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Solution for hash-map with >100M values
7 projects | reddit.com/r/java | 21 Dec 2020
Do you need to update the data after initial load? If not, then I would suggest using my Paldb fork , otherwise you could try my lasher library. It's in early stage but first results are very promising, I was testing it with 10-100M elements and the performance was similar to java hashmap.
We haven't tracked posts mentioning PalDB yet.
Tracking mentions began in Dec 2020.
What are some alternatives?
Oak - A Scalable Concurrent Key-Value Map for Big Data Analytics
SmoothieMap - A gulp of low latency Java
MapDB - MapDB provides concurrent Maps, Sets and Queues backed by disk storage or off-heap-memory. It is a fast and easy to use embedded Java database engine.
Chronicle Map - Replicate your Key Value Store across your network, with consistency, persistance and performance.
ReplDBClient - A Java Client for ReplDB
time-series-concurrency-example - Time Series Data and CompletableFuture example in Java
java-concurrent-hash-trie-map - Java port of a concurrent trie hash map implementation from the Scala collections library
FastKV - An efficient key-value storage library.
Elasticsearch - Free and Open, Distributed, RESTful Search Engine