calls gigapi “When you want a lightweight DuckDB/Parquet-based lakehouse for sub-second time-series queries and prefer a small Go service.”
Scalable datastore for metrics, events, and real-time analytics
gigapi is queued for analysis. Crawling candidates and ranking them takes a few minutes. This page updates itself when the list exists — you can also come back later.
What is known so far comes from the other direction:
These projects were analysed and named gigapi among their alternatives. The relationship is not symmetric — how gigapi rates them is a separate judgement, made when gigapi is analysed in its own right.
calls gigapi “When you want a lightweight DuckDB/Parquet-based lakehouse for sub-second time-series queries and prefer a small Go service.”
Scalable datastore for metrics, events, and real-time analytics
calls gigapi “Choose GigAPI for a lightweight lakehouse-style time-series engine on DuckDB/Parquet over object storage; trade off much lower maturity and a smaller community.”
QuestDB is a high performance, open-source, time-series database
calls gigapi “Choose it if you want a lightweight DuckDB-backed lakehouse with minimal infrastructure requirements.”
The world's fastest open query engine for sub-second analytics both on and off the data lakehouse. With the flexibility to support nearly any scenario, StarRocks provides best-in-class performance for multi-dimensional analytics, real-time analytics, and ad-hoc queries. A Linux Foundation project.
calls gigapi “Timeseries lakehouse on DuckDB/Parquet; choose it for sub-second time-series queries, not general analytics/search.”
Apache Doris is a real-time analytics and hybrid search database for AI agents.