Alternatives to Azure Redis Cache logo

Alternatives to Azure Redis Cache

Amazon ElastiCache, Azure CDN, Redis, Hazelcast, and Aerospike are the most popular alternatives and competitors to Azure Redis Cache.
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What is Azure Redis Cache and what are its top alternatives?

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.
Azure Redis Cache is a tool in the In-Memory Databases category of a tech stack.

Top Alternatives to Azure Redis Cache

  • Amazon ElastiCache

    Amazon ElastiCache

    ElastiCache improves the performance of web applications by allowing you to retrieve information from fast, managed, in-memory caches, instead of relying entirely on slower disk-based databases. ElastiCache supports Memcached and Redis. ...

  • Azure CDN

    Azure CDN

    It lets you reduce load times, save bandwidth, and speed responsiveness—whether you’re developing or managing websites or mobile apps, or encoding and distributing streaming media, gaming software, firmware updates, or IoT endpoints. ...

  • Redis

    Redis

    Redis is an open source, BSD licensed, advanced key-value store. It is often referred to as a data structure server since keys can contain strings, hashes, lists, sets and sorted sets. ...

  • 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. ...

  • 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. ...

  • 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 ...

  • 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. ...

Azure Redis Cache alternatives & related posts

Amazon ElastiCache logo

Amazon ElastiCache

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Deploy, operate, and scale an in-memory cache in the cloud
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PROS OF AMAZON ELASTICACHE
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    Redis
  • 31
    High-performance
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    Backed by amazon
  • 20
    Memcached
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    Elastic
CONS OF AMAZON ELASTICACHE
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    related Amazon ElastiCache posts

    John Kodumal

    As we've evolved or added additional infrastructure to our stack, we've biased towards managed services. Most new backing stores are Amazon RDS instances now. We do use self-managed PostgreSQL with TimescaleDB for time-series data—this is made HA with the use of Patroni and Consul.

    We also use managed Amazon ElastiCache instances instead of spinning up Amazon EC2 instances to run Redis workloads, as well as shifting to Amazon Kinesis instead of Kafka.

    See more
    Julien DeFrance
    Principal Software Engineer at Tophatter · | 16 upvotes · 2.2M views

    Back in 2014, I was given an opportunity to re-architect SmartZip Analytics platform, and flagship product: SmartTargeting. This is a SaaS software helping real estate professionals keeping up with their prospects and leads in a given neighborhood/territory, finding out (thanks to predictive analytics) who's the most likely to list/sell their home, and running cross-channel marketing automation against them: direct mail, online ads, email... The company also does provide Data APIs to Enterprise customers.

    I had inherited years and years of technical debt and I knew things had to change radically. The first enabler to this was to make use of the cloud and go with AWS, so we would stop re-inventing the wheel, and build around managed/scalable services.

    For the SaaS product, we kept on working with Rails as this was what my team had the most knowledge in. We've however broken up the monolith and decoupled the front-end application from the backend thanks to the use of Rails API so we'd get independently scalable micro-services from now on.

    Our various applications could now be deployed using AWS Elastic Beanstalk so we wouldn't waste any more efforts writing time-consuming Capistrano deployment scripts for instance. Combined with Docker so our application would run within its own container, independently from the underlying host configuration.

    Storage-wise, we went with Amazon S3 and ditched any pre-existing local or network storage people used to deal with in our legacy systems. On the database side: Amazon RDS / MySQL initially. Ultimately migrated to Amazon RDS for Aurora / MySQL when it got released. Once again, here you need a managed service your cloud provider handles for you.

    Future improvements / technology decisions included:

    Caching: Amazon ElastiCache / Memcached CDN: Amazon CloudFront Systems Integration: Segment / Zapier Data-warehousing: Amazon Redshift BI: Amazon Quicksight / Superset Search: Elasticsearch / Amazon Elasticsearch Service / Algolia Monitoring: New Relic

    As our usage grows, patterns changed, and/or our business needs evolved, my role as Engineering Manager then Director of Engineering was also to ensure my team kept on learning and innovating, while delivering on business value.

    One of these innovations was to get ourselves into Serverless : Adopting AWS Lambda was a big step forward. At the time, only available for Node.js (Not Ruby ) but a great way to handle cost efficiency, unpredictable traffic, sudden bursts of traffic... Ultimately you want the whole chain of services involved in a call to be serverless, and that's when we've started leveraging Amazon DynamoDB on these projects so they'd be fully scalable.

