DBMS > Atos Standard Common Repository vs. FeatureBase vs. TerminusDB vs. TigerGraph

System Properties Comparison Atos Standard Common Repository vs. FeatureBase vs. TerminusDB vs. TigerGraph

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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

Real-time database platform that powers real-time analytics and machine learning applications by simultaneously executing low-latency, high-throughput, and highly concurrent workloads.

Scalable Graph Database platform making enterprise data available by exploiting inferred entities and relationships

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

Primary database model

Document store
Key-value store

Relational DBMS

Graph DBMS

Secondary database models

Document store
RDF store

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

Score	0.23
Rank	#296	Overall
	#134	Relational DBMS

Score	0.19
Rank	#311	Overall
	#27	Graph DBMS

Score	1.44
Rank	#152	Overall
	#14	Graph DBMS

Website

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

www.featurebase.com

terminusdb.com

www.tigergraph.com

Technical documentation

docs.featurebase.com

terminusdb.github.io/terminusdb/#

docs.tigergraph.com

Developer

Atos Convergence Creators

Molecula and Pilosa Open Source Contributors

DataChemist Ltd.

Initial release

2016

2017

2018

2017

Current release

1703

2022, May 2022

11.0.0, January 2023

License

Commercial or Open Source

commercial

Open Source

GPL V3

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

Prolog, Rust

C++

Server operating systems

Linux

Linux
macOS

Linux

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

SQL queries

SQL-like query language (WOQL)

SQL-like query language (GSQL)

APIs and other access methods

LDAP

gRPC
JDBC
Kafka Connector
ODBC

OWL
RESTful HTTP API
WOQL (Web Object Query Language)

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

Supported programming languages

All languages with LDAP bindings

Java
Python

JavaScript
Python

C++
Java

Server-side scripts

Stored procedures

yes

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

cell division

Sharding

Graph Partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Journaling Streams

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

Transaction concepts

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

Atomic execution of specific operations

yes

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

yes, using Linux fsync

yes

in-memory journaling

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

LDAP bind authentication

Role-based access control

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