Alternatives
Products that do what Cutting the Fat from Stream Processing: Meet ZephFlow (Open Source) does
Hey HN, Apache Flink is a beast for heavy-duty stream processing – no doubt about it. We've used it, admired its power, and it heavily influenced our thinking. But let's be honest: for a lot of common, everyday stream processing tasks, Flink (and similar frameworks) can feel like bringing a bazooka to a knife fight. The operational overhead and complexity for simpler, stateless jobs often outweigh the benefits. That's why we built ZephFlow. What is ZephFlow? ZephFlow is a stream processing framework built for lightweight operations and simplicity. It distills the core principles of…
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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
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Hi HN! For the past bit we’ve been building Flowglad (https://flowglad.com) and can now feel it’s just gotten good enough to share with you all: Repo: https://github.com/flowglad/flowglad Demo video: https://www.youtube.com/watch?v=G6H0c1Cd2kU Flowglad is a payment processor that you integrate without writing any glue code. Along with processing your payments, it tells you in real time the features and usage credit balances that your customers have available to you based on their billing state. The DX feels like React, because we wanted to bring…
Nov 2025 · github.com
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2016 · github.com
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We are working on a product which makes stream processing easy for data analysts and data scientists. It’s a higher level alternative to Flink, Kafka Streams and Spark Streams. As well as making stream processing simpler, we also felt that lots of people were building these AWS stream processing platforms based on Kafka and something like Flink so wanted to offer this as a service. We would welcome any input on the space or approach: Home page: http://Timeflow.systems Demo: https://youtu.be/fGfgBaHXOkE
2020
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2020 · cloud.titanoboa.io
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2015 · github.com
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Open-source search engine indexing infrastructure with inline SEO quality gates, fair multi-site scheduling, and rolling quota circuit breaker. - IndexFlowing/IndexFlow-core
9d ago · github.com
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2020 · systemflow.co
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I'd like to share a project I've been working on for the past few months. It's a distributed workflow engine written entirely in Go. Some highlights: * Tasks are executed in a Docker container * Can run stand-alone or distributed * Highly extensible * Able to enforce limits (CPU/RAM) per task * Web UI Would love the get your feedback on it, and find out if this could be useful.
2023 · github.com
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https://github.com/fzakaria/WaterFlow Frustrated with AWS Flow that is a pain to setup on maven & IDEA, this is a new take on a framework heavily inspired by https://bitbucket.org/clarioanalytics/services-swift It adds JDK8 asynchronous interfaces to make writing distributed workflows pain free.
2016
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Hi HN! We are Ashish and Armend, founders of GlassFlow. Over the last year, we worked with teams running high-throughput pipelines into self-hosted ClickHouse. Mostly for observability and real-time analytics. A question that came repeatedly was: What happens when throughput grows? Usually, things work fine at 10k events/sec, but we started seeing backpressure and errors at >100k. When the throughput per pipeline stops scaling, then adding more CPU/memory doesn’t help because often parts of the pipeline are not parallelized or are bottlenecked by state handling. At this point,…
Apr 2026 · github.com
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We have been involved in a number of real time streaming projects using tools such as Flink, Spark Streams and Kafka Streams backed by "real time" databases such as Druid. We always found these projects quite complex to develop and run, with stream processing in particular being a bit of a dark art. A stream to stream join in Flink can get quite mind bending for instance. In 2020 we had the idea of building a low code SaaS product for real time streaming analytics. The first attempt failed due to being a little over-engineered and with too many changes of direction, but over the last few…
2021
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Hello people of HN and fellow SREs! Over the past year, we have been building Aperture - an open-source flow control and reliability platform for cloud applications. Over the past few years, companies like LinkedIn[1], Google [2], Netflix [3], Stripe [4] have built cutting-edge flow control technologies to keep their applications reliable. Flow control is powerful because it enables graceful degradation- the ability to preserve key user experience pathways, even in the face of application failures. With Aperture project, we hope to democratize building reliable applications with effective…
2022 · github.com
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2016 · concord.io
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Hi there HN! I'm Matthias and I've been into video streaming for quite a while now. Over the years I've built plenty of small setups, often CLI tools to test and debug streaming video. About a month ago, during my annual holiday, I started working on a simple API on top of my CLI tools. It's time consuming to craft and run multiple ffmpeg jobs, get GOP / keyframes right, merge playlists, package to HLS, ... One thing led to another and I eventually started exploring HLS interstitials, VMAP / VAST and dynamic ad insertion, MSE / EME (HLS.js in general), React (perf) as a player…
2024 · github.com
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Hello HN, Over the past year, we have been building Aperture - an open-source flow control and reliability platform for cloud applications. Over the past few years, companies like LinkedIn[1], Google [2], Netflix [3], Stripe [4] have built cutting-edge flow control technologies to keep their applications reliable. Flow control is powerful because it enables graceful degradation- the ability to preserve key user experience pathways, even in the face of application failures. With Aperture project, we hope to democratize building reliable applications with effective flow control. Aperture…
2022 · github.com
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