DBMS > Google Cloud Datastore vs. Graph Engine vs. Realm

System Properties Comparison Google Cloud Datastore vs. Graph Engine vs. Realm

Please select another system to include it in the comparison.

Editorial information provided by DB-Engines

Name

Description

Automatically scaling NoSQL Database as a Service (DBaaS) on the Google Cloud Platform

A distributed in-memory data processing engine, underpinned by a strongly-typed RAM store and a general distributed computation engine

A DBMS built for use on mobile devices that’s a fast, easy to use alternative to SQLite and Core Data

Primary database model

Document store

Graph DBMS
Key-value store

Document store

DB-Engines Ranking measures the popularity of database management systems
Trend Chart

Score	4.49
Rank	#79	Overall
	#12	Document stores

Score	0.62
Rank	#240	Overall
	#21	Graph DBMS
	#35	Key-value stores

Score	7.71
Rank	#52	Overall
	#9	Document stores

Website

cloud.google.com/datastore

www.graphengine.io

realm.io

Technical documentation

cloud.google.com/datastore/docs

www.graphengine.io/docs/manual

realm.io/docs

Developer

Google

Microsoft

Realm, acquired by MongoDB in May 2019

Initial release

2008

2010

2014

License

Commercial or Open Source

commercial

Open Source

MIT License

Open Source

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

Providers of DBaaS offerings, please contact us to be listed.

Implementation language

.NET and C

Server operating systems

hosted

.NET

Android
Backend: server-less
iOS
Windows

Data scheme

schema-free

yes

Typing

predefined data types such as float or date

yes, details here

yes

XML support

Some form of processing data in XML format, e.g. support for XML data structures, and/or support for XPath, XQuery or XSLT.

Secondary indexes

yes

SQL

Support of SQL

SQL-like query language (GQL)

APIs and other access methods

gRPC (using protocol buffers) API
RESTful HTTP/JSON API

RESTful HTTP API

Supported programming languages

.Net
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby

C#
C++
F#
Visual Basic

.Net
Java

with Android only
Objective-C
React Native
Swift

Server-side scripts

Stored procedures

using Google App Engine

yes

runs within the applications so server-side scripts are unnecessary

Triggers

Callbacks using the Google Apps Engine

yes

Change Listeners

Partitioning methods

Methods for storing different data on different nodes

Sharding

horizontal partitioning

none

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication using Paxos

none

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

using Google Cloud Dataflow

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency or Eventual Consistency depending on type of query and configuration

Strong Consistency is default for entity lookups and queries within an Entity Group (but can instead be made eventually consistent). Other queries are always eventual consistent.

Immediate Consistency

Foreign keys

Referential integrity

yes

via ReferenceProperties or Ancestor paths

Transaction concepts

Support to ensure data integrity after non-atomic manipulations of data

ACID

Serializable Isolation within Transactions, Read Committed outside of Transactions

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

optional: either by committing a write-ahead log (WAL) to the local persistent storage or by dumping the memory to a persistent storage

yes

In-memory capabilities

Is there an option to define some or all structures to be held in-memory only.

yes

In-Memory realm

User concepts

Access control

Access rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)

yes

More information provided by the system vendor

We invite representatives of system vendors to contact us for updating and extending the system information,
and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.

Related products and services

We invite representatives of vendors of related products to contact us for presenting information about their offerings here.

More resources

DB-Engines blog posts

MySQL, PostgreSQL and Redis are the winners of the March ranking
2 March 2016, Paul Andlinger

show all

Recent citations in the news

Google Cloud is NOT magicking away data egress fees
12 January 2024, The Stack

SAP adds vector datastore to HANA Cloud database
2 November 2023, Techzine Europe

NetApp Cloud Volumes Service datastore support for Google Cloud VMware Engine
7 February 2023, NetApp

Your Memories. Their Cloud.
1 January 2023, The New York Times

All of Google’s cloud database services are now out of beta
16 August 2016, TechCrunch

provided by Google News

Trinity
2 June 2023, Microsoft

Open source Microsoft Graph Engine takes on Neo4j
13 February 2017, InfoWorld

IBM releases Graph, a service that can outperform SQL databases
27 July 2016, GeekWire

How Google and Microsoft taught search to "understand" the Web
6 June 2012, Ars Technica

Aerospike Is Now a Graph Database, Too
21 June 2023, Datanami

provided by Google News

MongoDB aims to unify developer experience with launch of MongoDB Cloud
9 June 2020, diginomica

Kotlin Programming Language Will Surpass Java On Android Next Year
15 October 2017, Fossbytes

Is Swift the Future of Server-side Development?
12 September 2017, Solutions Review

A Quick Look at Open Source Databases for Mobile App Development
29 April 2018, Open Source For You

provided by Google News

Share this page