Hazelcast vs LokiJS vs Redis

Overview

Redis

Stacks61.9K

Followers46.5K

Votes3.9K

GitHub Stars42

Forks6

Hazelcast

Stacks427

Followers474

Votes59

GitHub Stars6.4K

Forks1.9K

LokiJS

Stacks43

Followers57

Votes3

GitHub Stars6.8K

Forks483

Hazelcast vs LokiJS vs Redis: What are the differences?

# Introduction

Key differences between Hazelcast, LokiJS, and Redis are outlined below:

1. **Data Storage and Retrieval**: Hazelcast is a distributed, in-memory data grid that provides high-performance data storage and retrieval for large volumes of data. LokiJS, on the other hand, is an in-memory database that stores data in JavaScript objects and operates locally within the browser, making it suitable for small-scale applications. Redis, a popular open-source in-memory data structure store, offers versatile data storage capabilities, including caching, messaging, and real-time analytics.

2. **Data Persistence**: While Hazelcast and Redis support data persistence to disk, allowing data to be stored even after system restarts, LokiJS focuses primarily on in-memory operations and does not offer built-in disk persistence. This distinction makes Hazelcast and Redis more suitable for applications requiring durable data storage and recovery in case of failures.

3. **Scalability and Performance**: Hazelcast is designed for horizontal scalability by distributing data across multiple nodes in a cluster, ensuring high performance and low latency. In contrast, LokiJS and Redis can scale vertically by deploying on more powerful hardware but may encounter limitations in handling massive datasets compared to Hazelcast's distributed architecture.

4. **Data Querying and Indexing**: While Redis supports indexing and querying of data using a variety of data structures like sets, lists, and sorted sets, Hazelcast focuses on distributed data processing and event-driven architecture rather than traditional database querying functionalities. LokiJS provides basic querying capabilities but may not match the performance of Redis for complex data operations.

5. **Programming Language Support**: Hazelcast and Redis offer client libraries for various programming languages, making it easier for developers to integrate these databases into their applications. LokiJS, being tailored for JavaScript environments, provides native support for JavaScript objects and libraries but may require additional effort for integration with other programming languages.

6. **Community Ecosystem and Support**: Redis has a robust community ecosystem with extensive documentation, tutorials, and community plugins available for developers. Hazelcast also has a dedicated community and commercial support options, whereas LokiJS, being a more niche solution, may have limited community resources and support avenues available to users.

In Summary, the key differences between Hazelcast, LokiJS, and Redis lie in their data storage mechanisms, persistence capabilities, scalability, querying functionalities, programming language support, and community support ecosystems.

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CLI (Node.js)

Manual

Detailed Comparison

Redis	Hazelcast	LokiJS
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.	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.	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.
-	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	-
Statistics
GitHub Stars 42	GitHub Stars 6.4K	GitHub Stars 6.8K
GitHub Forks 6	GitHub Forks 1.9K	GitHub Forks 483
Stacks 61.9K	Stacks 427	Stacks 43
Followers 46.5K	Followers 474	Followers 57
Votes 3.9K	Votes 59	Votes 3
Pros & Cons
Pros 888 Performance 542 Super fast 514 Ease of use 444 In-memory cache 324 Advanced key-value cache Cons 15 Cannot query objects directly 3 No secondary indexes for non-numeric data types 1 No WAL	Pros 11 High Availibility 6 Distributed compute 6 Distributed Locking 5 Sharding 4 Load balancing Cons 4 License needed for SSL	Pros 3 Can query the objects directly
Integrations
No integrations available	Java Spring	Node.js NativeScript Apache Cordova PhoneGap

What are some alternatives to Redis, Hazelcast, LokiJS?

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.

KeyDB

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.

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.

NCache

NCache is an open source distributed cache for .NET & .NET Core (Apache 2.0) by Alachisoft. NCache provides an extremely fast and linearly scalable distributed cache that caches application data and reduces expensive database trips.

Related Comparisons

Hazelcast vs LokiJS vs Redis: What are the differences?

# Introduction

Key differences between Hazelcast, LokiJS, and Redis are outlined below:

1. **Data Storage and Retrieval**: Hazelcast is a distributed, in-memory data grid that provides high-performance data storage and retrieval for large volumes of data. LokiJS, on the other hand, is an in-memory database that stores data in JavaScript objects and operates locally within the browser, making it suitable for small-scale applications. Redis, a popular open-source in-memory data structure store, offers versatile data storage capabilities, including caching, messaging, and real-time analytics.

2. **Data Persistence**: While Hazelcast and Redis support data persistence to disk, allowing data to be stored even after system restarts, LokiJS focuses primarily on in-memory operations and does not offer built-in disk persistence. This distinction makes Hazelcast and Redis more suitable for applications requiring durable data storage and recovery in case of failures.

3. **Scalability and Performance**: Hazelcast is designed for horizontal scalability by distributing data across multiple nodes in a cluster, ensuring high performance and low latency. In contrast, LokiJS and Redis can scale vertically by deploying on more powerful hardware but may encounter limitations in handling massive datasets compared to Hazelcast's distributed architecture.

4. **Data Querying and Indexing**: While Redis supports indexing and querying of data using a variety of data structures like sets, lists, and sorted sets, Hazelcast focuses on distributed data processing and event-driven architecture rather than traditional database querying functionalities. LokiJS provides basic querying capabilities but may not match the performance of Redis for complex data operations.

5. **Programming Language Support**: Hazelcast and Redis offer client libraries for various programming languages, making it easier for developers to integrate these databases into their applications. LokiJS, being tailored for JavaScript environments, provides native support for JavaScript objects and libraries but may require additional effort for integration with other programming languages.

6. **Community Ecosystem and Support**: Redis has a robust community ecosystem with extensive documentation, tutorials, and community plugins available for developers. Hazelcast also has a dedicated community and commercial support options, whereas LokiJS, being a more niche solution, may have limited community resources and support avenues available to users.

In Summary, the key differences between Hazelcast, LokiJS, and Redis lie in their data storage mechanisms, persistence capabilities, scalability, querying functionalities, programming language support, and community support ecosystems.

Hazelcast vs LokiJS vs Redis

Overview