Amazon ElastiCache vs Google Cloud SQL

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Amazon ElastiCache

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Google Cloud SQL

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Amazon ElastiCache vs Google Cloud SQL: What are the differences?

Developers describe Amazon ElastiCache as "Deploy, operate, and scale an in-memory cache in the cloud". 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. On the other hand, Google Cloud SQL is detailed as "Store and manage data using a fully-managed, relational MySQL database". MySQL databases deployed in the cloud without a fuss. Google Cloud Platform provides you with powerful databases that run fast, don’t run out of space and give your application the redundant, reliable storage it needs.

Amazon ElastiCache belongs to "Managed Memcache" category of the tech stack, while Google Cloud SQL can be primarily classified under "SQL Database as a Service".

Some of the features offered by Amazon ElastiCache are:

  • Support for two engines: Memcached and Redis
  • Ease of management via the AWS Management Console. With a few clicks you can configure and launch instances for the engine you wish to use.
  • Compatibility with the specific engine protocol. This means most of the client libraries will work with the respective engines they were built for - no additional changes or tweaking required.

On the other hand, Google Cloud SQL provides the following key features:

  • Familiar Infrastructure
  • Flexible Charging
  • Security, Availability, Durability

"Redis" is the primary reason why developers consider Amazon ElastiCache over the competitors, whereas "Fully managed" was stated as the key factor in picking Google Cloud SQL.

Instacart, SendGrid, and Sellsuki are some of the popular companies that use Amazon ElastiCache, whereas Google Cloud SQL is used by Implisit, Policygenius, and OTOBANK. Amazon ElastiCache has a broader approval, being mentioned in 342 company stacks & 79 developers stacks; compared to Google Cloud SQL, which is listed in 71 company stacks and 28 developer stacks.

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Pros of Amazon ElastiCache
Pros of Google Cloud SQL
  • 58
    Redis
  • 32
    High-performance
  • 26
    Backed by amazon
  • 21
    Memcached
  • 14
    Elastic
  • 13
    Fully managed
  • 10
    Backed by Google
  • 10
    SQL
  • 4
    Flexible
  • 3
    Encryption at rest and transit
  • 3
    Automatic Software Patching
  • 3
    Replication across multiple zone by default

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What is 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.

What is Google Cloud SQL?

Run the same relational databases you know with their rich extension collections, configuration flags and developer ecosystem, but without the hassle of self management.

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What companies use Amazon ElastiCache?
What companies use Google Cloud SQL?
See which teams inside your own company are using Amazon ElastiCache or Google Cloud SQL.
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What tools integrate with Amazon ElastiCache?
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What are some alternatives to Amazon ElastiCache and Google Cloud SQL?
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.
Elasticsearch
Elasticsearch is a distributed, RESTful search and analytics engine capable of storing data and searching it in near real time. Elasticsearch, Kibana, Beats and Logstash are the Elastic Stack (sometimes called the ELK Stack).
Memcached
Memcached is an in-memory key-value store for small chunks of arbitrary data (strings, objects) from results of database calls, API calls, or page rendering.
Azure Redis Cache
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.
Amazon DynamoDB
With it , you can offload the administrative burden of operating and scaling a highly available distributed database cluster, while paying a low price for only what you use.
See all alternatives