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Description

SwayDB is a type-safe & non-blocking key-value storage library for single/multiple disks and in-memory storage.

It's an implementation of Log-structured merge-tree written in Scala with asynchronous Leveled Compaction based on push-pull strategy built on the Actor model.

It supports configurable Graph like file format for faster reads and has compression support for both memory & persistent databases.

Documentation: http://swaydb.io

Programming language: Scala
License: Apache License 2.0
Tags: Database     Tools     Type-Safe    
Latest version: v0.16.2

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README

SwayDB Gitter Chat Build status Maven central

Persistent and in-memory key-value storage engine for the JVM aimed at high performance & resource efficiency.

Small footprint: around 7.1 MB jar size. No external core dependency (#307).

Scalable on a single machine: Distribute data to multiple local SSDs. Allocate single or multiple Threads for reads, caching & compaction.

Branches: This is the development branch. See master for stable version.

Status: Under testing & performance optimisations. See project status.

Documentation

Sponsors

Thank you JetBrains & JProfiler for full-featured open-source licences to their awesome development tools!

[Become a sponsor]

Overview

  • Simple data types - Map, Set, Queue, SetMap & MultiMap with native Java and Scala collections support.
  • Conditional updates using any pure JVM function - No query language.
  • Atomic updates and inserts with Transaction API.
  • Non-blocking core with configurable APIs for blocking, non-blocking and/or reactive use-cases.
  • Single or multiple disks persistent, in-memory or eventually persistent.
  • Streams - Async & sync forward and reverse data streaming/iteration.
  • TTL - non-blocking, non-polling asynchronous auto expiring key-values.
  • Range operations to update, remove & expire a range of key-values.
  • Key only iterations (Lazily fetched values).
  • Configurable compression with LZ4 & Snappy
  • Configurable core internals to support custom workloads.
  • Duplicate values elimination with compressDuplicateValues.

Use cases

Highly configurable to suit different workloads. Some known use-cases are:

  • General key-value storage
  • Message queues
  • Time-series or Events data
  • Caching
  • Application logs
  • Archiving data or cold storage with high file level compression

Quick start

Contributing

Contributions are encouraged and welcomed. We are here to help and answer any questions.

Code of conduct - Be nice, welcoming, friendly & supportive of each other. Follow the Apache foundation's COC.

  • Contributing to data management API

    • Build new data structures extending existing data structures. See MultiMap for example which is an extension of Map.
      • Graph
      • List
      • Geospatial
      • Logs
      • Observables
      • Full-text search
      • etc
    • Add support for external serialising, streaming & compression libraries.
    • Test and improve existing data structures.
  • Contributing to core API

  • Contributing to core internals

    • See code marked TODO.
    • Pick any small section to improve. You will find that everything is a function and can be unit-tested independently, so you can easily pick anything to work on.

Project status

Under testing & performance optimisations.

Your feedback and support is very important to get to production. Please get involved via chat, discussion, issues or by becoming a sponsor.

Future releases might not be backward compatible until we are production ready.

See tasks labelled Production release that are required before becoming production ready.

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