Alternatives
Products that do what Real Time Stream Processing Startup does
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
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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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2016 · github.com
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2017 · github.com
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Build real-time apps without maintaining the infrastructure
2017
- 10SD
Hey all! We’ve built a Pandas-like interface to make it easy to work with streaming data using what we call ‘Streaming DataFrames’. For example, suppose that you want to convert speed measurement units from meters per second to kilometers per hour With static data in Pandas, you’d do this: df["speed_km_h"] = df["speed_m_s"] * 3.6 With Streaming DataFrames, it’s pretty much the same thing… sdf["speed_km_h"] = sdf["speed_m_s"] * 3.6 …except it’s being done continuously and the updated records can be sent to an output topic in Kafka with almost no delay after they’ve been processed. You can…
2024 · github.com
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2016 · deepstream.io
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Hi HN, We are launching Denormalized (www.denormalized.io), a serverless real-time data platform built on Kafka and Pinot. We felt a bit burnt out by the sheer developer toil we faced when building application around the real-time data stack and set out to create a platform to allow small teams to be very productive with realtime data without having to glue together an elaborate system to serve real-time as well as time series queries. Here is our motivating post. Would appreciate any and all feedback.
2023 · teamdenormalized.substack.com
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2016 · alooma.com
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2015 · blog.memsql.com
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FastStream - https://github.com/airtai/faststream, a stream processing framework, already supports Kafka stream processing using the aiokafka library, as well as other brokers such as Redis, RabbitMQ, and NATS. Responding to popular demand, the latest 0.4.0rc0 version introduces support for Kafka stream processing using Confluent Kafka's Python library - https://github.com/confluentinc/confluent-kafka-python. Please take a look at it and let us know what you think: https://faststream.airt.ai/0.4/confluent/ Wondering why and how…
2024
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