Name: Google Cloud Datastore
Rating: 7.8 (36 reviews)
Author: Google

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Google Cloud Datastore is a NoSQL "schemaless" database as a service, supporting diverse data types. The database is managed; Google manages sharding and replication and prices according to storage and activity.

MongoDB is an open source document-oriented database system. It is part of the NoSQL family of database systems. Instead of storing data in tables as is done in a "classical" relational database, MongoDB stores structured data as JSON-like documents with dynamic schemas (MongoDB calls the format BSON), making the integration of data in certain types of applications easier and faster.

Shared

Serverless

Dedicated

Amazon DynamoDB is a cloud-native, NoSQL, serverless database service.

On-Demand - Write Operation

On-Demand Read Operation

On-Demand Data Stored

On-Demand Point-in-Time Recovery

On-Demand Snapshot

On-Demand Restoring a Backup

On-Demand Global Tables

On-Demand Streams

On-Demand Data Requests Outside AWS Regions

Provisioned - Write Operation

Provisioned - Read Operation

Provisioned - Data Stored

Provisioned - Point-in-Time Recovery

Provisioned - Snapshot

Provisioned - Restoring a Backup

Provisioned - Global Tables

Provisioned - Streams

Provisioned - Data Requests Outside AWS Regions

Google Cloud Datastore

Some cloud platforms offer options for using a database as a service, without physically launching a virtual machine instance for the database. In this configuration, application owners do not have to install and maintain the database on their own. Instead, the database service provider takes responsibility for installing and maintaining the database, and application owners pay according to their usage. For example, Amazon Web Services provides three database services as part of its cloud offering, SimpleDB, a NoSQL key-value store, Amazon Relational Database Service, an SQL-based database service with a MySQL interface, and DynamoDB.

NoSQL Databases

Likelihood to Recommend

Likelihood to Renew

Performance

Availability

Concurrency

Scalability

Data model flexibility

Deployment model flexibility

Google’s mission is to organize the world‘s information and make it universally accessible and useful. 

Since its founding in 1998, Google has grown by leaps and bounds. From offering search in a single language the company now offers dozens of products and services—including various forms of advertising and web applications for all kinds of tasks—in scores of languages. And starting from two computer science students in a university dorm room, the company now has thousands of employees and offices around the world.

NoSQL databases are designed to be used across large distrusted systems. They are notably much more scalable and much faster and handling very large data loads than traditional relational databases.

How fast the database performs under data load

Availability is the probability that the NoSQL database will be available to preform its function when called upon.

Concurrency is the ability for multiple processes to access or change shared data simultaneously. The greater the number of concurrent user processes that can execute without blocking each other, the greater the concurrency of the database system.

Security features include authentication against external security mechanisms liker LDAP, Windows Active Directory, and authorization or privilege management. Some NoSQL databases also support encryption.

NoSQL databases are inherently more stable than relational databases and have built-in support for replication and partitioning of data to support scalability.

NoSQL databases do not rely on rely on tables, columns, rows, or schemas to organize and retrieve data,  but use use more flexible data models to accommodate the large volume and variety of data being generated by modern applications.

Can be deployed on-premise or in the cloud.

Google Cloud Datastore 2020-02-12 16:33:03

Atlassian Confluence

Atlassian Jira

Google App Engine

MariaDB Platform

MySQL

Atlassian Bitbucket

Redmine

GitHub

CentOS Linux

Google Cloud Datastore 2019-03-07 13:32:06

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Google Cloud Datastore is being used by some departments in our company for testing and proof of concept purpose. We were looking for a product in Google Cloud to be used as our NoSQL database. Google Cloud Datastore came into our sight with its high availability and serverless nature which makes it a perfect candidate for our needs.

It is hosted in GCP, our primary cloud provider.
It integrates with all the services we use in GCP.

It is hosted on GCP, which makes it harder if your company have multi-cloud strategy.
When you want to migrate to other cloud providers, there can be a caveat.

It solves our NoSQL database problem.
It it highly scalable and available to meets our needs.

Amazon DynamoDB, MongoDB Atlas, Google Cloud Spanner, Google Cloud SQL

We're using Google Cloud Datastore as part of an application deployed to Google AppEngine, which is all running entirely in the Google Cloud Platform. Since our application is using Google AppEngine, we wanted to use a datastore which was simple to set up and didn't require managing servers or deployments/configurations for. Because Google Cloud Datastore is part of the Google Cloud Platform, it really simplified billing and management.

Automatically handles shards and replication.
Schema-less & NoSQL.
Fully managed.

Part of the Google Cloud Platform walled garden.
Pay for read/writes to the datastore, in addition to storage.
Not many libraries exist.

Simple billing part of Google Cloud Platform
No time spent configuring and maintaining Google Cloud Datastore.
Very good uptime for our applications.

Google App Engine, CentOS, MySQL, MariaDB, JIRA Software, Atlassian Confluence, Redmine, GitHub, Bitbucket

Google Cloud Datastore

Overview

What is Google Cloud Datastore?