Alternatives
Products that do what Sequin – A Kafka Alternative to REST APIs does
Hey HN! We're Eric, Carter, and Anthony from Sequin (https://sequin.io). Sequin streams data from platforms like Stripe, AWS, and Salesforce into messaging systems like Kafka. Sequin loads historic data into topics and then streams new changes in real-time. You can provision a stream of API data with a single POST request. This means you can add third-party data to your apps and internal tools super fast. We support streaming to Kafka and NATS. If you don’t have a messaging system, you can use our serverless hosted one. To get your data at rest, you can stream to databases like…
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Hi HN community, I'm Anthony, co-founder of Sequin (sequin.io), and am excited to show you what we've been working on. Sequin lets you skip HTTP APIs and integrate with Postgres and SQL instead. While we originally launched with a one-way sync from APIs to Postgres, as of today, you can now _write back_ to APIs using `insert`, `update`, and `delete` on your synced tables. We built Sequin because no one is happy with HTTP APIs today. For developers that need to build on top of third-party APIs, each integration is bespoke. There are few standards. I've personally seen over a dozen different…
2023
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2017 · github.com
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2020 · github.com
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2016 · alooma.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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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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2020 · github.com
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2017 · github.com
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2016 · heartbeat.appbase.io
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Hey HN! We recently launched a new capability to Hasura GraphQL Engine: Streaming Subscriptions for Postgres. Today we have a variety of solutions to ingest and store a large amount of data or a stream of data. However, once this data has been captured, securely exposing this data as a continuous stream to a large number of HTTP clients concurrently is a challenge. These are the challenges that Hasura aims to address: 1. Allow for Authorization rules so that clients can only consume the subset of the stream they have access to 2. Prevent missing events and allow each client to move through…
2022 · hasura.io
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2015 · github.com
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2016 · restdb.io
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2020 · github.com
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