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  1. Stackups
  2. Application & Data
  3. In-Memory Databases
  4. In Memory Databases
  5. Azure Redis Cache vs KeyDB

Azure Redis Cache vs KeyDB

OverviewComparisonAlternatives

Overview

Azure Redis Cache
Azure Redis Cache
Stacks58
Followers124
Votes7
KeyDB
KeyDB
Stacks37
Followers62
Votes5

Azure Redis Cache vs KeyDB: What are the differences?

Introduction

Azure Redis Cache and KeyDB are both in-memory data stores that can be used to improve the performance and scalability of web applications. However, there are several key differences between these two technologies that make them suitable for different use cases. Let's explore those differences in detail.

  1. Architecture: Azure Redis Cache is based on the open-source Redis database, while KeyDB is a Redis fork that aims to provide improved performance and scalability. KeyDB achieves this by implementing multi-threading, allowing more efficient utilization of CPU cores.

  2. Scalability: Azure Redis Cache is a fully managed service provided by Microsoft Azure, which means that it offers global distribution, automatic failover, and automatic scaling. On the other hand, KeyDB can be deployed on any infrastructure and can be scaled horizontally by adding more instances. This makes KeyDB more suitable for environments where fine-grained control over scalability is required.

  3. Compatibility: Azure Redis Cache is fully compatible with Redis, which means that any code or application that works with Redis can also work with Azure Redis Cache without any modifications. KeyDB also provides a high level of compatibility with Redis, but there might be some differences in behavior or features that need to be considered when migrating from Redis to KeyDB.

  4. Performance: KeyDB is designed to provide improved performance compared to Redis. By implementing multi-threading, KeyDB can take advantage of multiple CPU cores, allowing it to handle a higher volume of requests and achieve lower latencies. Azure Redis Cache also provides high performance, but it might not be able to match the performance of KeyDB in certain scenarios.

  5. Persistence: Azure Redis Cache supports different persistence options, including the ability to persist data on disk and achieve high availability through replication. KeyDB also supports persistence, but it provides additional options such as AOF (Append Only File) and RDB (Redis Database) persistence. These options provide different trade-offs between performance and durability.

  6. Ease of Management: Azure Redis Cache is a fully managed service, which means that Microsoft takes care of managing and maintaining the infrastructure, including backups and patching. This makes it easier for developers to focus on application development without worrying about infrastructure management. KeyDB, on the other hand, requires manual management and maintenance, which might require more effort from the developers or operations team.

In Summary, Azure Redis Cache is a fully managed service provided by Microsoft Azure, offering global distribution, automatic failover, and automatic scaling, while KeyDB is a Redis fork that provides improved performance and scalability through multi-threading. Azure Redis Cache offers ease of management and compatibility with Redis, while KeyDB provides fine-grained scalability control and additional persistence options.

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Detailed Comparison

Azure Redis Cache
Azure Redis Cache
KeyDB
KeyDB

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 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.

Enterprise-grade security; Flexible scaling; Improve application throughput and latency; Speed up applications with a distributed cache
Active Replication; FLASH storage support; direct backup to AWS S3; MultiMaster; Multithreaded
Statistics
Stacks
58
Stacks
37
Followers
124
Followers
62
Votes
7
Votes
5
Pros & Cons
Pros
  • 4
    Cache-cluster
  • 3
    Redis
Pros
  • 3
    Performance
  • 2
    Active Replication
Integrations
Spring Boot
Spring Boot
Java
Java
No integrations available

What are some alternatives to Azure Redis Cache, KeyDB?

Redis

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.

Hazelcast

Hazelcast

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.

Aerospike

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

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

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

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

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

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

LokiJS

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

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.

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