Open-Source Data Warehouse.
Built for Postgres

Self-host in minutes with a single binary.
No data pipelines or ETL required.
BemiDB
Built using firsthand insights from top tech companies
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Zero engineering fuss

Simple, single-binary deploy

Self-hosting has never been easier. No pipelines, no ETL, and no engineering complexity.

 
curl -sSL https://bemidb.com/install.sh | bash
 
bemidb sync \
  --pg-database-url postgres://user@hostname:5432/dbname
 
bemidb start
 
Built for scale

Fast and scalable

Use the same PostgreSQL queries you already know. Powered by modern open-source tech, it handles billions of rows in subsecond time.

Query time
BemiDB  ·  0.000s
PostgreSQL  ·  0.000s

No vendor lock-in

Store everything in open columnar format within your own object storage. Keep complete ownership and control—no hidden strings attached.

Works with Postgres ecosystem

Connect your favorite ORMs, BI dashboards, and notebooks—out of the box and with no new setup or syntax.

Integrates with all Postgres hosting providers
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Use cases

Powerful analytics

Centralized data store
Postgres in-app analytics
BI and ad-hoc queries
Centralize data without pipelines
Centralize data without pipelines
Combine multiple Postgres databases into one permanent cost-effective unified store. Simplify your analytics and reporting with a consolidated and unlimited dataset.
Testimonials

Join the community

One of the fastest-growing open source database projects
  • "After some initial trials that has proven BemiDB to be simply awesome, I was looking forward to try it out in the wild."
    Grzegorz Brzezinka
  • "Query Engine: embeds the DuckDB to run analytical queries. Storage Layer: uses the Iceberg table format to store data in columnar compressed Parquet files. Smart."
    Alex N.
  • "This is probably the most streamlined/all-inclusive solution out of all that I've seen."
    Dan Goodman
  • "Really cool! I have an IoT use-case where I ingest data, I want to keep like the last 3 months or so in Postgres, and then store the old data as parquet files on S3."
    oulipo
  • "After some initial trials that has proven BemiDB to be simply awesome, I was looking forward to try it out in the wild."
    Grzegorz Brzezinka
  • "Query Engine: embeds the DuckDB to run analytical queries. Storage Layer: uses the Iceberg table format to store data in columnar compressed Parquet files. Smart."
    Alex N.
  • "This is probably the most streamlined/all-inclusive solution out of all that I've seen."
    Dan Goodman
  • "Really cool! I have an IoT use-case where I ingest data, I want to keep like the last 3 months or so in Postgres, and then store the old data as parquet files on S3."
    oulipo
  • "After some initial trials that has proven BemiDB to be simply awesome, I was looking forward to try it out in the wild."
    Grzegorz Brzezinka
  • "Query Engine: embeds the DuckDB to run analytical queries. Storage Layer: uses the Iceberg table format to store data in columnar compressed Parquet files. Smart."
    Alex N.
  • "This is probably the most streamlined/all-inclusive solution out of all that I've seen."
    Dan Goodman
  • "Really cool! I have an IoT use-case where I ingest data, I want to keep like the last 3 months or so in Postgres, and then store the old data as parquet files on S3."
    oulipo
  • "After some initial trials that has proven BemiDB to be simply awesome, I was looking forward to try it out in the wild."
    Grzegorz Brzezinka
  • "Query Engine: embeds the DuckDB to run analytical queries. Storage Layer: uses the Iceberg table format to store data in columnar compressed Parquet files. Smart."
    Alex N.
  • "This is probably the most streamlined/all-inclusive solution out of all that I've seen."
    Dan Goodman
  • "Really cool! I have an IoT use-case where I ingest data, I want to keep like the last 3 months or so in Postgres, and then store the old data as parquet files on S3."
    oulipo
FAQ

Have any questions?

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Self-hosting has never been easier.
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