Changelog
Changelog
March 2025
Enhanced Full-Text Search and Advanced Query Debugging Features
Features
- Enhanced Full-Text Search (FTS): Fuzzy Search & Boosting Now Available: it improves user experience with resilient, typo-tolerant searches and can surface the most contextually relevant results faster.
- New SDK APIs:
explain_plan
: Diagnose query performance and debug unexpected results by inspecting the execution plan.analyze_plan
: Analyze query execution metrics to optimize performance and resource usage. Such metrics include execution time, number of rows processed, I/O stats, and more.restore
: Revert to a specific prior version of your dataset and modify it from a verified, stable state.
- Scalar Indexing for Extended Data Types: LanceDB now supports scalar indexing on UUID columns of FixedSizeBinary type.
- Binary vector support in TypeScript SDK: LanceDB’s TypeScript SDK now natively supports binary vector indexing and querying with production-grade efficiency.
- Support S3-compatible object store: Extended LanceDB Enterprise deployment
to work with S3-compatible object stores, such as Tigris, Minio and etc.
enterprise
Bug fix
- Improved Merge insert performance: Enhanced the merge-insert operation to reduce error rates during upsert operations, improving data reliability.[lance#3603].
- Batch Ingestion Error: Updated error codes for batch ingestion failures from 500 to 409 to accurately reflect resource conflict scenarios.
- Cloud Signup Workflow Fix: Resolved an issue where users encountered a blank page after organization creation during the Cloud signup process.
- Table Preview Data Display Issue: Fixed a bug causing the table preview
page to show a generic “Something went wrong” error for datasets containing
datetime
columns, which previously prevented data inspection. - Rate Limit Error Clarity: Added explicit error messaging for system rate limits (e.g., API keys per table), replacing vague notifications that confused users.
March 2025
Enhanced Full-Text Search and Advanced Query Debugging Features
Features
- Enhanced Full-Text Search (FTS): Fuzzy Search & Boosting Now Available: it improves user experience with resilient, typo-tolerant searches and can surface the most contextually relevant results faster.
- New SDK APIs:
explain_plan
: Diagnose query performance and debug unexpected results by inspecting the execution plan.analyze_plan
: Analyze query execution metrics to optimize performance and resource usage. Such metrics include execution time, number of rows processed, I/O stats, and more.restore
: Revert to a specific prior version of your dataset and modify it from a verified, stable state.
- Scalar Indexing for Extended Data Types: LanceDB now supports scalar indexing on UUID columns of FixedSizeBinary type.
- Binary vector support in TypeScript SDK: LanceDB’s TypeScript SDK now natively supports binary vector indexing and querying with production-grade efficiency.
- Support S3-compatible object store: Extended LanceDB Enterprise deployment
to work with S3-compatible object stores, such as Tigris, Minio and etc.
enterprise
Bug fix
- Improved Merge insert performance: Enhanced the merge-insert operation to reduce error rates during upsert operations, improving data reliability.[lance#3603].
- Batch Ingestion Error: Updated error codes for batch ingestion failures from 500 to 409 to accurately reflect resource conflict scenarios.
- Cloud Signup Workflow Fix: Resolved an issue where users encountered a blank page after organization creation during the Cloud signup process.
- Table Preview Data Display Issue: Fixed a bug causing the table preview
page to show a generic “Something went wrong” error for datasets containing
datetime
columns, which previously prevented data inspection. - Rate Limit Error Clarity: Added explicit error messaging for system rate limits (e.g., API keys per table), replacing vague notifications that confused users.
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.