Aeron: Efficient reliable UDP unicast, UDP multicast, and IPC message transport
91 points · Open discussionaeron-io
aeron
Java2014–2025
aeron-io / aeron
aeron
Efficient reliable UDP unicast, UDP multicast, and IPC message transport
29Distinct people
31Mentions
0Explicit recommenders
9KGitHub stars
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What it is
Efficient reliable UDP unicast, UDP multicast, and IPC message transport
GitHub
Where it is used
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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.
No direct repository links were found in the indexed HN discussions over the past seven days. Older discussions are available below.
Mentions over time
HN mentions by year31 dated mentions
Observed mentions: 2014-11-06 15:09:38 UTC to 2025-07-12 20:25:18 UTC.
Counts come from the repository’s dated source evidence. Index cutoff: 2026-11-02 08:16:59 UTC.
View mention counts and date ranges
| Period | Start (UTC) | End (exclusive, UTC) | Mentions | Submissions | Comments |
|---|---|---|---|---|---|
| 2014 | 2014-01-01 00:00:00 UTC | 2015-01-01 00:00:00 UTC | 2 | 1 | 1 |
| 2015 | 2015-01-01 00:00:00 UTC | 2016-01-01 00:00:00 UTC | 4 | 0 | 4 |
| 2016 | 2016-01-01 00:00:00 UTC | 2017-01-01 00:00:00 UTC | 7 | 2 | 5 |
| 2017 | 2017-01-01 00:00:00 UTC | 2018-01-01 00:00:00 UTC | 2 | 0 | 2 |
| 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 | 6 | 1 | 5 |
| 2021 | 2021-01-01 00:00:00 UTC | 2022-01-01 00:00:00 UTC | 2 | 1 | 1 |
| 2022 | 2022-01-01 00:00:00 UTC | 2023-01-01 00:00:00 UTC | 2 | 0 | 2 |
| 2023 | 2023-01-01 00:00:00 UTC | 2024-01-01 00:00:00 UTC | 3 | 1 | 2 |
| 2024 | 2024-01-01 00:00:00 UTC | 2025-01-01 00:00:00 UTC | 1 | 0 | 1 |
| 2025 | 2025-01-01 00:00:00 UTC | 2026-01-01 00:00:00 UTC | 1 | 1 | 0 |
From the project README
An excerpt from the repository, fetched Nov 13, 2026.
Read the project’s introduction
Aeron
Efficient reliable UDP unicast, UDP multicast, and IPC message transport. Java, C, and C++ clients are available in this
repository, and a .NET client is available. All
clients can exchange messages across machines, or on the same machine via IPC, very efficiently. Message streams can be
recorded by the Archive module to persistent storage
for later, or real-time, replay. Aeron Cluster
provides support for fault-tolerant services as replicated state machines based on the
Raft consensus algorithm.
Performance is the key focus. A design goal for Aeron is to be the highest throughput with the lowest and most
predictable latency of any messaging system. Aeron integrates with
Simple Binary Encoding (SBE) for the best possible message
encoding and decoding performance. Many of the data structures used in the creation of Aeron have been factored out to
the Agrona project.
For details of usage, protocol specification, FAQ, etc., please check out the
Wiki.
For the latest version information and changes, see the Change Log
with Java downloads at Maven Central.
Aeron is owned and operated by Adaptive Financial Consulting. Originally created by Martin Thompson and Todd Montgomery, the Aeron team joined Adaptive in 2022.
For Business users, to get started with Aeron Premium, please visit Aeron.io
We provide a range of services, including:
Training for development and operations with Aeron and Aeron Cluster.
Consulting, for example, if you’re not sure how to design your system or need help tuning your system.
We also offer a number of proprietary enhancements on top of Aeron and Aeron Cluster, such as kernel bypass with DPDK for increased performance, and blazing fast encryption with ATS.
If you’re building a new trading system, we have experienced Aeron developers who can help.
Please get in touch at sales@aeron.io if you would like to learn more about any of these.
How do I use Aeron?
Java Programming Guide
C++11 Programming Guide
Best Practices Guide
Monitoring and Debugging
Configuration Options
Channel Specific Configuration
Aeron Archive (Durable/Persistent Stream Storage)
Aeron Cluster (Fault Tolerant Services)
Aeron Docs
How does Aeron work?
Transport Protocol Specification
Design Overview
Design Principles
Flow Control Semantics
Media Driver Operation
How do I hack on Aeron?
Hacking on Aeron
Performance Testing
Building Aeron
License (See LICENSE file for full license)
Copyright 2014-2025 Real Logic Limited.
Licensed under the Apache License, Version 2.0 (the "License");
you may not use this file except in compliance with the License.
You may obtain a copy of the License at
https://www.apache.org/licenses/LICENSE-2.0
Unless required by applicable law or agreed to in writing, software
distributed under the License is distributed on an "AS IS" BASIS,
WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
See the License for the specific language governing permissions and
limitations under the License.
