Changelog
Changelog
February 2025
Multivector Search ready and Table data preview available in Cloud UI
Features
- Multivector Search is now live: documents can be stored as contextualized vector lists. Fast multi-vector queries are supported at scale, powered by our XTR optimization.
Drop_index
added to SDK: users can remove unused or outdated indexes from your tables.- Explore Your Data at a Glance: preview sample data from
any table with a single click.
lancedb-cloud
- Search by Project/Table in Cloud UI: allow users to quickly locate the desired project/table.
lancedb-cloud
Bug fix
- FTS stability fix: Resolved a crash in Full Text Search (FTS) during flat-mode searches.
prefilter
parameter enforcement: Fixed a bug where the prefilter parameter was not honored in FTS queries.- Vector index bounds error: Addressed an out-of-bounds indexing issue during vector index creation.
distance_range()
compatibility: Fixed errors when performing vector searches withdistance_range()
on unindexed rows.- Error messaging improvements: Replaced generic HTTP 500 errors with detailed, actionable error messages for easier debugging.
January 2025
Support Hamming Distance and GPU based indexing ready
Features
- Support Hamming distance and binary vector: Added
hamming
as a distance metric (joiningl2
,cosine
,dot
) for binary vector similarity search. - GPU-Accelerated IVF-PQ indexing: Build IVF-PQ indexes 10x faster.
enterprise
- AWS Graviton 4 & Google Axion build optimizations: ARM64 SIMD acceleration cuts query costs.
enterprise
- float16 Vector Index Supports: reduce storage size while maintaining search quality.
- Self-Serve Cloud Onboarding: new workflow-based UI guides users for smooth experience.
lancedb-cloud
Bug fix
list_indices
andindex_stats
now always fetch the latest version of the table by default unless a specific version is explicitly provided.- Error message fix: Improved clarity for cases where
create_index
is called to create a vector index on tables with fewer than 256 rows. - TypeScript SDK fixes: Resolved an issue where 1createTable()
failed to correctly save embeddings and for
mergeInsert` not utilizing saved embeddings. lancedb#2065 - Multi-vector schema inference: Addressed an issue where the vector column could not be inferred for multi-vector indexes. lancedb#2026
- Hybrid search consistency: Fixed a discrepancy where hybrid search returned distance values inconsistent with standalone vector search. lancedb#2061
December 2024
Performant SQL queries at scale and more cost-effective vector search
Features
- Run SQL with massive datasets: added Apache Arrow flight-SQL protocol
to run SQL queries with billions of data and return in seconds.
enterprise
. - Accelerate vector search: added our Quantinized-IVF algorithm and other optimization techniques to improve QPS/core.
enterprise
- Azure Stack Router Deployment: route traffic efficiently to serve low query latency.
enterprise
- Distance range filtering. filter query results using
distance_range()
to return search results with a lowerbound, upperbound or a range [lance#3326]. - Full-Text Search(FTS) indexing options: configure tokenizers, stopword lists and more at FTS index creation.
Bug fix
- Full-text search parameters: Fixed an issue where full-text search index configurations were not applied correctly. lancedb#1928
- Float16 vector queries: Addressed a bug preventing the use of lists of Float16 values in vector queries. lancedb#1931
- Versioned
checkout
API: Resolved inconsistencies in thecheckout
method when specifying theversion
parameter. lancedb#1988 - Table recreation error: Fixed an issue where dropping and recreating a table with the same name resulted in a table creation error.