DBMS > Atos Standard Common Repository vs. atoti vs. TigerGraph vs. VoltDB

System Properties Comparison Atos Standard Common Repository vs. atoti vs. TigerGraph vs. VoltDB

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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

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

An in-memory DBMS combining transactional and analytical processing to handle the aggregation of ever-changing data.

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

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

Document store
Key-value store

Object oriented DBMS

Graph DBMS

Relational DBMS

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

Score	0.61
Rank	#243	Overall
	#10	Object oriented DBMS

Score	1.80
Rank	#138	Overall
	#13	Graph DBMS

Score	1.47
Rank	#157	Overall
	#73	Relational DBMS

Website

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

atoti.io

www.tigergraph.com

www.voltdb.com

Technical documentation

docs.atoti.io

docs.tigergraph.com

docs.voltdb.com

Developer

Atos Convergence Creators

ActiveViam

VoltDB Inc.

Initial release

2016

2017

2010

Current release

1703

11.3, April 2022

License

Commercial or Open Source

commercial

free versions available

commercial

Open Source

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

Cloud-based only

Only available as a cloud service

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 and schema-less with LDAP views

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

SQL

Support of SQL

Multidimensional Expressions (MDX)

SQL-like query language (GSQL)

yes

only a subset of SQL 99

APIs and other access methods

LDAP

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

Java API
JDBC
RESTful HTTP/JSON API

Supported programming languages

All languages with LDAP bindings

C++
Java

C#
C++
Erlang

not officially supported
Go
Java
JavaScript

Node.js
PHP
Python

Server-side scripts

Stored procedures

Python

yes

Java

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

cell division

Sharding, horizontal partitioning

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Multi-source replication
Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency or Eventual Consistency depending on configuration

Foreign keys

Referential integrity

yes

Relationships in graphs

FOREIGN KEY constraints are not supported

Transaction concepts

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

Atomic execution of specific operations

ACID

Transactions are executed single-threaded within stored procedures

Concurrency

Support for concurrent manipulation of data

yes

yes, multi-version concurrency control (MVCC)

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

LDAP bind authentication

Role-based access control

Users and roles with access to stored procedures

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More resources

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