DBMS > AnzoGraph DB vs. Atos Standard Common Repository vs. Google BigQuery vs. SpaceTime vs. TinkerGraph

System Properties Comparison AnzoGraph DB vs. Atos Standard Common Repository vs. Google BigQuery vs. SpaceTime vs. TinkerGraph

Editorial information provided by DB-Engines

Name

This system has been discontinued and will be removed from the DB-Engines ranking.

Description

Scalable graph database built for online analytics and data harmonization with MPP scaling, high-performance analytical algorithms and reasoning, and virtualization

Highly scalable database system, designed for managing session and subscriber data in modern mobile communication networks

Large scale data warehouse service with append-only tables

SpaceTime is a spatio-temporal DBMS with a focus on performance.

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

Primary database model

Graph DBMS
RDF store

Document store
Key-value store

Relational DBMS

Spatial DBMS

Graph DBMS

Secondary database models

Relational DBMS

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

Score	0.23
Rank	#307	Overall
	#24	Graph DBMS
	#13	RDF stores

Score	60.38
Rank	#19	Overall
	#13	Relational DBMS

Score	0.00
Rank	#383	Overall
	#7	Spatial DBMS

Score	0.08
Rank	#348	Overall
	#35	Graph DBMS

Website

cambridgesemantics.com/anzograph

atos.net/en/convergence-creators/portfolio/standard-common-repository

cloud.google.com/bigquery

www.mireo.com/spacetime

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

Technical documentation

docs.cambridgesemantics.com/anzograph/userdoc/home.htm

cloud.google.com/bigquery/docs

Developer

Cambridge Semantics

Atos Convergence Creators

Google

Mireo

Initial release

2018

2016

2010

2020

2009

Current release

2.3, January 2021

1703

License

Commercial or Open Source

commercial

free trial version available

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

Java

C++

Java

Server operating systems

Linux

hosted

Linux

Data scheme

Schema-free and OWL/RDFS-schema support

Schema and schema-less with LDAP views

yes

schema-free

Typing

predefined data types such as float or date

optional

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.

yes

Secondary indexes

yes

SQL

Support of SQL

SPARQL and SPARQL* as primary query language. Cypher preview.

yes

A subset of ANSI SQL is implemented

APIs and other access methods

Apache Mule
gRPC
JDBC
Kafka
OData access for BI tools
OpenCypher
RESTful HTTP API
SPARQL

LDAP

RESTful HTTP/JSON API

RESTful HTTP API

TinkerPop 3

Supported programming languages

C++
Java
Python

All languages with LDAP bindings

.Net
Java
JavaScript
Objective-C
PHP
Python
Ruby

C#
C++
Python

Groovy
Java

Server-side scripts

Stored procedures

user defined functions and aggregates

user defined functions

in JavaScript

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Automatic sharding

Sharding

cell division

none

Fixed-grid hypercubes

none

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication in MPP-Cluster

yes

Real-time block device replication (DRBD)

none

MapReduce

Offers an API for user-defined Map/Reduce methods

Kerberos/HDFS data loading

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency in MPP-Cluster

Immediate Consistency or Eventual Consistency depending on configuration

Immediate Consistency

none

Foreign keys

Referential integrity

not needed in graphs

yes

Relationships in graphs

Transaction concepts

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

ACID

Atomic execution of specific operations

Since BigQuery is designed for querying data

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

Access rights for users and roles

LDAP bind authentication

Access privileges (owner, writer, reader) on dataset, table or view level

Google Cloud Identity & Access Management (IAM)

yes

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