hazelcast-jet

Distributed Stream and Batch Processing

Systems & Infrastructure Data & Databases

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3Mentions

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REPOSITORY AT A GLANCE

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What it is

Distributed Stream and Batch Processing

GitHub

Where it is used

No documented product use has been verified yet.

What people are saying

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Also in these discussions

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This week on Hacker News

Nov 7–Nov 14 UTC · Direct repository links and separately labeled related project stories. Indexed through 11/14/2026, 5:04:57 PM UTC.

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Mentions over time

HN mentions by year3 dated mentions

Observed mentions: 2018-06-11 20:57:23 UTC to 2021-07-13 19:53:37 UTC.

Counts come from the repository’s dated source evidence. Index cutoff: 2026-11-02 08:16:59 UTC.

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Period	Start (UTC)	End (exclusive, UTC)	Mentions	Submissions	Comments
2018	2018-01-01 00:00:00 UTC	2019-01-01 00:00:00 UTC	1	0	1
2019	2019-01-01 00:00:00 UTC	2020-01-01 00:00:00 UTC	0	0	0
2020	2020-01-01 00:00:00 UTC	2021-01-01 00:00:00 UTC	1	1	0
2021	2021-01-01 00:00:00 UTC	2022-01-01 00:00:00 UTC	1	0	1

What Hacker News says

3 sources

antpls·Jul 13, 2021

Since no one mentioned it in the comments so far, please add Hazelcast Jet to the long list of stream processors : https://github.com/hazelcast/hazelcast-jet

In Apache Heron: A realtime, distributed, fault-tolerant stream processing engine

cangencer·Aug 11, 2020Submission

Show HN: Jet – in-memory, fault-tolerant, distributed stream processing

129 points · Open discussion

cangencer·Jun 11, 2018

Single process "streaming" or basically CEP engines have been around for a very long time and used to be the norm before distributed stream processing engines came around (such as Storm). CEP engines have much richer functionality than distributed stream processing engines because they don't need to deal with partitioning or data distribution. I'm not quite sure I see the appeal of making a non-distributed engine but with the same limitations of a distributed engine. I work on Hazelcast Jet [1], which is a Java based distributed stream processing engine. The core engine is fast enough that it can be used with very good throughput on a single node (several times faster compared to Flink or Spark) but usually several nodes are not only needed strictly for parallelization but also for tolerating node failures and being able to restart where

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you left off. As others have pointed out, not every computation can be parallelised efficiently. Jet also offers in memory storage, so adding more nodes also increases your storage capacity. Since the core of Jet is small enough (~400kb JAR), we also considered making a non-distributed version that runs strictly in process. Mainly for lightweight usage or embedding but would also offer a path to distributed execution, if it was ever needed. [1] https://github.com/hazelcast/hazelcast-jet

In Do We Need Distributed Stream Processing?