What's New in v0.6.0

Version Compatibility

Milvus version pymilvus version Java SDK version
0.6.0 0.2.6 0.4.0


New features

  • CPU-only Milvus

    Milvus v0.6.0 provides Docker images for both CPU-only and GPU support Milvus. Milvus compilation on Docker is also supported on machines with or without GPU. #192

  • Table partitioning

    Add table partitioning funtion to secure fast query performance for incremental data. Partitioning APIs are added to Python, Java and C++ SDK to support partition creation, vector insertion into a specified partition and query against a specified partition, etc. #245

  • Experimental features

    The experimental features in Milvus are still under development and subject to change. They may contain unknown errors, and are intended for testing and user feedback gathering.

    • Mishards

    Propose Mishards, a Milvus sharding middleware, as the distributed deployment solution. Mishards provides unlimited extension of memory and computation capacity through request forwarding, read/write splitting, horizontal scalability and dynamic extension. #232

    • New index types

    Start supporting new experimental index types such as SPTAG-KDT, SPTAG-BKT, RNSG and IVFPQ. SPTAG#438 RNSG#554 IVFPQ#324

  • Index test reports

    Provide performance test reports for IVFFLAT, IVFSQ8 and IVFSQ8H indexes.


  • Milvus internal FAISS

    In addition to original FAISS, Milvus has made deep optimizations to increase query performance and support more index types such as IVFSQ8H. Now this part of internal FAISS is open sourced. #585

  • Multiple GPUs for index building

    Support index building by multiple GPUs to reduce index building and overall query time. You can specify multiple GPUs for index building process through Milvus configuration parameter build_index_resources. #414

Bug fixes

  • Solved the issue of increased memory usage during vector queries. #335
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