Critical zero-day flaw in MS SQL Server🔓|MariaDB acquires GridGain⚡|Build Your Own Data Lakehouse🤖

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Critical Microsoft SQL Server zero-day threatens security 🔓

MariaDB acquires GridGain to speed AI inference ⚡

Build Your Own Data Lakehouse: DIY Cost Guide🤖

Validio Raises $30M to Boost Enterprise Data Management💵

Also, check out the weekly Deep Dive - MS Fabric Interoperability

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DEEP DIVE

A detailed look into Microsoft Fabric, Part Four, Interoperability

In Microsoft Fabric, interoperability is not simply about offering a wide variety of connectors; it is the combination of a shared storage substrate, open data formats, multiple compute engines, and metadata-driven reuse that eliminates data silos and unnecessary duplication.

Here is a comprehensive overview of how Microsoft Fabric achieves interoperability across its ecosystem:

The Unified Storage Foundation: OneLake and Open Formats The core of Fabric’s architecture is OneLake, a single, unified logical data lake that acts as the "OneDrive for data" for an entire organization.

• Delta Lake Standard: All tabular data in Fabric is stored natively in the open-source Delta Lake (Parquet) format. This standardization allows disparate compute engines—such as Apache Spark, T-SQL (Data Warehouse and SQL analytics endpoints), and Kusto Query Language (KQL)—to simultaneously read and write to the same physical data footprint without proprietary translation layers.

• Apache Iceberg Interoperability: Fabric extends its open-format commitment through bidirectional metadata virtualization, allowing Apache Iceberg tables to be interpreted as Delta tables and vice versa, enabling seamless cross-platform catalog integration.

Zero-Copy Data Access and Virtualization Fabric minimizes data duplication through two primary virtualization and replication mechanisms:

• Shortcuts: Shortcuts act as virtual pointers to data stored internally in Fabric or externally in clouds like Azure Data Lake Storage (ADLS) Gen2, Amazon S3, Google Cloud Storage (GCS), and Dataverse. When an analytical engine queries a shortcut, it performs an in-place I/O operation against the source, bypassing the need to copy data into OneLake.

• Mirroring: For operational databases (such as Azure Cosmos DB, Azure SQL, Snowflake, and PostgreSQL), mirroring provides continuous, near real-time replication into OneLake. It converts transactional data into analytics-ready Delta tables and automatically generates a SQL analytics endpoint for immediate T-SQL querying, eliminating complex ETL pipelines.

Cross-Engine and Business Intelligence (BI) Integration Fabric decouples storage from compute, allowing specialized engines to interact with the same data.

• Direct Lake Mode: This feature bridges data engineering and business intelligence by allowing the Power BI VertiPaq engine to read Delta Parquet files directly from OneLake. It delivers the high performance of cached "Import mode" without the latency and management overhead of actually copying or refreshing the data.

• GraphQL API: For application developers, Fabric provides a unified API for GraphQL. This layer abstracts backend complexities, allowing applications to query data across lakehouses, warehouses, and SQL databases in a single API call without requiring custom backend code.

Cross-Platform and Cross-Tenant Collaboration Fabric is designed to integrate deeply with the broader external data ecosystem and across organizational boundaries:

• Databricks and Snowflake Partnerships: Fabric allows Azure Databricks Unity Catalog to query OneLake data directly without copying it. Similarly, bidirectional interoperability with Snowflake allows Fabric workloads to run directly on Snowflake-managed Iceberg tables via shortcuts.

• External Data Sharing: Organizations can share data from their OneLake in-place with users in an entirely different Fabric tenant. This creates a read-only shortcut in the consumer's tenant, allowing secure cross-company collaboration without duplicating datasets.

Unified Security and Governance Maintaining governance across multiple engines is a historical challenge that Fabric addresses through integrated security layers:

• Microsoft Purview: Built directly into Fabric, Purview provides centralized data discovery, end-to-end lineage tracking, Data Loss Prevention (DLP), and sensitivity labels that automatically follow data as it moves or is exported.

• OneSecurity (OneLake Security): Microsoft is actively unifying data access controls through OneLake Security. This data-plane role-based access control (RBAC) model defines security rules (such as folder, table, row, and column-level security) centrally in OneLake. Once defined, these rules are consistently enforced regardless of whether the user accesses the data via Spark, T-SQL, or Power BI.

Gladstone Benjamin

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