ClickHouse vs Chroma

ClickHouse expands collaboration with Microsoft, bringing Fabric integration, deeper OneLake interoperability, and enterprise deployment flexibility

ClickHouse announced a significant expansion of its strategic collaboration with Microsoft at The European Microsoft Fabric + SQL Community Conference in Barcelona on September 29, 2026. The expansion includes the public preview of the ClickHouse workload for Microsoft Fabric, general availability of OneLake read, public preview of OneLake write, and availability of ClickHouse Bring Your Own Cloud (BYOC) in the Microsoft Marketplace. These capabilities aim to enable sub-second analytics on OneLake data and provide enterprise deployment flexibility without data duplication.

• ClickHouse announced the expanded Microsoft collaboration on September 29, 2026 at The European Microsoft Fabric + SQL Community Conference in Barcelona.
• The ClickHouse workload for Microsoft Fabric is now available in public preview through the Fabric workload hub.
• ClickHouse support for reading Apache Iceberg tables from OneLake using OneLake Table APIs is now generally available.

ClickHouse expands collaboration with Microsoft, bringing Fabric integration, deeper OneLake interoperability, and enterprise deployment flexibility

On September 29, 2026, at The European Microsoft Fabric + SQL Community Conference in Barcelona, ClickHouse announced an expanded strategic collaboration with Microsoft. The announcement includes the public preview of the native ClickHouse workload for Microsoft Fabric, general availability of OneLake read, public preview of OneLake write, and availability of ClickHouse BYOC in the Microsoft Marketplace. These capabilities let joint customers query OneLake data at sub-second speeds without copying data, while BYOC provides managed ClickHouse Cloud inside a customer's Azure tenant with procurement via Microsoft agreements.

• On September 29, 2026, ClickHouse announced the expanded collaboration with Microsoft at The European Microsoft Fabric + SQL Community Conference in Barcelona.
• The native ClickHouse workload for Microsoft Fabric is now available in public preview through the Fabric workload hub, enabling sub-second analytics on OneLake queries.
• ClickHouse support for reading Apache Iceberg tables from OneLake using OneLake Table APIs is generally available; writing Iceberg tables to OneLake is in public preview.

ClickHouse appoints Mike Scarpelli, former Snowflake and ServiceNow CFO, to Board of Directors

ClickHouse, a leader in real-time analytics, data warehousing, observability, and AI/ML, today announced the appointment of Michael Scarpelli to its Board of Directors.

AI Agents Need Vector Databases for Memory

This technical blog post explains why retrieval-backed long-term memory for AI agents is best implemented with vector databases. It defines three memory types (working, long-term, episodic), outlines the memory stack (embedding model, vector store, chunking, metadata), recommends practical tooling (pgvector, Qdrant, Chroma) and embedding-dimension trade-offs, and provides a minimal Python example using pgvector and OpenAI embeddings. The author lists common production failure modes (stale memory, poor chunking, blind cosine similarity, context overflow, cost, privacy, and silent quality rot) and a practitioner's checklist for safe, private, and maintainable memory-enabled agents.

• Vector databases enable retrieval-backed long-term memory for agents by returning semantically similar chunks via embeddings and ANN search.
• Author recommends tooling trade-offs: pgvector (Postgres extension) for most production cases, Qdrant for heavy metadata filtering/scale, and Chroma for quick prototypes.
• Embedding dimension and model choice trade quality against cost; 768 dimensions is suggested as a sane production default.