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Releases: weaviate/weaviate

v1.25.12 - RAFT fixes, Bm25 speedups and experimental repair endpoint

19 Aug 12:08
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Full Changelog: v1.25.11...v1.25.12

v1.24.22 - Replication with PATCH requests Fix, Vector index tombstone cleanup process Fix, Sentry & Profiling Improvements

08 Aug 16:34
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Full Changelog: v1.24.21...v1.24.22

v1.25.11 - Flat index improvements, Shard initialization and Raft Fixes

05 Aug 20:02
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Full Changelog: v1.25.10...v1.25.11

v1.25.10 - BM25 performance improvements, Vector index tombostone cleanup Fix, Sentry monitoring improvements

31 Jul 09:33
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Full Changelog: v1.25.9...v1.25.10

v1.25.9 - Hybrid search and Object store retrevial performance Fix, Updates with empty arrays and lists Fix, Sentry configuration improvements

26 Jul 16:53
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Full Changelog: v1.25.8...v1.25.9

v1.26.1 - Hybrid search performance Fix, Tenants create API Fix, New JinaAI Reranker module

23 Jul 16:38
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Full Changelog: v1.26.0...v1.26.1

v1.26.0 - Tenant Offloading, Multi-Target Vector Search, Scalar Quantization, Async Replication, Improved Range Queries

23 Jul 01:10
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Breaking Changes

Tenant activity status update requests now limited to 100 tenants. This is mitigated by the official client libraries which batch requests containing greater than 100 tenants in the background.

New Features

Tenant Offloading

Designed to optimize storage costs and improve resource utilization by separating compute and storage for inactive tenants. This new feature allows inactive tenant data to be offloaded to object storage, thus reducing expenses by not paying for compute resources when the data is not actively used. This initial iteration is S3 compatible, and official support for other object storage solutions is coming soon.

Multi-Target Vector Search

Significantly enhances search capabilities by allowing users to perform searches across multiple vectors simultaneously. This feature improves search efficiency and relevance by querying multiple vectors in a single operation, enabling more comprehensive and accurate data retrieval.

Scalar Quantization

Optimizes storage and enhances search performance. Scalar Quantization compresses vector data by mapping the vector's floating point values to integers, significantly reducing storage size while maintaining accuracy. This compression allows for faster and more efficient searches by decreasing the amount of data processed.

Async Replication

Ensures data consistency and integrity across replicas by asynchronously replicating changes. The Merkle tree-based implementation allows for efficient comparison and synchronization of data, identifying differences quickly and reducing replication lag. This asynchronous approach minimizes the impact on performance while ensuring that all replicas are up-to-date, providing a robust and reliable HA solution

Improved Range Queries

Introduces a new range filter index type, drastically improving the performance of large scale queries on numeric ranges.

Other

Module Improvements

Performance Improvements

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v1.26.0-rc.1 - Tenant Offloading, Scalar Quantization, Async Replication, Improved Range Queries, Multi-tenancy Compression Support

18 Jul 22:57
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This is a release candidate for the upcoming v1.26.0 release
A release candidate (RC) means the release is considered feature complete and has finished beta-testing. Any issues discovered during the RC phase will lead to new rc releases. The final rc release becomes the stable release. We're happy for your feedback about this pre-release.

This pre-release contains:

  • Tenant Offloading
  • Scalar Quantization
  • Async Replication
  • Improved Range Queries
  • Async Indexing Observability

v1.25.8 - Tombstone panic prevention Fix, HNSW PQ Fixes, GraphQL with primitive type named classes Fix, Schema V2 loading in metadata only mode Fix, Sentry logging integration

18 Jul 20:29
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Full Changelog: v1.25.7...v1.25.8

v1.24.21 - Tombstone panic prevention Fix, GraphQL with primitive type named classes Fix, Sentry logging integration

18 Jul 18:55
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Full Changelog: v1.24.20...v1.24.21