Vector search for any cloud: Run on your storage, not theirs.

LanceDB runs natively on S3, GCS, or Azure Blob with compute-storage separation. Same code, any cloud. No lock-in, no managed service markup.

Tomorrow's AI is being built on LanceDB today

Vector search without the Azure markup

Azure AI Search is convenient but expensive. LanceDB runs on Azure Blob Storage — same region, same security, fraction of the cost. Native hybrid search without Azure's per-query pricing.

Azure AI Search LanceDB
Cost Azure managed service pricing Azure Blob storage rates. Up to 100x savings.
Search Vector + semantic ranking Native vector + full-text + SQL hybrid in one query.
Portability Azure-only Same code runs on any cloud.
Best for Azure-native shops wanting convenience Cost-efficient vector search on Azure.

Scale beyond Vertex rate limits

Vertex AI is great for GCP ML workflows. But vector search is rate-limited and priced per query. LanceDB runs on GCS with no API limits and native hybrid search.

Vertex AI Vector Search LanceDB
Cost Per-query pricing GCS storage rates. Up to 100x savings.
Limits API rate limits No artificial limits. 20K+ QPS.
Search Vector search only Native vector + full-text + SQL hybrid in one query.
Best for Light vector search in Vertex pipelines High-volume vector workloads on GCP

BigQuery for analytics. LanceDB for serving.

BigQuery is an analytics engine with vector features bolted on. LanceDB is purpose-built for low-latency vector serving with native hybrid search. Use both — BigQuery for batch, LanceDB for real-time.

BigQuery Vector Search LanceDB
Latency Analytics-optimized (seconds) Serving-optimized (milliseconds).
Search Vector search in SQL Native vector + full-text + SQL hybrid in one query.
Cost model Bytes scanned pricing Object storage rates.
Best for Vector analytics at rest Real-time vector search in production.
noize

Talk to Engineering

Or try LanceDB OSS — same code, scales to Cloud.