Google Cloud Datastore vs Redis Cloud: What are the differences?
What is Google Cloud Datastore? 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.
What is Redis Cloud? Enterprise-Class Redis for Developers. Redis Cloud is a fully-managed service for running your Redis dataset. It overcomes Redis’ scalability limitation by supporting all Redis commands at any dataset size. Your dataset is constantly replicated, so if a node fails, an auto-switchover mechanism guarantees data is served without interruption.
Google Cloud Datastore can be classified as a tool in the "NoSQL Database as a Service" category, while Redis Cloud is grouped under "Redis Hosting".
Some of the features offered by Google Cloud Datastore are:
- Schemaless access, with SQL-like querying
- Managed database
- Autoscale with your users
On the other hand, Redis Cloud provides the following key features:
- Infinite scalability, all commands supported
- Auto-failover with no ops
- Highest performance, even for small datasets
"High scalability" is the top reason why over 4 developers like Google Cloud Datastore, while over 7 developers mention "Heroku Addon" as the leading cause for choosing Redis Cloud.
Teleport, Policygenius, and Giftstarter are some of the popular companies that use Google Cloud Datastore, whereas Redis Cloud is used by Accenture, Luckycycle, and Ztory. Google Cloud Datastore has a broader approval, being mentioned in 46 company stacks & 16 developers stacks; compared to Redis Cloud, which is listed in 20 company stacks and 9 developer stacks.
What is Google Cloud Datastore?
What is Redis Cloud?
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What are the cons of using Google Cloud Datastore?
What are the cons of using Redis Cloud?
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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.
worked with a client that used datastore as their backend database. helped plan out their schema and architecture. loved the speed and simplicity.