Oak
A Scalable Concurrent Key-Value Map for Big Data Analytics (by yahoo)
Chronicle Map
Replicate your Key Value Store across your network, with consistency, persistance and performance. (by OpenHFT)
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Oak | Chronicle Map | |
---|---|---|
2 | 4 | |
266 | 2,684 | |
0.0% | 0.8% | |
0.0 | 8.4 | |
3 months ago | 7 days ago | |
Java | Java | |
Apache License 2.0 | Apache License 2.0 |
The number of mentions indicates the total number of mentions that we've tracked plus the number of user suggested alternatives.
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
Oak
Posts with mentions or reviews of Oak.
We have used some of these posts to build our list of alternatives
and similar projects. The last one was on 2022-10-11.
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JEP draft: 64 bit object headers
Another to add to your collection, https://github.com/yahoo/Oak
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Solution for hash-map with >100M values
Consider using an database (e.g. H2 embedded, redis) with an on-heap cache (e.g. Caffeine). Since you say it is a Zipfian distribution, the cache should absorb most of the requests. For an off-heap hashtable, you might try Oak as it is likely a faster implementation.
Chronicle Map
Posts with mentions or reviews of Chronicle Map.
We have used some of these posts to build our list of alternatives
and similar projects. The last one was on 2023-10-27.
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GC, hands off my data!
I decided to start with an overview of what open-source options are currently available. When it comes to the implementation of the on-heap cache mechanism, the options are numerous – there is well known: guava, ehcache, caffeine and many other solutions. However, when I began researching cache mechanisms offering the possibility of storing data outside GC control, I found out that there are very few solutions left. Out of the popular ones, only Terracotta is supported. It seems that this is a very niche solution and we do not have many options to choose from. In terms of less-known projects, I came across Chronicle-Map, MapDB and OHC. I chose the last one because it was created as part of the Cassandra project, which I had some experience with and was curious about how this component worked:
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Off-heap memory in Java
Chronicle-Map: Chronicle Map is an in-memory, key-value store, designed for low-latency, and/or multi-process applications.
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Solution for hash-map with >100M values
I've wrangled data sets in the ~600gb range using nothing but plain old Java and a few beefy boxes. This can all be kept in memory, but you have to go off-heap. You can use Chronicle Map and Chronicle Values to model this data and work with it off-heap in a way that's still very clean and object oriented. 128gb of RAM is cheap these days, whether you're in the cloud or not.