Postgres full-text/vector search & analytics
ParadeDB is a Postgres extension that adds full-text search with BM25 scoring, vector retrieval, and real-time analytics/aggregations directly into Postgres.
Solves the same problem with a different architecture or at a different layer. Expect to rewrite the integration.
Choose it when you want a standalone AI-native hybrid search database with dense/sparse/tensor vectors, under Apache-2.0 instead of a Postgres extension.
The AI-native database built for LLM applications, providing incredibly fast hybrid search of dense vector, sparse vector, tensor (multi-vector), and full-text.
Choose it when you need an all-in-one AI-native search database unifying vector, text, structured, and semi-structured data outside Postgres.
The AI-Native Search Database. Best for agent storage, it unifies vector, text, structured, and semi-structured data into a single engine. This all-in-one database makes agents smarter, easier to run, and more stable.
Choose it when you need a mature, distributed AI search platform at large scale instead of a Postgres-embedded extension.
The AI search platform
Choose it when you want a fast, easily deployable search server API with typo tolerance and hybrid search, not tied to Postgres.
A lightning-fast search engine API bringing AI-powered hybrid search to your sites and applications.
Choose it when you need a standalone BSD-licensed vector database with hybrid search and structured filtering outside Postgres.
Weaviate is an open-source vector database that stores both objects and vectors, allowing for the combination of vector search with structured filtering with the fault tolerance and scalability of a cloud-native database.
Choose it when you need a high-performance standalone search database with SQL and real-time full-text/vector/hybrid search under GPL.
Open-source search database for full-text, vector, and hybrid search with real-time indexing and SQL.
Choose it when you need a tiny in-process or edge search/RAG library in TypeScript rather than a server-side Postgres extension.
🌌 A complete search engine and RAG pipeline in your browser, server or edge network with support for full-text, vector, and hybrid search in less than 2kb.
Choose it when you want an in-memory, typo-tolerant search engine with simple deployment and GPL licensing, outside Postgres.
Open Source alternative to Algolia + Pinecone and an Easier-to-Use alternative to ElasticSearch ⚡ 🔍 ✨ Fast, typo tolerant, in-memory fuzzy Search Engine for building delightful search experiences
Choose it when you want an embedded retrieval library for multimodal AI with serverless deployment rather than a Postgres extension.
Developer-friendly OSS embedded retrieval library for multimodal AI. Search More; Manage Less.
Choose it when you need an in-process Rust search library or multi-tenant server with vector and lexical search under Apache-2.0.
SeekStorm: vector & lexical search - in-process library & multi-tenancy server, in Rust.
Choose it when you need scalable MPP analytics plus hybrid search in a standalone cluster, not a Postgres extension.
Apache Doris is a real-time analytics and hybrid search database for AI agents.
An earlier or more limited way to do the job. Still the right call when you need something small, proven, or CPU-only.
Choose it when you only need a high-performance standalone vector database and don't need Postgres integration, full-text, or analytics.
Qdrant - High-performance, massive-scale Vector Database and Vector Search Engine for the next generation of AI. Also available in the cloud https://cloud.qdrant.io/
Choose it when you want a minimal, widely supported Postgres extension for vector search only, without BM25 full-text or columnar analytics.
Open-source vector similarity search for Postgres
Choose it when you need a lightweight in-process vector database only, without full-text search or analytics.
A lightweight, lightning-fast, in-process vector database
Choose it when you need a vector-only DBMS, accepting GPL and a less active ecosystem versus Postgres-based options.
Epsilla is a high performance Vector Database Management System
Choose it when you need a distributed vector search engine specifically, without full-text or analytics.
Distributed vector search for AI-native applications
Choose it when you want a Postgres vector extension and accept a stale, less-maintained project; narrower than ParadeDB.
PostgreSQL vector database extension for building AI applications
Does the same job, but ships as an app. Useful to a person, not swappable into a codebase.
Choose it when you want a ready-to-deploy enterprise/site search server with crawling rather than building search into your own stack.
