DBMS > AnzoGraph DB vs. Atos Standard Common Repository vs. SpaceTime vs. Vertica vs. VoltDB

System Properties Comparison AnzoGraph DB vs. Atos Standard Common Repository vs. SpaceTime vs. Vertica vs. VoltDB

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

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

Cloud or off-cloud analytical database and query engine for structured and semi-structured streaming and batch data. Machine learning platform with built-in algorithms, data preparation capabilities, and model evaluation and management via SQL or Python.

Distributed In-Memory NewSQL RDBMS

Used for OLTP applications with a high frequency of relatively simple transactions, that can hold all their data in memory

Primary database model

Graph DBMS
RDF store

Document store
Key-value store

Spatial DBMS

Relational DBMS

Column oriented

Relational DBMS

Secondary database models

Relational DBMS

Spatial DBMS
Time Series 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	0.00
Rank	#383	Overall
	#7	Spatial DBMS

Score	10.68
Rank	#43	Overall
	#27	Relational DBMS

Score	1.44
Rank	#158	Overall
	#73	Relational DBMS

Website

cambridgesemantics.com/anzograph

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

www.mireo.com/spacetime

www.vertica.com

www.voltdb.com

Technical documentation

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

vertica.com/documentation

docs.voltdb.com

Developer

Cambridge Semantics

Atos Convergence Creators

Mireo

OpenText

previously Micro Focus and Hewlett Packard

VoltDB Inc.

Initial release

2018

2016

2020

2005

2010

Current release

2.3, January 2021

1703

12.0.3, January 2023

11.3, April 2022

License

Commercial or Open Source

commercial

free trial version available

commercial

Limited community edition free

Open Source

AGPL for Community Edition, commercial license for Enterprise, AWS, and Pro Editions

Cloud-based only

Only available as a cloud service

on-premises, all major clouds - Amazon AWS, Microsoft Azure, Google Cloud Platform and containers

DBaaS offerings (sponsored links)

Database as a Service

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

Implementation language

Java

C++

Java, C++

Server operating systems

Linux

Linux
OS X

for development

Data scheme

Schema-free and OWL/RDFS-schema support

Schema and schema-less with LDAP views

yes

Yes, but also semi-structure/unstructured data storage, and complex hierarchical data (like Parquet) stored and/or queried.

yes

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

No Indexes Required. Different internal optimization strategy, but same functionality included.

yes

SQL

Support of SQL

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

A subset of ANSI SQL is implemented

Full 1999 standard plus machine learning, time series and geospatial. Over 650 functions.

yes

only a subset of SQL 99

APIs and other access methods

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

LDAP

RESTful HTTP API

ADO.NET
JDBC
Kafka Connector
ODBC
RESTful HTTP API
Spark Connector
vSQL

character-based, interactive, front-end utility

Java API
JDBC
RESTful HTTP/JSON API

Supported programming languages

C++
Java
Python

All languages with LDAP bindings

C#
C++
Python

C#
C++
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
R

C#
C++
Erlang

not officially supported
Go
Java
JavaScript

Node.js
PHP
Python

Server-side scripts

Stored procedures

user defined functions and aggregates

yes, PostgreSQL PL/pgSQL, with minor differences

Java

Triggers

yes

yes, called Custom Alerts

Partitioning methods

Methods for storing different data on different nodes

Automatic sharding

Sharding

cell division

Fixed-grid hypercubes

horizontal partitioning, hierarchical partitioning

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication in MPP-Cluster

yes

Real-time block device replication (DRBD)

Multi-source replication

One, or more copies of data replicated across nodes, or object-store used for repository.

Multi-source replication
Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

Kerberos/HDFS data loading

Bi-directional Spark integration

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

Foreign keys

Referential integrity

not needed in graphs

yes

FOREIGN KEY constraints are not supported

Transaction concepts

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

ACID

Atomic execution of specific operations

ACID

Transactions are executed single-threaded within stored procedures

Concurrency

Support for concurrent manipulation of data

yes

Data access is serialized by the server

Durability

Support for making data persistent

yes

Snapshots and command logging

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

yes

fine grained access rights according to SQL-standard; supports Kerberos, LDAP, Ident and hash

Users and roles with access to stored procedures

More information provided by the system vendor

Specific characteristics

Deploy-anywhere database for large-scale analytical deployments. Deploy off-cloud,...
» more

Competitive advantages

Fast, scalable, and capable of high concurrency. Separation of compute/storage leverages...
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Typical application scenarios

Communication and network analytics, Embedded analytics, Fraud monitoring and Risk...
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Key customers

Abiba Systems, Adform, adMarketplace, AmeriPride, Anritsu, AOL, Avito, Auckland Transport,...
» more

Licensing and pricing models

Cost-based models and subscription-based models are both available. One license is...
» more

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and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.

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