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Google Cloud Datastore
Google Cloud Datastore

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Redis
Redis

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Google Cloud Datastore vs Redis: What are the differences?

Developers describe Google Cloud Datastore as "A Fully Managed NoSQL Data Storage Service". Use a managed, NoSQL, schemaless database for storing non-relational data. Cloud Datastore automatically scales as you need it and supports transactions as well as robust, SQL-like queries. On the other hand, Redis is detailed as "An in-memory database that persists on disk". 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.

Google Cloud Datastore can be classified as a tool in the "NoSQL Database as a Service" category, while Redis is grouped under "In-Memory Databases".

"High scalability" is the primary reason why developers consider Google Cloud Datastore over the competitors, whereas "Performance" was stated as the key factor in picking Redis.

Redis is an open source tool with 37.1K GitHub stars and 14.3K GitHub forks. Here's a link to Redis's open source repository on GitHub.

According to the StackShare community, Redis has a broader approval, being mentioned in 3239 company stacks & 1732 developers stacks; compared to Google Cloud Datastore, which is listed in 45 company stacks and 16 developer stacks.

- No public GitHub repository available -

What is Google Cloud Datastore?

Use a managed, NoSQL, schemaless database for storing non-relational data. Cloud Datastore automatically scales as you need it and supports transactions as well as robust, SQL-like queries.

What is 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.
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Why do developers choose Google Cloud Datastore?
Why do developers choose Redis?

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      What are some alternatives to Google Cloud Datastore and Redis?
      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.
      MongoDB
      MongoDB stores data in JSON-like documents that can vary in structure, offering a dynamic, flexible schema. MongoDB was also designed for high availability and scalability, with built-in replication and auto-sharding.
      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).
      Cassandra
      Partitioning means that Cassandra can distribute your data across multiple machines in an application-transparent matter. Cassandra will automatically repartition as machines are added and removed from the cluster. Row store means that like relational databases, Cassandra organizes data by rows and columns. The Cassandra Query Language (CQL) is a close relative of SQL.
      Cloud Firestore
      Cloud Firestore is a NoSQL document database that lets you easily store, sync, and query data for your mobile and web apps - at global scale.
      See all alternatives
      Decisions about Google Cloud Datastore and Redis
      Django
      Django
      Redis
      Redis

      I use Redis because, based on the case studies I have reviewed, it appears to be the most performant cache database for my Django projects. The ease of configuration and deployment is also a big plus.

      Using both higher level view caching as well as low-level QuerySet caching with Redis has allowed me to improve HTTP request times by an order of magnitude.

      See more
      Interest over time
      Reviews of Google Cloud Datastore and Redis
      Review ofRedisRedis

      Redis is a good caching tool for a cluster, but our application had performance issues while using Aws Elasticache Redis since some page had 3000 cache hits per a page load and Redis just couldn't quickly process them all in once + latency and object deseialization time - page load took 8-9 seconds. We create a custom hybrid caching based on Redis and EhCache which worked great for our goals. Check it out on github, it's called HybriCache - https://github.com/batir-akhmerov/hybricache.

      How developers use Google Cloud Datastore and Redis
      Avatar of Cloudcraft
      Cloudcraft uses RedisRedis

      Redis is used for storing all ephemeral (that's data you don't necessarily want to store permanently) user data, such as mapping of session IDs (stored in cookies) to current session variables at Cloudcraft.co. The many datastructures supported by Redis also makes it an excellent caching and realtime statistics layer. It doesn't hurt that the author, Antirez, is the nicest guy ever! These days, I would be really hard pressed to find any situation where I would pick something like Memcached over Redis.

      Avatar of Trello
      Trello uses RedisRedis

      Trello uses Redis for ephemeral data that needs to be shared between server processes but not persisted to disk. Things like the activity level of a session or a temporary OpenID key are stored in Redis, and the application is built to recover gracefully if any of these (or all of them) are lost. We run with allkeys-lru enabled and about five times as much space as its actual working set needs, so Redis automatically discards data that hasn鈥檛 been accessed lately, and reconstructs it when necessary.

      Avatar of Stack Exchange
      Stack Exchange uses RedisRedis

      The UI has message inbox that is sent a message when you get a new badge, receive a message, significant event, etc. Done using WebSockets and is powered by redis. Redis has 2 slaves, SQL has 2 replicas, tag engine has 3 nodes, elastic has 3 nodes - any other service has high availability as well (and exists in both data centers).

      Avatar of Brandon Adams
      Brandon Adams uses RedisRedis

      Redis makes certain operations very easy. When I need a high-availability store, I typically look elsewhere, but for rapid development with the ability to land on your feet in prod, Redis is great. The available data types make it easy to build non-trivial indexes that would require complex queries in postgres.

      Avatar of Kent Steiner
      Kent Steiner uses RedisRedis

      I use Redis for cacheing, data storage, mining and augmentation, proprietary distributed event system for disparate apps and services to talk to each other, and more. Redis has some very useful native data types for tracking, slicing and dicing information.

      Avatar of CommentBox.io
      CommentBox.io uses Google Cloud DatastoreGoogle Cloud Datastore

      This is our primary database, though most of our actual data is stored in static storage. This database houses the metadata necessary for indexing and finding static data.

      Avatar of papaver
      papaver uses Google Cloud DatastoreGoogle Cloud Datastore

      worked with a client that used datastore as their backend database. helped plan out their schema and architecture. loved the speed and simplicity.

      Avatar of Giftstarter
      Giftstarter uses Google Cloud DatastoreGoogle Cloud Datastore

      We store our data in this store.

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