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Quokka Alternatives
Similar projects and alternatives to quokka
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Judoscale
Save 47% on cloud hosting with autoscaling that just works. Judoscale integrates with Django, FastAPI, Celery, and RQ to make autoscaling easy and reliable. Save big, and say goodbye to request timeouts and backed-up task queues.
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intelligent-trading-bot
Intelligent Trading Bot: Automatically generating signals and trading based on machine learning and feature engineering
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hamilton
Hamilton helps data scientists and engineers define testable, modular, self-documenting dataflows, that encode lineage/tracing and metadata. Runs and scales everywhere python does.
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CodeRabbit
CodeRabbit: AI Code Reviews for Developers. Revolutionize your code reviews with AI. CodeRabbit offers PR summaries, code walkthroughs, 1-click suggestions, and AST-based analysis. Boost productivity and code quality across all major languages with each PR.
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fugue
A unified interface for distributed computing. Fugue executes SQL, Python, Pandas, and Polars code on Spark, Dask and Ray without any rewrites.
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hyperDB
A hyper-fast local vector database for use with LLM Agents. Now accepting SAFEs at $135M cap.
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opteryx
🦖 A SQL-on-everything Query Engine you can execute over multiple databases and file formats. Query your data, where it lives.
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InfluxDB
InfluxDB high-performance time series database. Collect, organize, and act on massive volumes of high-resolution data to power real-time intelligent systems.
quokka discussion
quokka reviews and mentions
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How Query Engines Work
An awesome read!
Something related that I found out about from HN a few months back is another engine called quokka. It's particularly interesting and applicable how quokka schedules distributed queries to outperform Spark https://github.com/marsupialtail/quokka/blob/master/blog/why...
- Quokka – Distributed Polars on Ray
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Algorithmic Trading with Go
Hi Justin, you might be interested in my blog: https://github.com/marsupialtail/quokka/blob/master/blog/bac... advocating a cloud based approach.
You don't have to use the system I am building, but it's worth thinking about that design.
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Daft: A High-Performance Distributed Dataframe Library for Multimodal Data
SQL support is very challenging.
I work on Quokka (https://github.com/marsupialtail/quokka). I support Iceberg reads. Recently we are adding SQL support from just parsing the DuckDB logical plan, though that is very challenging as well.
The Python world lacks a standard for a plug and play SQL query optimizer. Apache Calcite is good for the JVM world, but not great if you are trying to cut out the JVM.
- Why your dataframe library needs to understand vector embeddings
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The Inner Workings of Distributed Databases
In case people are interested, I wrote a post about fault tolerance strategies of data systems like Spark and Flink: https://github.com/marsupialtail/quokka/blob/master/blog/fau...
The key difference here is that these systems don't store data, so fault tolerance means recovering within a query instead of not losing data.
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Launch HN: DAGWorks – ML platform for data science teams
would love to collaborate on an integration with pyquokka (https://github.com/marsupialtail/quokka) once I put out a stable release end of this month :-)
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is spark always your go to solution ?
Then you should keep an eye on quokka. This may become the "Spark" for Polars/DuckDB. It seems to be under active development though I'm not sure how stable it is.
- Distributed fault tolerance made simple
- Fault tolerance for distributed data systems is quite simple
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A note from our sponsor - InfluxDB
influxdata.com | 28 Apr 2025
Stats
marsupialtail/quokka is an open source project licensed under Apache License 2.0 which is an OSI approved license.
The primary programming language of quokka is Python.