ClickHouse vs Neo4j

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.

Neo4j GraphAware Financial Crime Intelligence debuts for full-cycle detection, investigation & prevention

On September 16, 2026, Neo4j announced Neo4j GraphAware Financial Crime Intelligence, a graph-native detection and investigation solution for banks and insurers to prevent financial crime. It is built on a reusable knowledge layer for enterprise AI and is the first milestone since Neo4j closed its acquisition of GraphAware in August 2026. The solution covers the full crime cycle—Signal, Alert, Investigate, Decide—and is available now.

• Neo4j announced Neo4j GraphAware Financial Crime Intelligence on September 16, 2026, as a graph-native detection and investigation solution for banks and insurers.
• The release is the first milestone after Neo4j closed its acquisition of GraphAware in August 2026.
• The OECD reported that $442 billion was lost to consumer fraud globally in 2025; Interpol reported over 5,800 arrests across 97 countries from a single global fraud bust in July 2026.

Introducing Neo4j GraphAware Financial Crime Intelligence

Neo4j introduced Neo4j GraphAware Financial Crime Intelligence, a graph-native foundation for financial crime operations. The solution unifies internal and external data into an entity-resolved knowledge layer to help banking and insurance teams detect connected fraud patterns, investigate alerts with full context, and make defensible decisions. It includes predefined detection models and works alongside existing detection engines and case management systems.

• Neo4j announced Neo4j GraphAware Financial Crime Intelligence on September 15, 2026.
• The solution provides a graph-native knowledge layer that continuously integrates and enriches internal and external data into an entity-resolved graph.
• It targets fraud investigations, AML and transaction monitoring, KYC/customer due diligence, sanctions screening, mule detection, and insurance claims investigations.

Benchmark of Five Managed Graph Databases

A reproducible benchmark comparing CognoDB Cloud, Neo4j AuraDB, Memgraph, FalkorDB and ArangoDB revealed major pitfalls in naive measurement: geographic placement of managed instances skewed raw latency numbers, server-reported execution time (via Bolt drivers) is required for fair engine-to-engine comparison, and CognoDB v0.9.11 exhibited a background-indexing behaviour that caused indexed lookups to return no results while an index was building, silently dropping relationship writes. Concurrency characteristics differed: cloud-hosted databases scaled with client concurrency due to network latency hiding server idle time, while local instances became CPU-bound and slowed. The author published the full harness and raw data on GitHub.

• Five graph databases were benchmarked: CognoDB Cloud, Neo4j AuraDB, Memgraph, FalkorDB and ArangoDB.
• Geographic placement of managed cloud instances (e.g., CognoDB in Google Cloud us-east4 and Neo4j AuraDB in Google's Singapore range) skewed raw wall-clock latency measurements.
• Using server-reported execution time via Bolt drivers (network excluded) was necessary to fairly compare engines in different regions.