Hazelcast vs KeyDB
Overview
Detailed Comparison
With its various distributed data structures, distributed caching capabilities, elastic nature, memcache support, integration with Spring and Hibernate and more importantly with so many happy users, Hazelcast is feature-rich, enterprise-ready and developer-friendly in-memory data grid solution. | KeyDB is a fully open source database that aims to make use of all hardware resources. KeyDB makes it possible to breach boundaries often dictated by price and complexity. |
Distributed implementations of java.util.{Queue, Set, List, Map};Distributed implementation of java.util.concurrent.locks.Lock;Distributed implementation of java.util.concurrent.ExecutorService;Distributed MultiMap for one-to-many relationships;Distributed Topic for publish/subscribe messaging;Synchronous (write-through) and asynchronous (write-behind) persistence;Transaction support;Socket level encryption support for secure clusters;Second level cache provider for Hibernate;Monitoring and management of the cluster via JMX;Dynamic HTTP session clustering;Support for cluster info and membership events;Dynamic discovery, scaling, partitioning with backups and fail-over | Active Replication; FLASH storage support; direct backup to AWS S3; MultiMaster; Multithreaded |
Statistics | |
GitHub Stars 6.4K | GitHub Stars - |
GitHub Forks 1.9K | GitHub Forks - |
Stacks 354 | Stacks 37 |
Followers 474 | Followers 62 |
Votes 59 | Votes 5 |
Pros & Cons | |
Pros
Cons
| Pros
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Integrations | |
| No integrations available | |
What are some alternatives to Hazelcast, KeyDB?
Redis
Redis is an open source (BSD licensed), in-memory data structure store, used as a database, cache, and message broker. Redis provides data structures such as strings, hashes, lists, sets, sorted sets with range queries, bitmaps, hyperloglogs, geospatial indexes, and streams.
Aerospike
Aerospike is an open-source, modern database built from the ground up to push the limits of flash storage, processors and networks. It was designed to operate with predictable low latency at high throughput with uncompromising reliability – both high availability and ACID guarantees.
MemSQL
MemSQL converges transactions and analytics for sub-second data processing and reporting. Real-time businesses can build robust applications on a simple and scalable infrastructure that complements and extends existing data pipelines.
Apache Ignite
It is a memory-centric distributed database, caching, and processing platform for transactional, analytical, and streaming workloads delivering in-memory speeds at petabyte scale
SAP HANA
It is an application that uses in-memory database technology that allows the processing of massive amounts of real-time data in a short time. The in-memory computing engine allows it to process data stored in RAM as opposed to reading it from a disk.
VoltDB
VoltDB is a fundamental redesign of the RDBMS that provides unparalleled performance and scalability on bare-metal, virtualized and cloud infrastructures. VoltDB is a modern in-memory architecture that supports both SQL + Java with data durability and fault tolerance.
Tarantool
It is designed to give you the flexibility, scalability, and performance that you want, as well as the reliability and manageability that you need in mission-critical applications
Azure Redis Cache
It perfectly complements Azure database services such as Cosmos DB. It provides a cost-effective solution to scale read and write throughput of your data tier. Store and share database query results, session states, static contents, and more using a common cache-aside pattern.
LokiJS
LokiJS is a document oriented database written in javascript, published under MIT License. Its purpose is to store javascript objects as documents in a nosql fashion and retrieve them with a similar mechanism. Runs in node (including cordova/phonegap and node-webkit), nativescript and the browser.
BuntDB
BuntDB is a low-level, in-memory, key/value store in pure Go. It persists to disk, is ACID compliant, and uses locking for multiple readers and a single writer. It supports custom indexes and geospatial data. It's ideal for projects that need a dependable database and favor speed over data size.
