DBMS > Google Cloud Datastore vs. Graph Engine vs. TinkerGraph vs. Warp 10

System Properties Comparison Google Cloud Datastore vs. Graph Engine vs. TinkerGraph vs. Warp 10

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 lightweight, in-memory graph engine that serves as a reference implementation of the TinkerPop3 API

TimeSeries DBMS specialized on timestamped geo data based on LevelDB or HBase

Primary database model

Document store

Graph DBMS
Key-value store

Graph DBMS

Time Series DBMS

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

Score	4.13
Rank	#71	Overall
	#12	Document stores

Score	0.56
Rank	#241	Overall
	#21	Graph DBMS
	#34	Key-value stores

Score	0.08
Rank	#345	Overall
	#34	Graph DBMS

Score	0.06
Rank	#351	Overall
	#35	Time Series DBMS

Website

cloud.google.com/datastore

www.graphengine.io

tinkerpop.apache.org/docs/current/reference/#tinkergraph-gremlin

www.warp10.io

Technical documentation

cloud.google.com/datastore/docs

www.graphengine.io/docs/manual

www.warp10.io/content/02_Getting_started

Developer

Google

Microsoft

SenX

Initial release

2008

2010

2009

2015

License

Commercial or Open Source

commercial

Open Source

MIT License

Open Source

Apache 2.0

Open Source

Apache License 2.0

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

Java

Server operating systems

hosted

.NET

Linux
OS X
Windows

Data scheme

schema-free

yes

schema-free

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

TinkerPop 3

HTTP API
Jupyter
WebSocket

Supported programming languages

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

C#
C++
F#
Visual Basic

Groovy
Java

Server-side scripts

Stored procedures

using Google App Engine

yes

WarpScript

Triggers

Callbacks using the Google Apps Engine

Partitioning methods

Methods for storing different data on different nodes

Sharding

horizontal partitioning

none

Sharding

based on HBase

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication using Paxos

none

selectable replication factor

based on HBase

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.

none

Immediate Consistency

based on HBase

Foreign keys

Referential integrity

yes

via ReferenceProperties or Ancestor paths

yes

Relationships in graphs

Transaction concepts

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

ACID

Serializable Isolation within Transactions, Read Committed outside of Transactions

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

optional

yes

In-memory capabilities

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

yes

User concepts

Access control

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

Mandatory use of cryptographic tokens, containing fine-grained authorizations

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

Recent citations in the news

Google Cloud vs AWS: Which Cloud Computing Platform is Better?
11 September 2024, Cloudwards

Google Gets Rid of Fees To Transfer Data Out of Cloud Platform
12 January 2024, Spiceworks News and Insights

Best cloud storage of 2024
13 September 2024, TechRadar

Google App Engine
26 April 2024, TechTarget

17 Top Cloud Storage Companies to Know
9 April 2024, Built In

provided by Google News

Trinity
30 October 2010, Microsoft

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

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

The graph analytics landscape 2019
27 February 2019, Data Science Central

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

provided by Google News

Unit testing Apache TinkerPop transactions: From TinkerGraph to Amazon Neptune
3 June 2024, AWS Blog

Simple Deployment of a Graph Database: JanusGraph
12 October 2020, Towards Data Science

Introducing Gremlin query hints for Amazon Neptune
26 February 2019, AWS Blog

provided by Google News

Launched Just A Year Ago, Open-Source Scality S3 Server Gains Extraordinary Momentum As It Simplifies The Life Of Developers
28 June 2017, PR Newswire

provided by Google News

Share this page