GoKawiilOpenDuck
An open-source implementation of the ideas pioneered by MotherDuck — differential storage, hybrid (dual) execution, and transparent remote databases for DuckDB — available for anyone to run, extend, and build on.
MotherDuck showed that DuckDB can work beautifully in the cloud: ATTACH 'md:mydb' , and remote tables appear local. Queries split transparently across your laptop and the cloud. Storage is layered and snapshot-based. OpenDuck takes those architectural ideas — differential storage, dual execution, the attach-based UX — and makes them open. Open protocol, open backend, open extension.
import duckdb con = duckdb . connect () con . execute ( "LOAD 'openduck';" ) con . execute ( "ATTACH 'openduck:mydb?endpoint=http://localhost:7878&token=xxx' AS cloud;" ) con . sql ( "SELECT * FROM cloud.users" ). show () # remote, transparent con . sql ( "SELECT * FROM local.t JOIN cloud.t2 ON ..." ). show () # hybrid, one query # direct connect using openduck python library con = openduck . connect ( "od:mydb" ) con = openduck . connect ( "openduck:myd" ) # direct connect using duckb (TODO: needs duckdb to autoload openduck the same way motherduck works today) con = duckdb . connect ( "od:mydb" ) con = duckdb . connect ( "openduck:myd" )
What OpenDuck does
Differential storage
Append-only layers with PostgreSQL metadata. DuckDB sees a normal file; OpenDuck persists data as immutable sealed layers addressable from object storage. Snapshots give you consistent reads. One serialized write path, many concurrent readers.
Hybrid (dual) execution
A single query can run partly on your machine and partly on a remote worker. The gateway splits the plan, labels each operator LOCAL or REMOTE , and inserts bridge operators at the boundaries. Only intermediate results cross the wire.
[LOCAL] HashJoin(l.id = r.id) [LOCAL] Scan(products) ← your laptop [LOCAL] Bridge(R→L) [REMOTE] Scan(sales) ← remote worker
... continue reading