Postgres Read Replica Optimized for Analytics

Stop overloading your Postgres. Unlock scalable analytics without any complexity.

Built using firsthand insights from top tech companies

No setup

1-click cloud analytics

Connect and automatically replicate data from your existing PostgreSQL database to a scalable read replicate optimized for analytics—without any complexity.

Query performance

Fast, scalable, and cost-effective

Leverage the optimized analytics query engine and compressed data stored in a columnar format in object storage with predictable and low-cost pricing.

SELECT s.name, s.address FROM supplier s, country c

WHERE s.key IN (

SELECT ps.supplier_key FROM part_supplier ps

WHERE ps.part_key IN (

SELECT p.key FROM part p

WHERE p.name LIKE 'Belt'

) AND

ps.available_quantity > (

SELECT 0.5 * SUM(l.quantity) FROM line_item l

WHERE l.part_key = ps.part_key AND

l.supplier_key = ps.supplier_key AND

l.shipment_date >= date '2025-01-25' AND

l.shipment_date < date '2025-01-25' + INTERVAL '1 year'

)

) AND

s.country_key = c.key AND

c.name = 'Switzerland'

ORDER BY s.name;

Developer friendly

Run fast read SQL analytics queries while using familiar tools that work with PostgreSQL. Connect your favorite ORMs in applications and business intelligence tools.

Complete data control

All data is stored in a compressed columnar data format. Connect your S3-compatible object storage to keep open access for any data tools without vendor lock-in.

Trusted integrations with Postgres hosting partners

Testimonials

Join the community

"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

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