---
title: Welcome to ParadeDB
sidebarTitle: Introduction
description: Just use Postgres
canonical: https://www.paradedb.com/docs/start/introduction
---

import { Architecture } from "/snippets/architecture.jsx";

When Postgres queries get too slow, developers usually reach for systems like Elasticsearch. ParadeDB makes text and vector search, filters, facets, and joins fast in Postgres, so you can keep scaling with it.

ParadeDB accelerates these queries with a custom index, delivered through the `pg_search` Postgres extension. It runs inside standard Postgres, with no fork or sidecar process.

<Architecture />

## Who is ParadeDB for?

You're likely a good fit for ParadeDB if:

- **You're outgrowing Postgres full-text search or pgvector.** Your queries are getting slower, index builds are taking too long, or you're spending too much time working around feature limits and tuning performance.
- **You're building an application that needs both transactions and search.** You want user-facing search, RAG, or live dashboards without managing multiple databases and the pipelines that keep them in sync.
- **You're already syncing Postgres with an external search engine like Elasticsearch.** You're spending too much time on reindexing, data pipelines, and denormalization, and want to keep Postgres JOINs and transactional guarantees.

## Why Use ParadeDB?

Keep scaling with Postgres as your queries and workloads grow more demanding.

### No Second System

With external search engines and vector stores, you have to manage sync jobs, duplicated schemas, denormalization, freshness checks, and failures across systems. ParadeDB keeps these workloads in Postgres, so index updates happen with your writes and queries run directly against your application data.

### Postgres-Native Developer Experience

Create indexes and query them with SQL. Full-text search, vector retrieval, hybrid search, filters, joins, facets, and aggregations compose with the schema and tools you already use.

### Built for Demanding Queries

ParadeDB indexes serve lexical search, vector retrieval, ranking, filtering, and aggregations from a single wide index. Queries run faster because these operations execute together on dense data structures, rather than combining results from separate scans, indexes, or systems. You get the capabilities and performance of a standalone search engine without giving up Postgres transactions and ACID guarantees.

## Who Uses ParadeDB?

ParadeDB powers core search and analytics workloads at organizations ranging from Fortune 500 companies to fast-growing startups.

- **Alibaba Cloud** ([case study](https://www.paradedb.com/customers/alibaba)), the cloud computing arm of Alibaba Group and the largest Asia-Pacific cloud provider.
- **Bilt Rewards** ([case study](https://www.paradedb.com/customers/bilt)), a rent payments technology company that processed over $36B in payments in 2024.
- **Modern Treasury** ([case study](https://www.paradedb.com/customers/moderntreasury)), a financial technology company that automates the full cycle of money movement.
- **Cofactr** ([case study](https://www.paradedb.com/customers/cofactr)), a full-service electronics purchasing platform for hardware teams.

See all our [case studies](https://paradedb.com/customers).

## Next Steps

<CardGroup cols={2}>
  <Card title="Getting Started" icon="forward-fast" href="/start/install">
    Install ParadeDB and run your first queries.
  </Card>
  <Card
    title="Architecture"
    icon="diagram-project"
    href="/concepts/architecture"
  >
    Learn how ParadeDB is built.
  </Card>
  <Card title="Reference" icon="magnifying-glass" href="/reference/overview">
    Indexing, query types, tokenizers, vectors, and aggregates.
  </Card>
  <Card title="Deploy" icon="server" href="/operate/deploy/overview">
    Deploy ParadeDB in our cloud or on your own infrastructure.
  </Card>
</CardGroup>