ParadeDB is a Postgres extension that provides elastic-quality search capabilities directly within the database. It integrates features like text, hybrid, and faceted search, eliminating the need for a separate search engine infrastructure. This approach simplifies the data stack by enabling logical replication and zero ETL processes from existing Postgres deployments.
Funding
$500K raised to dateRaised to date based on public sources. This may differ from the amount the company actually raised and is based only on what is publicly available on the internet.
Founders
Product
Problem
Traditional search and analytics solutions require complex ETL pipelines to synchronize data between PostgreSQL and specialized engines like Elasticsearch. This introduces overhead, potential data loss, and operational complexity, especially for update-heavy workloads requiring real-time data availability.
Solution
ParadeDB transforms PostgreSQL into a real-time search and analytics engine, eliminating the need for separate tools and ETL processes. By integrating native indexing and query capabilities directly within PostgreSQL, ParadeDB ensures immediate data availability and consistency. It supports update-heavy workloads with ACID guarantees, allowing users to leverage existing PostgreSQL infrastructure for both transactional and analytical workloads. This approach simplifies the data stack, reduces operational overhead, and strengthens data reliability.
Target Audience
ParadeDB targets enterprises and developers using PostgreSQL who need real-time search and analytics capabilities without the complexity and overhead of separate systems.
Features
- Native PostgreSQL indexes for full-text search, analytics, and faceting
- BM25 scoring and custom tokenizers to enhance search relevance
- Support for hybrid search combining vector and keyword queries
- Zero-ETL integration with existing PostgreSQL infrastructure and managed services like Amazon RDS, Azure Postgres, and Google Cloud SQL
- Direct querying and ingestion of data from S3, GCS, and Azure Blob Storage
- Compatibility with the PostgreSQL dialect, eliminating the need to learn a new query language
- Automatic index cleanup integrated with PostgreSQL's vacuum process