> ## Documentation Index > Fetch the complete documentation index at: https://www.paradedb.com/docs/llms.txt > Use this file to discover all available pages before exploring further. # Welcome to ParadeDB > Search belongs with your application data export const Architecture = () =>
; When queries get too slow, developers usually reach for systems like Elasticsearch. ParadeDB makes text and vector search, filters, facets, and joins fast in Postgres. ParadeDB accelerates these queries inside Postgres with a custom index. The index ships as **pg\_search**, a standard Postgres extension. This means ParadeDB is vanilla Postgres with an extension installed, not a Postgres fork or sidecar process. ParadeDB Cloud is coming soon: a fully managed platform for running ParadeDB with better developer experience, higher performance, and more scalability than self-managing the extension. The [waitlist is open now](https://www.paradedb.com/cloud) for early access. ## Who is ParadeDB for? You're likely a good fit for ParadeDB if any of the following sound like you: 1. You're **combining transactional workloads with search**: semantic search, full-text search, vector retrieval, lexical ranking, or hybrid search need to run against your source of truth data. 2. You've **outgrown Postgres full-text search or pgvector** and are frustrated with performance bottlenecks, missing features, or a clunky developer experience. 3. You're **evaluating a search engine like Elasticsearch or a vector store like Pinecone**, but don't want to run and continuously sync additional systems with your database. ## Why ParadeDB? For teams that already use Postgres, ParadeDB is the shortest path from transactional data to production-grade search. ### No Second System External search engines and vector stores make you own sync jobs, duplicated schemas, freshness checks, and cross-system failures. ParadeDB keeps search in Postgres, so index updates happen with your writes and queries run against your source of truth 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 Real Search Workloads A ParadeDB index serves lexical search, vector retrieval, ranking, filtering, and aggregations from one place. ParadeDB can be fast because these workloads push down into a single wide index, instead of being stitched together across scans, indexes, or systems. You get dedicated-search-engine capabilities without giving up Postgres transactions and ACID guarantees. For deeper evaluation, compare ParadeDB with [Postgres full-text search, pgvector, search engines, and vector stores](/docs/start/alternatives). ## Who Uses ParadeDB? ParadeDB powers core search and analytics workloads at organizations ranging from Fortune 500 companies to fast-growing startups. * **Alibaba Cloud**, the cloud computing arm of Alibaba Group and the largest Asia-Pacific cloud provider. [Case study](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](https://www.paradedb.com/customers/case-study-bilt). * **Modern Treasury**, a financial technology company that automates the full cycle of money movement. [Case study](https://www.paradedb.com/customers/case-study-modern-treasury). * **Cofactr**, a full-service electronics purchasing platform for hardware teams. [Case study](https://www.paradedb.com/customers/case-study-cofactr). * **TCDI**1, a giant in the legal software and litigation management space. *1. Case study coming soon.* ## Next Steps These pages cover the core workflow. Install ParadeDB and run your first queries. Learn how ParadeDB is built. Indexing, query types, tokenizers, vectors, and aggregates. Deploy ParadeDB as a Postgres extension or standalone database.