DBMS > DataFS vs. Google Cloud Datastore vs. Riak KV vs. TigerGraph vs. TinkerGraph

System Properties Comparison DataFS vs. Google Cloud Datastore vs. Riak KV vs. TigerGraph vs. TinkerGraph

Editorial information provided by DB-Engines

Name

Description

All data is stored inside objects which are linked by so-called link attributes. Objects consist of classes which can be extended and de-extended at runtime. Graphs can be defined with a struct.

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

Distributed, fault tolerant key-value store

A complete, distributed, parallel graph computing platform supporting web-scale data analytics in real-time

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

Primary database model

Object oriented DBMS

Document store

Key-value store

with links between data sets and object tags for the creation of secondary indexes

Graph DBMS

Secondary database models

Graph DBMS

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

Score	0.09
Rank	#360	Overall
	#17	Object oriented DBMS

Score	4.36
Rank	#72	Overall
	#12	Document stores

Score	4.01
Rank	#79	Overall
	#9	Key-value stores

Score	1.80
Rank	#138	Overall
	#13	Graph DBMS

Score	0.13
Rank	#345	Overall
	#35	Graph DBMS

Website

newdatabase.com

cloud.google.com/datastore

www.tigergraph.com

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

Technical documentation

dev.mobiland.com/Overview.xsp

cloud.google.com/datastore/docs

www.tiot.jp/riak-docs/riak/kv/latest

docs.tigergraph.com

Developer

Mobiland AG

Google

OpenSource, formerly Basho Technologies

Initial release

2018

2008

2009

2017

2009

Current release

1.1.263, October 2022

3.2.0, December 2022

License

Commercial or Open Source

commercial

Open Source

Apache version 2, commercial enterprise edition

commercial

Open Source

Apache 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

Erlang

C++

Java

Server operating systems

Windows

hosted

Linux
OS X

Linux

Data scheme

Classes, Structs, and Lists are written in proprietary DataTypeDefinitionLanguage (.dtdl) and Objects consisting of those are written in proprietary DataAccessDefinitionLanguage (.dadl)

schema-free

yes

schema-free

Typing

predefined data types such as float or date

yes

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

restricted

SQL

Support of SQL

SQL-like query language (GQL)

SQL-like query language (GSQL)

APIs and other access methods

.NET Client API
Proprietary client DLL
WinRT client

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

HTTP API
Native Erlang Interface

GSQL (TigerGraph Query Language)
Kafka
RESTful HTTP/JSON API

TinkerPop 3

Supported programming languages

.Net
C
C#
C++
VB.Net

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

unofficial client library
C#
C++

unofficial client library
Clojure

unofficial client library
Dart

unofficial client library
Erlang
Go

unofficial client library
Groovy

unofficial client library
Haskell

unofficial client library
Java
JavaScript

unofficial client library
Lisp

unofficial client library
Perl

unofficial client library
PHP
Python
Ruby
Scala

unofficial client library
Smalltalk

unofficial client library

C++
Java

Groovy
Java

Server-side scripts

Stored procedures

using Google App Engine

Erlang

yes

Triggers

no, except callback-events from server when changes happened

Callbacks using the Google Apps Engine

yes

pre-commit hooks and post-commit hooks

Partitioning methods

Methods for storing different data on different nodes

Proprietary Sharding system

Sharding

no "single point of failure"

none

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication using Paxos

selectable replication factor

none

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

using Google Cloud Dataflow

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

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.

Eventual Consistency

none

Foreign keys

Referential integrity

yes

via ReferenceProperties or Ancestor paths

links between data sets can be stored

yes

Relationships in graphs

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

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

optional

In-memory capabilities

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

yes

User concepts

Access control

Windows-Profile

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

yes, using Riak Security

Role-based access control

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