Elasticsearch vs Google Cloud Datastore: What are the differences?
Elasticsearch: Open Source, Distributed, RESTful Search Engine. 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); 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.
Elasticsearch and Google Cloud Datastore are primarily classified as "Search as a Service" and "NoSQL Database as a Service" tools respectively.
Some of the features offered by Elasticsearch are:
- Distributed and Highly Available Search Engine.
- Multi Tenant with Multi Types.
- Various set of APIs including RESTful
On the other hand, Google Cloud Datastore provides the following key features:
- Schemaless access, with SQL-like querying
- Managed database
- Autoscale with your users
"Powerful api" is the primary reason why developers consider Elasticsearch over the competitors, whereas "High scalability" was stated as the key factor in picking Google Cloud Datastore.
Elasticsearch is an open source tool with 42.4K GitHub stars and 14.2K GitHub forks. Here's a link to Elasticsearch's open source repository on GitHub.
Uber Technologies, Instacart, and Slack are some of the popular companies that use Elasticsearch, whereas Google Cloud Datastore is used by Teleport, Policygenius, and Giftstarter. Elasticsearch has a broader approval, being mentioned in 2003 company stacks & 979 developers stacks; compared to Google Cloud Datastore, which is listed in 46 company stacks and 16 developer stacks.
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