DBMS > Amazon Redshift vs. Atos Standard Common Repository vs. JanusGraph vs. Teradata vs. TigerGraph

System Properties Comparison Amazon Redshift vs. Atos Standard Common Repository vs. JanusGraph vs. Teradata vs. TigerGraph

Editorial information provided by DB-Engines

Name

This system has been discontinued and will be removed from the DB-Engines ranking.

Description

Large scale data warehouse service for use with business intelligence tools

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

A Graph DBMS optimized for distributed clusters

It was forked from the latest code base of Titan in January 2017

A hybrid cloud data analytics software platform (Teradata Vantage)

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

Primary database model

Relational DBMS

Document store
Key-value store

Graph DBMS

Relational DBMS

Graph DBMS

Secondary database models

Document store
Graph DBMS
Spatial DBMS
Time Series DBMS

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

Score	16.88
Rank	#35	Overall
	#22	Relational DBMS

Score	2.02
Rank	#125	Overall
	#12	Graph DBMS

Score	44.87
Rank	#22	Overall
	#15	Relational DBMS

Score	1.80
Rank	#138	Overall
	#13	Graph DBMS

Website

aws.amazon.com/redshift

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

janusgraph.org

www.teradata.com

www.tigergraph.com

Technical documentation

docs.aws.amazon.com/redshift

docs.janusgraph.org

docs.teradata.com

docs.tigergraph.com

Developer

Amazon (based on PostgreSQL)

Atos Convergence Creators

Linux Foundation; originally developed as Titan by Aurelius

Teradata

Initial release

2012

2016

2017

1984

2017

Current release

1703

0.6.3, February 2023

Teradata Vantage 1.0 MU2, January 2019

License

Commercial or Open Source

commercial

Open Source

Apache 2.0

commercial

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

C++

Server operating systems

hosted

Linux

Linux
OS X
Unix
Windows

hosted
Linux

Linux

Data scheme

yes

Schema and schema-less with LDAP views

yes

Typing

predefined data types such as float or date

yes

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

restricted

yes

Join-index to prejoin tables, aggregate index, sparse index, hash index

SQL

Support of SQL

yes

does not fully support an SQL-standard

yes

SQL 2016 + extensions

SQL-like query language (GSQL)

APIs and other access methods

JDBC
ODBC

LDAP

Java API
TinkerPop Blueprints
TinkerPop Frames
TinkerPop Gremlin
TinkerPop Rexster

.NET Client API
HTTP REST
JDBC
JMS Adapter
ODBC
OLE DB

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

Supported programming languages

All languages supporting JDBC/ODBC

All languages with LDAP bindings

Clojure
Java
Python

C
C++
Cobol
Java (JDBC-ODBC)
Perl
PL/1
Python
R
Ruby

C++
Java

Server-side scripts

Stored procedures

user defined functions

in Python

yes

UDFs, stored procedures, table functions in parallel

yes

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

cell division

yes

depending on the used storage backend (e.g. Cassandra, HBase, BerkeleyDB)

Sharding

Hashing

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

via Faunus, a graph analytics engine

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Immediate Consistency or Eventual Consistency depending on configuration

Eventual Consistency
Immediate Consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

informational only, not enforced by the system

yes

Relationships in graphs

yes

Relationships in graphs

Transaction concepts

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

ACID

Atomic execution of specific operations

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

Supports various storage backends: Cassandra, HBase, Berkeley DB, Akiban, Hazelcast

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

fine grained access rights according to SQL-standard

LDAP bind authentication

User authentification and security via Rexster Graph Server

fine grained access rights according to SQL-standard

Role-based access control

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