DBMS > Atos Standard Common Repository vs. HugeGraph vs. Oracle vs. TigerGraph vs. Valentina Server

System Properties Comparison Atos Standard Common Repository vs. HugeGraph vs. Oracle vs. TigerGraph vs. Valentina Server

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

A fast-speed and highly-scalable Graph DBMS

Widely used RDBMS

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

Object-relational database and reports server

Primary database model

Document store
Key-value store

Secondary database models

Document store
Graph DBMS

with Oracle Spatial and Graph
RDF store

with Oracle Spatial and Graph
Spatial DBMS

with Oracle Spatial and Graph
Vector DBMS

since Oracle 23

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

Score	0.15
Rank	#339	Overall
	#33	Graph DBMS

Score	1234.27
Rank	#1	Overall
	#1	Relational DBMS

Score	1.83
Rank	#141	Overall
	#13	Graph DBMS

Score	0.18
Rank	#329	Overall
	#144	Relational DBMS

Website

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

github.com/hugegraph
hugegraph.apache.org

www.oracle.com/database

www.tigergraph.com

www.valentina-db.net

Technical documentation

hugegraph.apache.org/docs

docs.oracle.com/en/database

docs.tigergraph.com

valentina-db.com/docs/dokuwiki/v5/doku.php

Developer

Atos Convergence Creators

Baidu

Oracle

Paradigma Software

Initial release

2016

2018

1980

2017

1999

Current release

1703

0.9

23c, September 2023

5.7.5

License

Commercial or Open Source

commercial

Open Source

Apache Version 2.0

commercial

restricted free version is available

commercial

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 and C++

C++

Server operating systems

Linux

Linux
macOS
Unix

AIX
HP-UX
Linux
OS X
Solaris
Windows
z/OS

Linux

Linux
OS X
Windows

Data scheme

Schema and schema-less with LDAP views

yes

Schemaless in JSON and XML columns

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

also supports composite index and range index

yes

SQL

Support of SQL

yes

with proprietary extensions

SQL-like query language (GSQL)

yes

APIs and other access methods

LDAP

Java API
RESTful HTTP API
TinkerPop Gremlin

JDBC
ODBC
ODP.NET
Oracle Call Interface (OCI)

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

ODBC

Supported programming languages

All languages with LDAP bindings

Groovy
Java
Python

C
C#
C++
Clojure
Cobol
Delphi
Eiffel
Erlang
Fortran
Groovy
Haskell
Java
JavaScript
Lisp
Objective C
OCaml
Perl
PHP
Python
R
Ruby
Scala
Tcl
Visual Basic

C++
Java

.Net
C
C#
C++
Objective-C
PHP
Ruby
Visual Basic
Visual Basic.NET

Server-side scripts

Stored procedures

asynchronous Gremlin script jobs

PL/SQL

also stored procedures in Java possible

yes

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

cell division

yes

depending on used storage backend, e.g. Cassandra and HBase

Sharding, horizontal partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

yes

depending on used storage backend, e.g. Cassandra and HBase

Multi-source replication
Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

via hugegraph-spark

can be realized in PL/SQL

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency or Eventual Consistency depending on configuration

Eventual Consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

edges in graph

yes

Relationships in graphs

yes

Transaction concepts

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

Atomic execution of specific operations

ACID

isolation level can be parameterized

ACID

Concurrency

Support for concurrent manipulation of data

yes

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

Version 12c introduced the new option 'Oracle Database In-Memory'

yes

User concepts

Access control

LDAP bind authentication

Users, roles and permissions

fine grained access rights according to SQL-standard

Role-based access control

fine grained access rights according to SQL-standard

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