DBMS > AnzoGraph DB vs. Atos Standard Common Repository vs. Google Cloud Datastore vs. H2GIS

System Properties Comparison AnzoGraph DB vs. Atos Standard Common Repository vs. Google Cloud Datastore vs. H2GIS

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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

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

Spatial extension of H2

Primary database model

Graph DBMS
RDF store

Document store
Key-value store

Document store

Spatial DBMS

Secondary database models

Relational DBMS

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

Score	0.22
Rank	#302	Overall
	#24	Graph DBMS
	#13	RDF stores

Score	4.13
Rank	#71	Overall
	#12	Document stores

Score	0.00
Rank	#385	Overall
	#7	Spatial DBMS

Website

cambridgesemantics.com/anzograph

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

cloud.google.com/datastore

www.h2gis.org

Technical documentation

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

cloud.google.com/datastore/docs

www.h2gis.org/docs/home

Developer

Cambridge Semantics

Atos Convergence Creators

Google

CNRS

Initial release

2018

2016

2008

2013

Current release

2.3, January 2021

1703

License

Commercial or Open Source

commercial

free trial version available

commercial

Open Source

LGPL 3.0

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

Server operating systems

Linux

hosted

Data scheme

Schema-free and OWL/RDFS-schema support

Schema and schema-less with LDAP views

schema-free

yes

Typing

predefined data types such as float or date

optional

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.

yes

Secondary indexes

yes

SQL

Support of SQL

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

SQL-like query language (GQL)

yes

APIs and other access methods

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

LDAP

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

Supported programming languages

C++
Java
Python

All languages with LDAP bindings

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

Java

Server-side scripts

Stored procedures

user defined functions and aggregates

using Google App Engine

yes

based on H2

Triggers

yes

Callbacks using the Google Apps Engine

yes

Partitioning methods

Methods for storing different data on different nodes

Automatic sharding

Sharding

cell division

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication in MPP-Cluster

yes

Multi-source replication using Paxos

yes

based on H2

MapReduce

Offers an API for user-defined Map/Reduce methods

Kerberos/HDFS data loading

yes

using Google Cloud Dataflow

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 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

not needed in graphs

yes

via ReferenceProperties or Ancestor paths

yes

Transaction concepts

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

ACID

Atomic execution of specific operations

ACID

Serializable Isolation within Transactions, Read Committed outside of Transactions

ACID

Concurrency

Support for concurrent manipulation of data

yes

yes, multi-version concurrency control (MVCC)

Durability

Support for making data persistent

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 and roles

LDAP bind authentication

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

yes

based on H2

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More resources

Recent citations in the news

AnzoGraph: A graph database for deep analytics
15 April 2019, InfoWorld

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AnzoGraph: A W3C Standards-Based Graph Database | by Jo Stichbury
8 February 2019, Towards Data Science

Cambridge Semantics Fits AnzoGraph DB with More Speed, Free Access
23 January 2020, Solutions Review

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