Google Cloud Datastore vs Orchestrate: 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, Orchestrate is detailed as "Database as a Service. Add Search, Time-Ordered Events, Geospatial or Graph Queries Fast with a REST API". Orchestrate is a managed database service that delivers a single access point to full-text search, time-ordered events, geospatial and graph queries through a REST API. It allows developers to build complete apps or add features to existing ones fast, without the operational burden of deploying and managing multiple databases themselves.
Google Cloud Datastore and Orchestrate can be categorized as "NoSQL Database as a Service" tools.
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, Orchestrate provides the following key features:
- Time-series Events
What is Google Cloud Datastore?
What is Orchestrate?
Want advice about which of these to choose?Ask the StackShare community!
Why do developers choose Orchestrate?
What are the cons of using Google Cloud Datastore?
What are the cons of using Orchestrate?
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What tools integrate with Google Cloud Datastore?
What tools integrate with Orchestrate?
When creating proofs of concept or small personal projects that are hosted primarily in GCP, with non-relational data models, this is the NoSQL managed database I usually pair them with.
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.