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Azure Redis Cache

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Azure Redis Cache vs Redis: What are the differences?

Azure Redis Cache and Redis are both in-memory data stores. Let's explore the key differences between the two.

  1. Scalability: One major difference between Azure Redis Cache and Redis is the scalability. Azure Redis Cache provides the ability to scale up and down based on demand without any downtime. It offers different pricing tiers with varying sizes of cache instances. On the other hand, Redis is a self-managed solution, and the scalability depends on the infrastructure it is deployed on. Users need to manually manage and scale Redis clusters to meet their requirements.

  2. Managed Service: Azure Redis Cache is a managed service provided by Microsoft. This means that Microsoft takes care of the infrastructure, updates, backups, and monitoring of the cache. Users can focus on using the cache without worrying about the underlying infrastructure. Redis, on the other hand, is an open-source solution that needs to be managed by the users themselves. Users are responsible for setting up the infrastructure, managing updates, backups, and monitoring of the Redis instances.

  3. Integration with Azure services: Azure Redis Cache seamlessly integrates with various Azure services like Azure Functions, Azure App Service, and Azure Logic Apps. This allows developers to easily incorporate caching in their applications and leverage other Azure services for building scalable and performant applications. Redis, being a standalone solution, does not have such direct integrations with Azure services and requires custom integration efforts.

  4. Security and Compliance: Azure Redis Cache provides built-in security features like SSL/TLS encryption, authentication, and access control policies. It also complies with various certifications and regulations like ISO, SOC, and HIPAA. Redis, being a self-managed solution, relies on the user's implementation for security measures. Users are responsible for implementing encryption, access control, and compliance measures as per their requirements.

  5. Monitoring and Metrics: Azure Redis Cache provides comprehensive monitoring and metrics through Azure Monitor. Users can easily monitor cache performance, get insights, and set up alerts. Redis, on the other hand, requires users to set up their own monitoring and metrics solutions. Users need to configure tools like Prometheus or Grafana to monitor and gather metrics from Redis instances.

  6. Pricing Model: Azure Redis Cache offers a pay-as-you-go pricing model based on cache size and performance tier. Users can choose the appropriate pricing tier based on their requirements and only pay for the resources they consume. Redis, being an open-source solution, does not have any specific pricing. Users can deploy Redis on their preferred infrastructure and need to manage the costs associated with the infrastructure, maintenance, and support.

In summary, Azure Redis Cache is a managed service provided by Microsoft, offering scalability, integration with Azure services, built-in security and compliance features, monitoring and metrics through Azure Monitor, and a pay-as-you-go pricing model. Redis, on the other hand, is a self-managed solution with users needing to manage scalability, infrastructure, security, monitoring, and pricing on their own.

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Pros of Azure Redis Cache
Pros of Redis
  • 4
    Cache-cluster
  • 3
    Redis
  • 886
    Performance
  • 542
    Super fast
  • 513
    Ease of use
  • 444
    In-memory cache
  • 324
    Advanced key-value cache
  • 194
    Open source
  • 182
    Easy to deploy
  • 164
    Stable
  • 155
    Free
  • 121
    Fast
  • 42
    High-Performance
  • 40
    High Availability
  • 35
    Data Structures
  • 32
    Very Scalable
  • 24
    Replication
  • 22
    Great community
  • 22
    Pub/Sub
  • 19
    "NoSQL" key-value data store
  • 16
    Hashes
  • 13
    Sets
  • 11
    Sorted Sets
  • 10
    NoSQL
  • 10
    Lists
  • 9
    Async replication
  • 9
    BSD licensed
  • 8
    Bitmaps
  • 8
    Integrates super easy with Sidekiq for Rails background
  • 7
    Keys with a limited time-to-live
  • 7
    Open Source
  • 6
    Lua scripting
  • 6
    Strings
  • 5
    Awesomeness for Free
  • 5
    Hyperloglogs
  • 4
    Transactions
  • 4
    Outstanding performance
  • 4
    Runs server side LUA
  • 4
    LRU eviction of keys
  • 4
    Feature Rich
  • 4
    Written in ANSI C
  • 4
    Networked
  • 3
    Data structure server
  • 3
    Performance & ease of use
  • 2
    Dont save data if no subscribers are found
  • 2
    Automatic failover
  • 2
    Easy to use
  • 2
    Temporarily kept on disk
  • 2
    Scalable
  • 2
    Existing Laravel Integration
  • 2
    Channels concept
  • 2
    Object [key/value] size each 500 MB
  • 2
    Simple

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Cons of Azure Redis Cache
Cons of Redis
    Be the first to leave a con
    • 15
      Cannot query objects directly
    • 3
      No secondary indexes for non-numeric data types
    • 1
      No WAL

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    What companies use Azure Redis Cache?
    What companies use Redis?
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    What tools integrate with Azure Redis Cache?
    What tools integrate with Redis?

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    What are some alternatives to Azure Redis Cache and Redis?
    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
    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.
    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 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
    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.
    See all alternatives