Real Time Analytics SaaS
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…
Real Time Analytics SaaS launched on November 13, 2021 with 7 votes, #1,458 of 2,925 launches that month and more than 50% of that year's launches.
What it does
In the maker’s words, at launch
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…
Does a similar job
all alternatives →- RTReal Time Stream Processing Startup2020 · ▲6
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
Deepstream.io – open-source real-time server with pub/sub and data sync2016 · deepstream.io · ▲301A realtime server for the modern web


- LVLive visualization of Kafka streams2016 · alooma.com · ▲144
DuckDB for Kafka Stream ProcessingDec 2025 · sql-flow.com · ▲77Hello 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…
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