Roadmap

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In Progress

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Vector Search

• Native vector search (beta). Search pgvector’s vector type with the ParadeDB index, combining vector similarity with metadata filters and full-text search in a single query.
• Incremental index maintenance. Vector search quality currently degrades as indexed rows are updated. We are implementing SPFresh to maintain index quality incrementally.
• Remaining pgvector types. Implement support for pgvector’s halfvec, sparsevec, and bit types.

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JOIN Improvements

• Accelerated JOINs (beta). Apply search filters and aggregates directly in the index to speed up queries that join tables.
• Smarter JOIN planning for search indexes. Apply index-aware optimizations and cost estimation strategies when multiple ParadeDB-indexed tables are joined.

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Ecosystem Integrations

• ORMs. Official support for Prisma, Diesel, and others is coming. Drizzle, Django, SQLAlchemy, Rails, and Entity Framework Core are already available.
• AI Frameworks. Official support for LangChain, LlamaIndex, CrewAI, and others is coming.

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Cloud Platform

• Distributed search. Scale search across multiple nodes to support larger datasets and workloads.
• Reranking. Improve search relevance by reranking retrieved results with dedicated ranking models.

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Planned

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Object Storage

• Offload index segments to object storage. Reduce storage costs for large datasets by storing index segments in object storage.

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Deeper Analytics Improvements

• Push Postgres visibility rules into the index. This is currently a filter applied post index scan that adds overhead to large scans.

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We’re Hiring

We’re tackling some of the hardest and (in our opinion) most impactful problems in Postgres. If you want to be a part of it, check out our open roles!