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Products that do what Apache Fluss (Incubating) – Streaming Storage for Real-Time Analytics does

Hey HN! On behalf of the Fluss community, I would like to share Apache Fluss (Incubating). Fluss is a next-generation streaming storage designed for real-time analytics. As a columnar streaming storage, it is the first of its kind and fills a significant gap in the current data management landscape [1]. In particular, Fluss aims to address the high costs and inefficiencies of current (row-oriented) streaming storage technologies and lakehouse architectures. Initially launched internally at Alibaba in July 2023, Fluss was open-sourced in November 2024 [2] and entered the Apache Incubator in…

  1. 1BP

    Hi HN! We're Evgeny and Arjun, and we’re building a better way to do analytics with Postgres. We love Postgres for its simplicity, power, and rich ecosystem. But engineers have to still get bogged down with heavyweight and expensive OLAP systems when connecting an analytics data stack. Postgres is amazing at OLTP queries, but not for OLAP queries (large data scans and aggregations). Even in this case, we’ve still heard from countless scaling startups that they still try to use only a read replica to run analytics workloads since they don’t want to deal with the data engineering complexity of…

    2024 · github.com

  2. 2SS
  3. 3FD
  4. 4SL

    S2 was on HN for our intro blog post a year ago (https://news.ycombinator.com/item?id=42480105). S2 started out as a serverless API — think S3, but for streams. The idea of streams as a cloud storage primitive resonated with a lot of folks, but not having an open source option was a sticking point for adoption – especially from projects that were themselves open source! So we decided to build it: https://github.com/s2-streamstore/s2 s2-lite is MIT-licensed, written in Rust, and uses SlateDB (https://slatedb.io) as its storage engine. SlateDB is an…

    Jan 2026 · github.com

  5. 5TA

    I built a SQLite VFS in Rust that serves cold queries directly from S3 with sub-second performance, and often much faster. It’s called turbolite. It is experimental, buggy, and may corrupt data. I would not trust it with anything important yet. I wanted to explore whether object storage has gotten fast enough to support embedded databases over cloud storage. Filesystems reward tiny random reads and in-place mutation. S3 rewards fewer requests, bigger transfers, immutable objects, and aggressively parallel operations where bandwidth is often the real constraint. This was explicitly inspired…

    Mar 2026 · github.com

  6. 6ZA
  7. 7SJ
  8. 8SP

    This is a MVP for Serverless Postgres. 1/ It uses Fly.io[0], which can automatically pause your database after all connections are released (and start it again when new connections join). 2/ It uses Oriole[1], a Postgres extension with experimental support for S3 / Decoupled Storage[2]. 3/ It uses Tigris[3], Globally Distributed S3-Compatible Object Storage. Oriole will automatically backup the data to Tigris using background workers. I wouldn't recommend using this in production, but I think it's in a good spot to provoke some discussion and ideas. You can get it running…

    2024 · github.com

  9. 9FA

    I've just released an early version off my project I've been working on for a few months now and would love some feedback. https://github.com/fourlexboehm/faasta I was surprised there isn't yet an open/source and standards compliant way to host wasi-http functions in a way that takes advantages of WASM, a multi tenanted application. If you're not familiar with wasi, Compared to something like AWS Lambda, this approach is much more efficient as a single process can serve 1000s of function invocations concurrently and asynchronously, instead requiring an entire VM.…

    2025 · github.com

  10. 10DE

    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

  11. 11PD

    PicoMQ is a Rust server for Durable Streams, built on Object Store. Cheap, URL-addressable, granular streams (create/append/read/long-poll/SSE), with Pico Protocol or Durable Streams Protocol as the facade. S3Stream is the stream storage primitive, used in AutoMQ, shipped as a Rust library. Coordination is a command log in Postgres.

    13d ago · picomq.com

  12. 12CS

    We started CallFS after yet another late-night “why did the uploads vanish?” incident. Our small team had stitched together rsync, a fragile NFS mount, and an S3 bucket—none of it observable, all of it waiting to bite us. So we wrote a single-process file service in Go that: • Speaks the S3 API (so existing tooling works). • Stores hot data on local disks for speed; cold data can sit in any S3-compatible bucket. • Exposes Prometheus metrics and JSON logs by default, because “what happened?” shouldn’t be guesswork. • Ships as a ~25 MB static binary—no external deps, MIT license. Today it’s…

    2025 · github.com

  13. 13

    Analytics service for Kafka

    2024

  14. 14F3

    2025 · infinyon.com

  15. 15AA

    Apache Amoro (incubating) is a Lakehouse management system built on open data lake formats. Working with compute engines including Flink, Spark, and Trino, Amoro brings pluggable and self-managed features for Lakehouse to provide out-of-the-box data warehouse experience, and helps data platforms or products easily build infra-decoupled, stream-and-batch-fused and lake-native architecture.

    2024 · github.com

  16. 16DF

    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

  17. 17EY

    Hey HN, We're thrilled to introduce you to Edginary, our new groundbreaking startup set to change how developers access and scale their data globally. We've all felt the pain points of dealing with centralized data sources: performance bottlenecks, reliability issues, and the dreaded revenue loss due to downtime. Edginary is here to tackle these issues head-on. Edginary is a serverless platform that moves your data close to your users in real-time so they can access it in ultra low-latency. By reducing the load on your servers and databases, we aim to not only improve performance and…

    2024 · edginary.io

  18. 18SR
  19. 19RT

    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

  20. 20AR

    Hey HN, cofounder of Artie here. We’ve built a real-time data replication tool that captures every row-level change in your source database and streams it to your warehouse in under 60 seconds. The last time I posted here, people had to book a call with us in order to access Artie. Today, that’s no longer the case. You can now connect your source and destination and start streaming immediately. I spent years of my career building large-scale data pipelines and experienced how difficult it was to get real-time data firsthand. I believed there must be a better way to stream data into our…

    Jun 2026 · artie.com

  21. 21SD

    Hi HN, I'm Dean, the non-technical co-founder of SchemafreeSQL. We released our beta version about a year ago. You can see the HN Post here https://news.ycombinator.com/item?id=30291592 Today I am pleased to announce our initial release of our hosted SFSQL offering. A major concern from the HN Beta feedback we received was our longevity. Being a hosted database solution I can see why. We took that to heart and re-engineered our offering. We de-risked it by minimizing the amount of infrastructure under our management, fly.io manages customer's dedicated SFSQL endpoints,…

    2023 · schemafreesql.com

  22. 22AC
  23. 23RT

    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

  24. 24AD

    I created a data store called Nubostore that is serverless, globally distributed, strongly consistent, low latency, real-time, with Instant-Search engine, and accessible via REST and GraphQL. I wanted a powerful data storage system, without the complexity of database management. Please let me know your thoughts! https://nubo.app/nubostore

    2022

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