Read the full README on GitHubWhat Hacker News says
31 sourcesSee https://github.com/real-logic/aeron (also from the creator of the disruptor)
In Ultra-low-latency, batching and concurrent queue for IPC in JavaSemi-related is the Aeron project: https://github.com/real-logic/aeron
In LMAX Disruptor – High Performance Inter-Thread Messaging LibraryNot to be confused with the famous Aeron chair, this Aeron is "efficient reliable UDP unicast, UDP multicast, and IPC message transport."
https://github.com/real-logic/aeron
In Aeron – Proof of the benefits of open developmentAeron: Efficient reliable UDP unicast, UDP multicast, and IPC message transport
2 points · Open discussionIf you're interested in this topic, I highly suggest some of the talks and papers about the LMAX Disruptor [0] and Martin Thompson's latest project Aeron [1]. It targets the JVM, but the lessons are generally applicable since I don't think Concord/Aria are open source.
[0] https://lmax-exchange.github.io/disruptor/
[1] https://github.com/real-logic/aeron
In State machine replication, and why you should careI assume your live subscribers are external people over the internet?
The trading platforms I've worked on tend to order things into a single stream that you can act upon. This helps with testing, race conditions, auditability. You will want to be able to replay an exact series of events to recreate conditions.
LMAX Disruptor[1] and Aeron[2] are two open source examples of something widely used, either using the libraries themselves or as concepts.
Some things that trading systems (generally?) need which you may not, which might simplify your architecture:
- Every message must be delivered and in order. UDP is usually used over TCP, as the platform will likely want more control over handling missed messages.
- It will be common to have read/write applications that need to add a message as a response. Writing is difficult as you need to be
Read the rest
quick, otherwise a subsequent message from another application might invalidate your message.
Do subscribers need older data? How do dropped packets impact the system? Can they just be forgotten? What latency requirements do you have? Do subscribers also write to the same stream?
- [1] https://lmax-exchange.github.io/disruptor/
- [2] https://github.com/real-logic/aeron
It targets the properties that Aeron protocol aims for too (https://github.com/real-logic/aeron).
In Homa, a transport protocol to replace TCP for low-latency RPC in data centersAeron: Low-latency, reliable networking over UDP
3 points · Open discussion>> Almost no one provides tooling and platforms that address it
I think this is due to the nature of the mentioned companies are not being too common (yet?). There are tools and systems that you can use, especially from high frequency trading which has somewhat similar challenges. KDB+ and co. would be my first stop to check if there is something that I could use. The question is the financial structure and scaling of the problem, to determine if these tools are in game. There are other interesting projects in the space:
- https://github.com/real-logic/aeron
- https://lmax-exchange.github.io/disruptor/
Of course these are not exactly what you need, long term storage and querying (like KDB) is largely unsolved.
The other tools that you might be referring to by "most of the opensource platforms" indeed are not capable doing this. I spent th
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e last 10 years on optimizing such platforms but it is not even remotely close to what you need, you (or anybody who thinks these could be optimized) are wasting your time.
Just off the top of my head, there are .NET copies of:
- Akka https://github.com/akka/akka
- Lucene https://github.com/apache/lucene-solr
- Aeron https://github.com/real-logic/aeron
- Retrofit https://github.com/square/retrofit
Not to mention projects like Apache Spark, Cassandra, Elasticsearch, Druid - Java projects. Many projects (Foundation DB, Scylla DB, I could find more) will have in-house support for Java and not .NET.
The .NET equivalents to these libraries tend to be playing catch up. Xamarin Android will always be playing catch-up to Android's Java/Kotlin APIs for Android. Big machine learning projects like PyTorch and TensorFlow tend to give first-class support of some fashion to a Java API (mostly due to Android). Is there a .NET equivalent to Deeplearning4j? Hadoop? Hive? Kakfa?
In Java there is a proliferation of web project
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s: Spring, Vert.x, Quarkus, Micronaut, Play 2, Spark Java; Netty, Jetty, Apache. In .NET all you ever hear about is Microsoft projects ASP.NET core; Kestrel, IIS.
Working as a .NET dev, when there is an SDK, if it's not from Microsoft, it's clear the .NET SDK is a lower priority for bug fixes and new features compared to e.g. the Java/Python/etc.
This reminds me a bit of Aeron (https://github.com/real-logic/aeron) which is a reliable UDP uni/multicast transport library with built-in flow control. It's written in Java and seems to have superb performance (I haven't used it myself). Might be an interesting alternative if you don't want to write it all yourself.
In Launch HN: QuestDB (YC S20) – Fast open source time series databaseCouple of protocols that would be nice to benchmark for comparison:
* AMQP 1.0 - can also be used for RPC without a broker in between client and server. See https://qpid.apache.org/proton/
* Aeron - low latency, UDP based, see https://github.com/real-logic/aeron
In RPC Olympics – The Search for the Perfect RPC ProtocolAeron[1] is something I have been look at as well.
I like that it is adaptable to run without an external broker (using embedded media driver option), yet can add that for scalability/redundancy.
Our use cases do not require a query on top of streams.
Instead all data would go into timescaleDB [2].
[1] https://github.com/real-logic/aeron/wiki/Java-Programming-Gu...
[2] https://github.com/timescale/timescaledb
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