.Leverage a hybrid enforcement model that applies direct checks for external services like Teams while using Activator-managed enforcement for workflow and job execution across workspaces.Outbound Access Protection is available in Public Preview for all Fabric customers using Operations Agent. Configure access rules from the workspace security settings.Tentative GA Scope: Activator OAP toggle for OAOntology OAP toggle for OAPower Automate OAP toggle for OA","feature_name":"Outbound access protection for Operations Agent","last_modified":"2026-07-29","product_id":"cef5a30d-562f-f011-8c4d-6045bd096d8f","product_name":"IQ","release_date":"Q3 2026","release_item_id":"675ce012-f144-f111-88b5-6045bd006301","release_status":"Shipped","release_type":"Public preview"},{"active":true,"blog_title":"Using Bulk Copy API for faster ingestion in Fabric Data Warehouse (Preview)","blog_url":"https://community.fabric.microsoft.com/t5/Fabric-Updates-Blog/Using-Bulk-Copy-API-for-faster-ingestion-in-Fabric-Data/ba-p/5195627","feature_description":"Fabric Data Warehouse will support the bcp utility and the TDS Bulk Load API, enabling high-performance data ingestion from a variety of client tools such as bcp, SSIS, and Azure Data Factory. This integration simplifies bulk data loading into Fabric DW and supports scalable, efficient workflows. Centralized support for these APIs ensures consistency across ingestion pipelines and improves interoperability with existing tools.<br/>An example of a bcp command that loads file content into a DW table:<br/>```bcp dbo.artists in gold_artist.txt -d TextDW -c -S myworkspace.datawarehouse.fabric.microsoft.com -G -U theuser@microsoft.com ```","feature_name":"BCP","last_modified":"2026-07-29","product_id":"fa3a73cd-dcd6-ee11-9079-000d3a310f67","product_name":"Data Warehouse","release_date":"Q2 2026","release_item_id":"d58f4693-ca80-ef11-ac21-6045bd062aa2","release_status":"Shipped","release_type":"Public preview"},{"active":true,"blog_title":null,"blog_url":null,"feature_description":"Fabric Data Warehouse will introduce string similarity and comparison functions based on Levenshtein and Jaro-Winkler algorithms. 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