Chronicle Map
JetBrains Xodus
| Chronicle Map | JetBrains Xodus | |
|---|---|---|
| 5 | 1 | |
| 2,770 | 1,181 | |
| 0.6% | 0.3% | |
| 8.7 | 9.0 | |
| 4 days ago | 7 days ago | |
| Java | Java | |
| Apache License 2.0 | Apache License 2.0 |
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.
Chronicle Map
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Indexing All of Wikipedia on a Laptop
We’re using JVector for the vector index and Chronicle Map for the article data. There are several things I don’t love about Chronicle Map, but nothing else touches it for simple disk-based key/value performance.
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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.
JetBrains Xodus
What are some alternatives?
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.
Redisson - Redisson - Easy Redis Java client and Real-Time Data Platform. Valkey compatible. Sync/Async/RxJava/Reactive API. Over 50 Redis or Valkey based Java objects and services: Set, Multimap, SortedSet, Map, List, Queue, Deque, Semaphore, Lock, AtomicLong, Map Reduce, Bloom filter, Spring, Tomcat, Scheduler, JCache API, Hibernate, RPC, local cache...
H2 - H2 is an embeddable RDBMS written in Java.
Spring Data JPA - Simplifies the development of creating a JPA-based data access layer.
Jedis - Redis Java client
Realm - Realm is a mobile database: a replacement for SQLite & ORMs
Speedment - Speedment is a Stream ORM Java Toolkit and Runtime
OrientDB - OrientDB is the most versatile DBMS supporting Graph, Document, Reactive, Full-Text and Geospatial models in one Multi-Model product. OrientDB can run distributed (Multi-Master), supports SQL, ACID Transactions, Full-Text indexing and Reactive Queries.
HikariCP - 光 HikariCP・A solid, high-performance, JDBC connection pool at last.
MariaDB4j - MariaDB Embedded in Java JAR