RAG and retrieval pipelines
You need tight control over documents, embeddings, and their versions for retrieval.
Choose Deeplake
Medium-High confidence
- Documents and embeddings evolve over time
- Need lineage between raw data and vectors
- Want unified storage for text and embeddings
Versioned datasets reduce retrieval drift and make it clear which embeddings power each release.
Expected gains
- Clear lineage for embeddings
- Fewer production regressions
- Simpler pipeline maintenance
Choose Vector DB only
Medium confidence
- Stable document set
- Embedding refresh is rare
- Do not need dataset versioning
Vector databases are strong when only search is required.
Operational safety signals
- Rollback to previous embedding set
- Structured metadata for audits
Explore more use cases
See additional decision guides tailored to different workflows.