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ParadeDB

Elastic-quality search and analytics inside Postgres, delivered as a single extension — a modern alternative to Elasticsearch.

Starting at$0
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💡

In Plain English

Elastic-quality search and analytics inside Postgres, delivered as a single extension — a modern alternative to Elasticsearch.

OverviewFeaturesPricingUse CasesFAQ

Overview

ParadeDB is an open-source Postgres extension that bolts production-grade full-text search, BM25 ranking, faceting, fuzzy and semantic search, and analytical query acceleration directly onto a normal Postgres database. The pitch resonates with teams who have lived through the operational pain of running Elasticsearch alongside their primary database: instead of dual-writing to ES, dealing with replication lag, and reconciling schemas, you keep one source of truth (Postgres) and add ParadeDB as an extension that gives you pgsearch for BM25 search, pglakehouse for fast analytics over object storage, and integrations with pgvector and embedding providers for hybrid vector + keyword retrieval. Because everything is SQL, ORMs, BI tools, and existing app code keep working. For AI workloads ParadeDB has positioned itself as a strong RAG backend and increasingly as an MCP-friendly knowledge layer — search, filter, and rank documents through a familiar Postgres connection that agents can hit via an MCP database tool. The core is open source under PostgreSQL license; the managed ParadeDB Cloud offering provides hosted clusters with point-in-time recovery, monitoring, and SLAs, with paid tiers usage-based and Enterprise plans for dedicated clusters. Teams adopt ParadeDB to retire an Elasticsearch deployment, to add fast hybrid search to an existing Postgres app, or to ground LLM agents on structured business data without leaving the relational world.

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Key Features

Feature information is available on the official website.

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Pricing Plans

Open Source

$0

    Cloud

    Usage-based

      Enterprise

      Custom

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        Best Use Cases

        🎯

        Replacing Elasticsearch with a Postgres-native stack

        ⚡

        Adding production search to SaaS apps

        🔧

        RAG over structured business data

        🚀

        Hybrid search for agent retrieval tools

        💡

        Analytical dashboards over operational data

        Pros & Cons

        ✓ Pros

        • ✓One database to operate instead of Postgres + Elasticsearch
        • ✓Plain SQL means existing app code and ORMs keep working
        • ✓Hybrid keyword + vector search is a strong RAG primitive
        • ✓PostgreSQL-license core avoids the Elastic license drama
        • ✓Managed cloud has HA, PITR, and monitoring without DevOps work

        ✗ Cons

        • ✗Not a fit for massive horizontally-distributed search at OpenSearch scale
        • ✗pg_lakehouse analytics newer than Snowflake or DuckDB equivalents
        • ✗Requires Postgres tuning skills to get peak performance
        • ✗Documentation still maturing compared to Elastic's decade-old corpus
        • ✗Migrating off Elasticsearch requires reindexing application logic, not just data

        Frequently Asked Questions

        How much does ParadeDB cost?+

        ParadeDB pricing starts at $0. They offer 3 pricing tiers.
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        Quick Info

        Category

        Search Engine

        Website

        www.paradedb.com
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