SereneDB
SereneDB builds an open-source, distributed, real-time search analytics database that unifies full-text, vector and analytical queries in one PostgreSQL-compatible engine. Its stated mission is to provide an easy-to-use unified search and analytics solution that changes how applications store and retrieve data.
At a Glance
- Developers and engineering teams
- Enterprises needing unified search and analytics
- AI-agent and RAG application builders
- Data-platform and observability teams
- +2 more
AI Tools by SereneDB
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SereneDB
Open Source Search Analytics DB
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Latest News
SereneDB launches Krummelanke, its production-ready search and analytical engine for the agentic future.
SereneDB vs ClickHouse benchmark: 92 search and analytics queries over 100M, 1B and 10B OpenTelemetry logs.
SereneDB vs Elasticsearch, OpenSearch and CrateDB benchmark published.
SereneDB vs ParadeDB, TigerData and PostgreSQL benchmark published.
Products & Services
Open-source, distributed real-time search analytics database combining full-text/BM25, vector and hybrid search with OLAP analytics in one PostgreSQL-compatible SQL engine. It can query remote Parquet, CSV and JSON data and supports zero-ETL search over object storage.
The first production-ready version of SereneDB's real-time search analytics database, positioned for high-volume AI-agent querying and released under Apache 2.0.
A desktop interface for analytics data workflows, distributed as macOS, Linux and Windows installers.
An open-source documentation-search application positioned as an alternative to Algolia DocSearch.
Market Position
SereneDB positions itself as a single Postgres-compatible engine combining Elasticsearch-like search with ClickHouse-like analytics, with vector/hybrid search and remote-data search without ETL. Its stated competitive alternatives include Elasticsearch, OpenSearch, CrateDB, ClickHouse, PostgreSQL, ParadeDB, TigerData, ArangoDB and Lucene/Tantivy-based systems; the company emphasizes public, reproducible benchmarks and claims its IResearch core outperforms Lucene and Tantivy on the cited benchmark.
Leadership
Founders
Alexander Malandin
CEO and co-founder; previously held enterprise-sales roles at EMC, Dell and ArangoDB.
Andrey Abramov
CTO and co-founder; previously worked at Quest Software and EMC in search R&D and at ArangoDB, including as a senior product manager.
Valery Mironov
Co-founder and Principal Engineer; previously worked at ArangoDB and YDB, focusing on core engineering and low-level systems work.
Executive Team
Alexander Malandin
CEO and Managing Director
Co-founder with prior enterprise-sales experience at EMC, Dell and ArangoDB.
Andrey Abramov
CTO
Co-founder and database/search engineer; previously at Quest Software, EMC search R&D and ArangoDB, and credited with starting IResearch.
Founding Story
The founders had worked together for about 16 years and had built production search technology, including the IResearch C++ search core, since 2014. They started SereneDB to bring real-time search and analytical processing together in one open-source, PostgreSQL-compatible database, eliminating duplicated data and separate search/analytics systems.
Business Model
Revenue Model
The publicly described product is open-source under Apache 2.0 and is distributed as a binary, Docker image, Linux installer and SereneUI downloads; no public subscription or usage-pricing model was identified.
Target Markets
- Developers and engineering teams
- Enterprises needing unified search and analytics
- AI-agent and RAG application builders
- Data-platform and observability teams
- Organizations with data in S3/object storage or data lakes
- Legal-tech and document/compliance software teams
- Full-text search
- Vector and hybrid search
- PostgreSQL-compatible search
- Real-time analytics and OLAP
- Search over data lakes and remote object storage
- Zero-ETL search
- Justee.ai