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

Apache Ignite vs Azure Redis Cache

OverviewComparisonAlternatives

Overview

Azure Redis Cache
Azure Redis Cache
Stacks58
Followers124
Votes7
Apache Ignite
Apache Ignite
Stacks110
Followers168
Votes41
GitHub Stars5.0K
Forks1.9K

Apache Ignite vs Azure Redis Cache: What are the differences?

Introduction

In this article, we will discuss the key differences between Apache Ignite and Azure Redis Cache.

  1. Language Support: Apache Ignite supports multiple programming languages such as Java, .NET, C++, and Node.js, making it compatible with a wide range of applications. On the other hand, Azure Redis Cache primarily focuses on providing support for programming languages commonly used in the Microsoft ecosystem, such as C#, Java, Python, and JavaScript.

  2. Cache Architecture: Apache Ignite offers a distributed in-memory cache architecture that allows for storing a large amount of data in memory, providing excellent performance for data-intensive applications. In contrast, Azure Redis Cache follows a traditional cache architecture where data is stored in memory, but it also supports persistence to disk.

  3. Distributed Computations: One significant difference between Apache Ignite and Azure Redis Cache is their support for distributed computations. Apache Ignite provides a built-in compute grid that enables parallel execution of complex computations across a cluster of nodes. On the other hand, Azure Redis Cache does not offer a similar built-in feature for distributed computations.

  4. Data Partitioning: Apache Ignite offers flexible data partitioning strategies, allowing for efficient data distribution across a cluster of nodes, reducing the chances of hotspots and ensuring high scalability. In contrast, Azure Redis Cache does not provide granular control over data partitioning and relies on a sharding mechanism that is managed by Microsoft.

  5. Data Durability and Persistence: Apache Ignite provides options for data durability and persistence, with features such as write-through, write-behind, and disk-based persistence. This ensures that data is not lost in the event of node failures or system restarts. In contrast, Azure Redis Cache primarily focuses on in-memory caching and does not offer built-in mechanisms for data persistence.

  6. Pricing Model: Apache Ignite follows an open-source model, allowing users to use it for free without any licensing costs. However, there may be costs associated with infrastructure, support, and maintenance. Azure Redis Cache, being a managed service provided by Microsoft, has its pricing model based on factors such as cache size, data transfer, and throughput.

In summary, Apache Ignite offers broader language support, a distributed compute grid, flexible data partitioning, and data durability features, while Azure Redis Cache primarily focuses on in-memory caching with limited language support and persistence options. Additionally, Apache Ignite follows an open-source model, while Azure Redis Cache has a pricing model based on usage.

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Detailed Comparison

Azure Redis Cache
Azure Redis Cache
Apache Ignite
Apache Ignite

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.

It is a memory-centric distributed database, caching, and processing platform for transactional, analytical, and streaming workloads delivering in-memory speeds at petabyte scale

Enterprise-grade security; Flexible scaling; Improve application throughput and latency; Speed up applications with a distributed cache
Memory-Centric Storage; Distributed SQL; Distributed Key-Value
Statistics
GitHub Stars
-
GitHub Stars
5.0K
GitHub Forks
-
GitHub Forks
1.9K
Stacks
58
Stacks
110
Followers
124
Followers
168
Votes
7
Votes
41
Pros & Cons
Pros
  • 4
    Cache-cluster
  • 3
    Redis
Pros
  • 5
    Multiple client language support
  • 5
    Written in java. runs on jvm
  • 5
    Free
  • 5
    High Avaliability
  • 4
    Load balancing
Integrations
Spring Boot
Spring Boot
Java
Java
MongoDB
MongoDB
MySQL
MySQL
Apache Spark
Apache Spark

What are some alternatives to Azure Redis Cache, Apache Ignite?

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.

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

KeyDB

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.

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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