What is Azure Redis Cache and what are its top alternatives?
Top Alternatives to Azure Redis Cache
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. ...
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 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. ...
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 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. ...
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. ...
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 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
- Backed by amazon25
related Amazon ElastiCache posts
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.
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.
- Low Latency1
related Azure CDN posts
- Super fast535
- Ease of use511
- In-memory cache442
- Advanced key-value cache321
- Open source190
- Easy to deploy179
- High Availability39
- Data Structures34
- Very Scalable32
- Great community20
- "NoSQL" key-value data store17
- Sorted Sets10
- BSD licensed8
- Async replication7
- Integrates super easy with Sidekiq for Rails background7
- Open Source6
- Keys with a limited time-to-live6
- Lua scripting5
- Awesomeness for Free!4
- outstanding performance3
- Runs server side LUA3
- LRU eviction of keys3
- Written in ANSI C3
- Feature Rich3
- Data structure server2
- Performance & ease of use2
- Existing Laravel Integration1
- Automatic failover1
- Easy to use1
- Object [key/value] size each 500 MB1
- Channels concept1
- Temporarily kept on disk1
- Dont save data if no subscribers are found1
- Cannot query objects directly12
- No WAL1
- No secondary indexes for non-numeric data types1
related Redis posts
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.
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.
- High Availibility9
- Distributed Locking6
- Distributed compute5
- Load balancing4
- Map-reduce functionality3
- Sql query support in cluster wide3
- Written in java. runs on jvm2
- Multiple client language support2
- Rest interface2
- Optimis locking for map2
- Easy to use1
- Super Fast1
- Admin Interface (Management Center)1
- Better Documentation1
- License needed for SSL3
related Hazelcast posts
- Ram and/or ssd persistence10
- Easy clustering support9
- Easy setup4
- Petabyte Scale1
- Performance better than Redis1
related Aerospike posts
related SAP HANA posts
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
- Written in java. runs on jvm3
- Load balancing2
- High Avaliability2
- Rest interface2
- Sql query support in cluster wide2
- Multiple client language support1
- Better Documentation1
- Distributed compute1
- Distributed Locking1
- Easy to use1