Tinybird: ClickHouse vs DuckDB — how many nodes do you need?

Tinybird‘s comparison of ClickHouse and DuckDB framed around scale and node count — the source that stakes out this spoke’s embedded↔distributed axis (analytical-databases). Found via WebSearch (the user’s prompt was “Tinybird ClickHouse vs DuckDB analytics”).

The comparison

• duckdb suffices for interactive notebooks, exploratory analysis, production under ~100 GB, edge/embedded, single-machine (no clustering).
• clickhouse needs multiple nodes for high-ingest pipelines (100K+ rows/s), hundreds of concurrent queries, datasets exceeding RAM, and production fault tolerance.
• Indicative numbers: DuckDB ~1B rows / ~50 GB on a 16 GB MacBook, TPC-H in ~1m16s; ClickHouse 1 TB query ~10 s single-node → ~2-3 s on 4 nodes; ingest ~200K inserts/s/node → ~800K/s across 4.

Vendor bias — recorded

This is a Tinybird marketing blog (T3). Tinybird sells managed ClickHouse, so the piece favors ClickHouse for production, then positions Tinybird as eliminating “node management complexity” (shard placement/replication/routing), with multiple sign-up CTAs. The numbers are vendor-run and indicative, not independent benchmarks. Weigh against the independent posthog-duckdb-vs-clickhouse (which reaches for DuckDB because ClickHouse didn’t fit a key workload).

Tier

T3 — vendor blog with a clear commercial incentive; useful for the architecture framing and ballpark figures, not as a neutral benchmark.

Related

clickhouse · duckdb · tinybird · analytical-databases · posthog-duckdb-vs-clickhouse · synthesis