---
title: Simple, Elastic-Quality Search for Postgres
description: ParadeDB is the modern Elastic alternative built as a Postgres extension.
canonical: https://docs.paradedb.com/welcome/introduction
---
## Who is ParadeDB for?
You are likely a good fit for ParadeDB if you identify with the following:
1. Your **primary database is Postgres**, either managed (e.g. AWS RDS) or self-managed
2. You **have used Postgres' built-in search** capabilities via `tsvector` and the GIN index, but have reached a scale where you're limited by **performance bottlenecks** or **missing features** like BM25 scoring or fuzzy search
3. You are evaluating a search engine like Elasticsearch, but **don't want to introduce another cumbersome dependency** to your stack
## Why ParadeDB?
For teams that already use Postgres, ParadeDB is the simplest way to bring Elastic-quality search to your application.
### Zero ETL Required
Syncing Postgres with an external search engine like Elastic can be a time-consuming, error-prone process that involves babysitting ETL pipelines
and debugging data inconsistency issues. ParadeDB eliminates this class of problems because you can:
- [Install](/deploy/self-hosted/extension) the ParadeDB extension directly inside your Postgres, if it is self-managed
- [Run ParadeDB as a logical replica](/deploy/self-hosted/logical-replication/getting-started) of your primary Postgres, if you use managed Postgres providers like RDS
### Search That Feels Like Postgres
In ParadeDB, writing a search query is as simple as writing SQL. ParadeDB supports JOINs, which removes the complexity of denormalizing your existing schema.
### As Reliable As Postgres
ParadeDB supports Postgres transactions and ACID guarantees. This means that data is searchable immediately
after it's written to ParadeDB, and durable thanks to Postgres write-ahead logging.
## ParadeDB vs. Alternatives
People usually compare ParadeDB to two other types of systems: OLTP databases like vanilla Postgres and search engines like Elastic.
| | **OLTP database** | **Search engine** | **ParadeDB** |
| --------------------------- | ------------------------------------------------------------------------ | ------------------------------------------------------------------------------------------------------ | ------------------------------------------------------------------------------------------------------------------------- |
| **Primary role** | System of record | Search and retrieval engine | System of record **and** search/analytics engine |
| **Examples** | Postgres, MySQL | Elasticsearch, OpenSearch | |
| **Search features** | Basic FTS (no BM25, weak ranking) | Rich search features (BM25, fuzzy matching, faceting, hybrid search) | Rich search features (BM25, fuzzy matching, faceting, hybrid search) |
| **Analytics features** | Not an analytical DB (no column store, batch processing, etc.) | Column store, batch processing, parallelization via sharding | Column store, batch processing, parallelization via Postgres [parallel workers](/documentation/performance-tuning/writes) |
| **Lag** | None in a single cluster | At least network, ETL transformation, and indexing time | None in a single cluster |
| **Operational complexity** | Simple (single datastore) | Complex (ETL pipelines, managing multiple systems) | Simple (single datastore) |
| **Scalability** | Vertical scaling in a single node, horizontal scaling through Kubernetes | Horizontal scaling through sharding | Vertical scaling in a single node, horizontal scaling through [Kubernetes](/deploy/self-hosted/kubernetes) |
| **Language** | SQL | Custom DSL | Standard SQL with custom search operators |
| **ACID guarantees** | Full ACID compliance, read-after-write guarantees | No transactions, atomic only per-document, eventual consistency, durability not guaranteed until flush | Full ACID compliance, read-after-write guarantees |
| **Update & delete support** | Built for fast-changing data | Struggles with updates/deletes | Built for fast-changing data |
## Production Readiness
As a company, ParadeDB is over two years old. ParadeDB launched in the [Y Combinator (YC)](https://ycombinator.com) S23 batch and has been validated in
production since December 2023.
[ParadeDB Community](https://github.com/paradedb/paradedb), the open-source version of ParadeDB, has been deployed over 400,000 times in the past 12 months.
ParadeDB Enterprise, the durable and production-hardened edition of ParadeDB, powers core search and analytics use cases at enterprises ranging from Fortune 500s to fast-growing startups. A few
examples include:
- **Alibaba Cloud**, the largest Asia-Pacific cloud provider, uses ParadeDB to power search inside their data warehouse. [Case study available](https://www.paradedb.com/customers/case-study-alibaba).
- **Bilt Rewards**, a rent payments technology company that processed over $36B in payments in 2024. [Case study available](https://www.paradedb.com/customers/case-study-bilt).
- **Modern Treasury**1, a financial technology company that automates the full cycle of money movement.
- **Span**1, one of the fastest-growing AI developer productivity platforms
- **TCDI**1, a giant in the legal software and litigation management space.
_1. Case study coming soon_
## Next Steps
You're now ready to jump into our guides.
Get started with ParadeDB in under five minutes.
Learn how ParadeDB is built.
API reference for full text search and analytics.
Deploy ParadeDB as a Postgres extension or standalone database.