Documentation
Performance

Performance

We regularly test our architecture, infrastructure, and query engine at scale to ensure Altertable delivers consistent performance as your data grows.

Benchmarking

One benchmark we use is TPC-H at scale factor 100 (about 250 GB). It provides a repeatable workload for query performance comparisons.

Benchmark numbers are directional: real-world performance depends on data shape, storage layout, query mix, and cache warmth.

Query Time

Average TPCH Benchmark (sf=100) results - lower is better

Altertable
<1s
Snowflake(X-Large)
1s
BigQuery
2s
Fabric
3s
Snowflake(X-Small)
4s
Redshift
4s
Databricks
5s

Cold vs Hot Queries

Due to our lakehouse architecture, some data might be required to get downloaded from the infinite-scale distributed storage to the local DuckDB worker machine. Therefore, the first query might be considered "cold"—most of the elapsed time will probably be spent downloading the data. However, subsequent queries (hot) will be significantly faster as the data is already available locally.

Our Approach to Performance

Benchmarks can be over-optimized for a single scenario. We prioritize customer workloads and production query patterns over synthetic benchmark tuning.

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