    See more
    Azure CDN logo

    Azure CDN

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    A global CDN solution for delivering high-bandwidth content
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    PROS OF AZURE CDN
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      Low Latency
    CONS OF AZURE CDN
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      Redis logo

      Redis

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      PROS OF REDIS
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        Performance
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        Super fast
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        Ease of use
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        In-memory cache
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        Advanced key-value cache
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        Open source
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        Easy to deploy
      • 163
        Stable
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        Free
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        Fast
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        High-Performance
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        High Availability
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        Data Structures
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        Very Scalable
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        Replication
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        Great community
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        Pub/Sub
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        "NoSQL" key-value data store
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        Hashes
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        Sets
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        Sorted Sets
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        Lists
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        BSD licensed
      • 8
        NoSQL
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        Async replication
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        Integrates super easy with Sidekiq for Rails background
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        Bitmaps
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        Open Source
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        Keys with a limited time-to-live
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        Strings
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        Lua scripting
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        Awesomeness for Free!
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        Hyperloglogs
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        outstanding performance
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        Runs server side LUA
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        Networked
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        LRU eviction of keys
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        Written in ANSI C
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        Feature Rich
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        Transactions
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        Data structure server
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        Performance & ease of use
      • 1
        Existing Laravel Integration
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        Automatic failover
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        Easy to use
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        Object [key/value] size each 500 MB
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        Simple
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        Channels concept
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        Scalable
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        Temporarily kept on disk
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        Dont save data if no subscribers are found
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        Jk
      CONS OF REDIS
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        Cannot query objects directly
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        No WAL
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        No secondary indexes for non-numeric data types

      related Redis posts

      Robert Zuber

      We use MongoDB as our primary #datastore. Mongo's approach to replica sets enables some fantastic patterns for operations like maintenance, backups, and #ETL.

      As we pull #microservices from our #monolith, we are taking the opportunity to build them with their own datastores using PostgreSQL. We also use Redis to cache data we’d never store permanently, and to rate-limit our requests to partners’ APIs (like GitHub).

      When we’re dealing with large blobs of immutable data (logs, artifacts, and test results), we store them in Amazon S3. We handle any side-effects of S3’s eventual consistency model within our own code. This ensures that we deal with user requests correctly while writes are in process.

      See more

      I'm working as one of the engineering leads in RunaHR. As our platform is a Saas, we thought It'd be good to have an API (We chose Ruby and Rails for this) and a SPA (built with React and Redux ) connected. We started the SPA with Create React App since It's pretty easy to start.

      We use Jest as the testing framework and react-testing-library to test React components. In Rails we make tests using RSpec.

      Our main database is PostgreSQL, but we also use MongoDB to store some type of data. We started to use Redis  for cache and other time sensitive operations.

      We have a couple of extra projects: One is an Employee app built with React Native and the other is an internal back office dashboard built with Next.js for the client and Python in the backend side.

      Since we have different frontend apps we have found useful to have Bit to document visual components and utils in JavaScript.

      See more
      Hazelcast logo

      Hazelcast

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      Clustering and highly scalable data distribution platform for Java
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      PROS OF HAZELCAST
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        High Availibility
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        Distributed Locking
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        Distributed compute
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        Sharding
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        Load balancing
      • 3
        Map-reduce functionality
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        Publish-subscribe
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        Sql query support in cluster wide
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        Written in java. runs on jvm
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        Simple-to-use
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        Multiple client language support
      • 2
        Rest interface
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        Optimis locking for map
      • 1
        Easy to use
      • 1
        Performance
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        Super Fast
      • 1
        Admin Interface (Management Center)
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        Better Documentation
      CONS OF HAZELCAST
      • 3
        License needed for SSL

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      Aerospike logo

      Aerospike

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      Flash-optimized in-memory open source NoSQL database
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      PROS OF AEROSPIKE
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        Ram and/or ssd persistence
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        Easy clustering support
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        Easy setup
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        Acid
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        Scale
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        Petabyte Scale
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        Performance better than Redis
      CONS OF AEROSPIKE
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        SAP HANA logo

        SAP HANA

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        PROS OF SAP HANA
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          In-memory
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          Distributed
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          SQL
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          OLAP
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          OLTP
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          Performance
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          Realtime
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          Concurrent
        • 1
          JSON
        CONS OF SAP HANA
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          Hi. We are planning to develop web, desktop, and mobile app for procurement, logistics, and contracts. Procure to Pay and Source to pay, spend management, supplier management, catalog management. ( similar to SAP Ariba, gap.com, coupa.com, ivalua.com vroozi.com, procurify.com

          We got stuck when deciding which technology stack is good for the future. We look forward to your kind guidance that will help us.

          We want to integrate with multiple databases with seamless bidirectional integration. What APIs and middleware available are best to achieve this? SAP HANA, Oracle, MySQL, MongoDB...

          ASP.NET / Node.js / Laravel. ......?

          Please guide us

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          Apache Ignite logo

          Apache Ignite

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          An open-source distributed database, caching and processing platform
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          PROS OF APACHE IGNITE
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            Written in java. runs on jvm
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            Free
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            Load balancing
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            High Avaliability
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            Rest interface
          • 2
            Sql query support in cluster wide
          • 1
            Multiple client language support
          • 1
            Better Documentation
          • 1
            Distributed compute
          • 1
            Distributed Locking
          • 1
            Easy to use
          CONS OF APACHE IGNITE
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            MemSQL logo

            MemSQL

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            Database for real-time transactions and analytics.
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            PROS OF MEMSQL
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              Distributed
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              Realtime
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              JSON
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              Sql
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              Concurrent
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              Columnstore
            • 1
              Ultra fast
            • 1
              Scalable
            CONS OF MEMSQL
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