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We’re a lean team that likes to ship at incredibly high velocity.

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In Progress

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JOIN Improvements

  • Join pushdown (beta). Join pushdown pushes search predicates directly into the index for significantly better performance.
  • Scoring and highlighting across JOINs. BM25 score and snippet functions can be used in JOIN queries.
  • 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 more ORMs, like Prisma 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 are coming.
  • PaaS Providers. Official tutorials for hosting ParadeDB on more platform-as-a-service providers like Porter.run and others is coming. Railway, Render, and DigitalOcean are already available.

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Long Term

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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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Managed Cloud

  • Today, you can deploy ParadeDB self-hosted, on cloud platforms, or with ParadeDB BYOC. We’re also building ParadeDB Cloud, a fully managed ParadeDB: first-class search from Postgres, with a developer experience to match. Join the waitlist to get notified when it launches.

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Completed

  • Native vector search (beta). The ParadeDB index natively indexes pgvector’s vector type, addressing pgvector’s limitations around filtered queries — specifically, queries that combine vector similarity with metadata filters or full-text search predicates.

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Analytics

  • A custom scan node for aggregates. Plain SQL aggregates like COUNT, and clauses like GROUP BY, go through the same fast execution path as our aggregate UDFs.
  • Aggregate pushdown across joins. Aggregates over multi-table joins are pushed down into the index when every joined table has a ParadeDB index.
  • Parallel execution for joins and aggregates. Utilizes an MPP strategy that partitions joins and aggregates into multiple shared-nothing stages executed by parallel workers.

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Write Throughput

  • Background merging. Improves write performance by merging index segments asynchronously without blocking inserts.
  • Pending list. Buffers recent write before flushing them to the LSM tree.

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Improved UX

  • More intuitive index configuration. Overhaul the complicated JSON WITH index options.
  • More ORM friendly. Overhaul the query builder functions to use actual column references instead of string literals.
  • New operators. In addition to the existing @@@ operator, introduce new operators for different query types (e.g. phrase, term, conjunction/disjunction).

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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, please check out our open roles!