LanceDB runs natively on S3, GCS, or Azure Blob with compute-storage separation. Same code, any cloud. No lock-in, no managed service 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. |
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 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. |
Or try LanceDB OSS — same code, scales to Cloud.