"if you have worked with analytical systems in the past, you may assume that DuckDB cannot handle transactional workloads. But DuckDB has been built as a transactional, multi-connection database with full MVCC and transaction isolation since day one. Most users just never needed that in a single-user scenario. It turns out DuckDB handles transactions well: it's fast enough to compete with general-purpose databases like PostgreSQL on quite a few workloads, and the client/server pattern finally lets that machinery shine in multi-tenant, long-running deployments."
Does anyone have any links to benchmarks or stories of attempting this in practice? (Even what their internal benchmark that lead them to say "it's fast enough to compete with general-purpose databases like PostgreSQL on quite a few workloads" was?)
"if you have worked with analytical systems in the past, you may assume that DuckDB cannot handle transactional workloads. But DuckDB has been built as a transactional, multi-connection database with full MVCC and transaction isolation since day one. Most users just never needed that in a single-user scenario. It turns out DuckDB handles transactions well: it's fast enough to compete with general-purpose databases like PostgreSQL on quite a few workloads, and the client/server pattern finally lets that machinery shine in multi-tenant, long-running deployments."
https://duckdb.org/2026/08/17/duckdb-20-highlights
Does anyone have any links to benchmarks or stories of attempting this in practice? (Even what their internal benchmark that lead them to say "it's fast enough to compete with general-purpose databases like PostgreSQL on quite a few workloads" was?)
Is there a guide on this anywhere?