Ross ROSS = Recommend OSS · open-source software intelligence for agents

marsupialtail/quokka

Making data lake work for time series observed · 2026-08-28

github.com/marsupialtail/quokka · homepage · Python · Apache-2.0 (permissive) observed · 2026-08-28

Health v2 · maintenance only

23/100

  • Activity 0
  • Release rhythm 8
  • Longevity 100
How is this computed?

round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10) — computed 2026-09-03. Adoption (stars, forks) is never an input.

  • gap_med: n/a
  • age_days: 1749
  • days_rel: n/a
  • days_push: 743
  • n_releases_24m: 0

Full methodology

Adoption not part of the score

1192 stars · 63 forks observed · 2026-08-28

What it is AI-extracted, prompt v1, taxonomy v1, 2026-08-30, confidence not recorded

Quokka is a lightweight distributed dataflow/query engine written in Python, built on Ray, DuckDB, Polars, and Arrow, designed for stateful and windowed computation over large time series datasets in data lakes. It offers a Polars-inspired DataStream API plus SQL support, outperforming SparkSQL on many SQL workloads over cloud storage.

Use cases

  • run distributed SQL queries over parquet and csv files in a data lake
  • backtest trading strategies against years of tick-level market data
  • perform complex windowed and asof joins on terabytes of time series data
  • apply machine learning models inside distributed data pipelines
  • do feature engineering across thousands of columns at scale
  • replace SparkSQL with a faster Python-native query engine
  • process streaming clickstream data with incremental algorithms

When to choose

  • you need distributed time series analytics with complex windows, asof joins, or pattern matching
  • you want a Python-native alternative to Spark with a Polars-like API
  • you run SQL workloads over cloud object storage and need better performance than SparkSQL
  • you want to embed PyTorch or scikit-learn transformations inside a distributed pipeline

When to avoid

  • you need a mature, battle-tested engine with a large community like Spark or Flink
  • your datasets are small enough for pandas, Polars, or DuckDB on a single machine
  • you need full compatibility with the latest Polars API
  • you require streaming ingestion of live real-time data rather than historical batch analysis

Facets

library · maturity active

etl streaming data-science big-data data-science time-series analytics python cloud data-lake-analytics distributed-query-engine datastream-api polars-inspired ray-based time-series-analytics sql-engine mlops query-engine distributed-computing data-engineering docker

2 sources

Member repositories

RepositoryRoleHealth v2
marsupialtail/quokkamain23

For agents

markdown · JSON · MCP: product_card(name="marsupialtail/quokka")

Data as of 2026-08-30T08:39:29.467469+00:00 · Report a problem