Dev tools · alternatives · 2026
24 alternatives to Jet – in-memory, fault-tolerant, distributed stream processing
Distributed Stream and Batch Processing. Contribute to hazelcast/hazelcast-jet development by creating an account on GitHub.
Jet is a distributed stream processing platform designed for handling large-scale data flows with fault tolerance and in-memory processing capabilities. It is intended for developers and organizations that need to… Below are 24 products that do a similar job, ranked by how close each is in meaning and then by launch-day votes. Jet – in-memory, fault-tolerant, distributed stream processing launched in 2020; newer entries below may have overtaken it.
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Hello Everyone! We built SQLFlow as a lightweight stream processing engine. We leverage DuckDB as the stream processing engine, which gives SQLFlow the ability to process 10's of thousands of messages a second using ~250MiB of memory! DuckDB also supports a rich ecosystem of sinks and connectors! https://sql-flow.com/docs/category/tutorials/ https://github.com/turbolytics/sql-flow We were tired of running JVM's for simple stream processing, and also of bespoke one off stream processors I would love your feedback, criticisms and/or…
Dec 2025 · sql-flow.com · its alternatives →
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A Python stream processing engine modeled after Yahoo! Pipes - nerevu/riko
2016 · github.com · its alternatives →
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2016 · codeship.com · its alternatives →
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Goka is a compact yet powerful distributed stream processing library for Apache Kafka written in Go. - lovoo/goka
2017 · github.com · its alternatives →
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Advanced Bloom Filter Based Algorithms for Efficient Approximate Data De-Duplication in Streams - jparkie/PDD
2016 · github.com · its alternatives →
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tl;dr we built an embeddable stream processing engine in Rust using apache DataFusion, check us out at https://github.com/probably-nothing-labs/denormalized Hey HN, We’d like to showcase a very early version of our embeddable stream processing engine called Denormalized. The rise of DuckDB has abundantly made it clear that even for many workloads of Terabyte scale, a single node system outshines the distributed query engines of previous generation such as Spark, Snowflake etc in terms of both performance and cost. Now a lot of workloads DuckDB is used for were normally…
2024 · github.com · its alternatives →
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CLI to transform between JSON, EDN, YAML and Transit using Clojure - borkdude/jet
2019 · github.com · its alternatives →
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🦭 Distributed log streaming engine built from first principles - nubskr/walrus
Dec 2025 · github.com · its alternatives →
- 9PS
Hello HN, I am Sai Srirampur, one of the Co-founders of PeerDB. (https://github.com/PeerDB-io/peerdb). We spent the past 7 months building a solid experience to replicate data from Postgres to data warehouses. Now we're expanding to queues. PeerDB Streams provides a simple and native way to replicate changes as they happen in Postgres to Queues (Kafka, Redpanda, Google PubSub, etc). We use Postgres logical decoding to enable Change Data Capture (CDC). Blog post here: https://blog.peerdb.io/peerdb-streams-simple-native-postgres.... 10-min quickstart here:…
2024 · its alternatives →
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DuckDB for streaming data. Contribute to turbolytics/sql-flow development by creating an account on GitHub.
2024 · github.com · its alternatives →
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Hi HN, I’m excited to share Kameo, a lightweight Rust library that helps you build fault-tolerant, distributed, and asynchronous actors. If you're working on distributed systems, microservices, or real-time applications, Kameo offers a simple yet powerful API for handling concurrency, panic recovery, and remote messaging between nodes. Key Features: - Async Rust: Each actor runs as a separate Tokio task, making concurrency management simple. - Remote Messaging: Seamlessly send messages to actors across different nodes. - Supervision and Fault Tolerance: Create self-healing systems with actor…
2024 · github.com · its alternatives →
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Hey HN, Arroyo is a modern, open-source stream processing engine, that lets anyone write complex queries on event streams just by writing SQL—windowing, aggregating, and joining events with sub-second latency. Today data processing typically happens in batch data warehouses like BigQuery and Snowflake despite the fact that most of the data is coming in as streams. Data teams have to build complex orchestration systems to handle late-arriving data and job failures while trying to minimize latency. Stream processing offers an alternative approach, where the query is compiled into a streaming…
2023 · github.com · its alternatives →
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LBADD: An experimental, distributed SQL database. Contribute to tomarrell/lbadd development by creating an account on GitHub.
2019 · github.com · its alternatives →
- 14SA
2025 · slipstream.readthedocs.io · its alternatives →
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2024 · github.com · its alternatives →
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Probabilistic data structures for processing continuous, unbounded streams. - tylertreat/BoomFilters
2015 · github.com · its alternatives →
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Streamjet▲21A professional broadcast platform in your browser.
2022 · streamjet.io · its alternatives →
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Utility function to parallelise pipelines of Python asyncio iterators/generators - michalc/asyncio-buffered-pipeline
2020 · github.com · its alternatives →
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Hi HN, I built a Java library called SmartFileProcessor to make high-performance, multi-threaded file processing simpler and more maintainable. Most Java file processing solutions either involve a lot of boilerplate or don’t handle concurrency, backpressure, or metrics well out of the box. I needed something fast, clean, and production-friendly — so I built this. Key features: Multi-threaded line/batch processing using a configurable thread pool Producer/consumer model with built-in backpressure Buffered, asynchronous writing with optional auto-flush Live metrics: memory usage,…
2025 · github.com · its alternatives →
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Python stream processing for humans. Contribute to omegaml/minibatch development by creating an account on GitHub.
2020 · github.com · its alternatives →
- 21SA
Yes, Python. I can already hear the screams from the rafters telling me how terrible of a choice Python is - but in my case, I valued modularity, extensibility, hackability over raw performance. (It was also a challenge to myself to see how far I can get without referencing existing implementations) Synchrotron processes nodes: simple Python classes with typed I/O and a render() method for processing. It can be as concise as 5 lines: class IncrementNode(Node): input: StreamInput output: StreamOutput def render(self, ctx): self.out.write(self.a.read(ctx) + 1) Nodes can then be spawned…
2025 · synchrotron.thatother.dev · its alternatives →
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Distributed data transfer with LT codes. Contribute to mgronhol/pouring-rain development by creating an account on GitHub.
2012 · github.com · its alternatives →
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A flink alternative powered by DuckDB
2025 · turbolytics.io · its alternatives →
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Also compare
- DuckDB for Kafka Stream Processing alternatives
- Riko – A Python stream processing engine modeled after Yahoo! Pipes alternatives
- Jet – Codeship’s CI Platform for Docker alternatives
- Goka – distributed stream processing library for Kafka written in Go alternatives
- PDD – Probabilistic De-Duplication of Streams with Bloom Filters alternatives
- Denormalized – Embeddable Stream Processing in Rust and DataFusion alternatives
Ranked by how close each launch is in meaning, then by votes. Prices were read from each product’s own site when checked and can change. Refine with your own description →