Open-source, self-hosted enterprise & site search server built on OpenSearch. Crawls web / file / DB / cloud sources, 20+ languages, REST API, and AI/RAG & semantic search. Apache-2.0.
These projects were analysed and named paradedb among their alternatives. The relationship is not symmetric — how paradedb rates them is a separate judgement, made when paradedb is analysed in its own right.
calls paradedb “Choose when you want full-text and vector search as Postgres extensions, uniting your database and search.”
For developers, who are building real-time data-driven applications, Redis is the preferred, fastest, and most feature-rich cache, data structure server, and document and vector query engine.
calls paradedb “Choose ParadeDB when you want full-text and hybrid search built into PostgreSQL for large-scale data without a separate search service.”
A lightning-fast search engine API bringing AI-powered hybrid search to your sites and applications.
calls paradedb “choose for a Postgres distribution with integrated full-text and vector retrieval, but AGPL licensing and Postgres scalability limits apply.”
Milvus is a high-performance, cloud-native vector database built for scalable vector ANN search
calls paradedb “Choose when you want analytics and search inside an existing Postgres service.”
DuckDB is an analytical in-process SQL database management system
calls paradedb “Choose when you want a Postgres extension that combines full-text and vector search with a familiar SQL interface, replacing a dedicated vector service.”
Qdrant - High-performance, massive-scale Vector Database and Vector Search Engine for the next generation of AI. Also available in the cloud https://cloud.qdrant.io/
calls paradedb “choose when you already run Postgres and want full-text and vector search inside that database rather than a dedicated search server”
Open Source alternative to Algolia + Pinecone and an Easier-to-Use alternative to ElasticSearch ⚡ 🔍 ✨ Fast, typo tolerant, in-memory fuzzy Search Engine for building delightful search experiences
calls paradedb “choose for full-text and vector search in one Postgres extension, but its API differs from pgvector.”
Open-source vector similarity search for Postgres
calls paradedb “Choose when you already run Postgres and want full-text + vector search in the same SQL database.”
Weaviate is an open-source vector database that stores both objects and vectors, allowing for the combination of vector search with structured filtering with the fault tolerance and scalability of a cloud-native database.
calls paradedb “Postgres-native search and analytics; choose it to keep application data, full-text, vector, and aggregations in one PostgreSQL deployment instead of adding Doris.”
Apache Doris is a real-time analytics and hybrid search database for AI agents.
calls paradedb “Postgres extension for full-text/vector; choose when already on Postgres and want unified queries.”
A lightweight, lightning-fast, in-process vector database
calls paradedb “Choose if you want search and vector retrieval inside PostgreSQL to avoid a separate search server; requires Postgres and uses a different query interface.”
Open-source search database for full-text, vector, and hybrid search with real-time indexing and SQL.
calls paradedb “Postgres extension for hybrid search; choose it if you want search inside your existing Postgres database.”
Developer-friendly OSS embedded retrieval library for multimodal AI. Search More; Manage Less.
calls paradedb “Postgres-native hybrid search extension; choose when you want SQL access and data stored in Postgres rather than an embedded JS library.”
🌌 A complete search engine and RAG pipeline in your browser, server or edge network with support for full-text, vector, and hybrid search in less than 2kb.
calls paradedb “Choose for full-text and vector search integrated into Postgres without distributed complexity.”
OceanBase is the unified distributed database for the AI era — open-source, multi-model, one engine for your most demanding workloads.
calls paradedb “Use when you want full-text/vector search and analytics inside Postgres without adding a separate warehouse engine.”
Data Agent Ready Warehouse : One for Analytics, Search, AI, Python Sandbox. — rebuilt from scratch. Unified architecture on your S3.
calls paradedb “Choose when you already live in Postgres and want full-text+vector search as an extension rather than running a separate Vespa cluster.”
The AI search platform
calls paradedb “Single-node PostgreSQL with built-in full-text and vector search, choose when you don't need horizontal scaling and prefer the Postgres ecosystem.”
TiDB is built for agentic workloads that grow unpredictably, with ACID guarantees and native support for transactions, analytics, and vector search. No data silos. No noisy neighbors. No infrastructure ceiling.