DBMS > Galaxybase vs. IBM Db2 vs. Teradata vs. Yanza

System Properties Comparison Galaxybase vs. IBM Db2 vs. Teradata vs. Yanza

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Editorial information provided by DB-Engines

Name

Yanza seems to be discontinued. Therefore it is excluded from the DB-Engines Ranking.

Description

Scalable, ACID-compliant native distributed parallel graph platform

Common in IBM host environments, 2 different versions for host and Windows/Linux

A hybrid cloud data analytics software platform (Teradata Vantage)

Time Series DBMS for IoT Applications

Primary database model

Graph DBMS

Relational DBMS

Since Version 10.5 support for JSON/BSON documents compatible with MongoDB

Relational DBMS

Time Series DBMS

Secondary database models

Document store
RDF store

in Db2 LUW (Linux, Unix, Windows)
Spatial DBMS

with Db2 Spatial Extender

Document store
Graph DBMS
Spatial DBMS
Time Series DBMS

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

Score	0.00
Rank	#383	Overall
	#39	Graph DBMS

Score	128.46
Rank	#8	Overall
	#5	Relational DBMS

Score	45.33
Rank	#21	Overall
	#15	Relational DBMS

Website

galaxybase.com

www.ibm.com/products/db2

www.teradata.com

yanza.com

Technical documentation

www.ibm.com/docs/en/db2

docs.teradata.com

Developer

Chuanglin(Createlink) Technology Co., Ltd 浙江创邻科技有限公司

IBM

Teradata

Yanza

Initial release

2017

1983

host version

1984

2015

Current release

Nov 20, November 2021

12.1, October 2016

Teradata Vantage 1.0 MU2, January 2019

License

Commercial or Open Source

commercial

free version is available

commercial

free version available

Cloud-based only

Only available as a cloud service

but mainly used as a service provided by Yanza

DBaaS offerings (sponsored links)

Database as a Service

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

Implementation language

C and Java

C and C++

Server operating systems

Linux

AIX
HP-UX
Linux
Solaris
Windows
z/OS

hosted
Linux

Windows

Data scheme

Strong typed schema

yes

schema-free

Typing

predefined data types such as float or date

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

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

SQL

Support of SQL

yes

SQL 2016 + extensions

APIs and other access methods

Browser interface
console (shell)
Graph API (Gremlin)
OpenCypher
Proprietary native API

ADO.NET
JDBC
JSON style queries

MongoDB compatible
ODBC
XQuery

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

HTTP API

Supported programming languages

Go
Java
Python

C
C#
C++
Cobol
Delphi
Fortran
Java
Perl
PHP
Python
Ruby
Visual Basic

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

any language that supports HTTP calls

Server-side scripts

Stored procedures

user defined procedures and functions

yes

UDFs, stored procedures, table functions in parallel

Triggers

yes

Timer and event based

Partitioning methods

Methods for storing different data on different nodes

Sharding

only with Windows/Unix/Linux Version

Sharding

Hashing

none

Replication methods

Methods for redundantly storing data on multiple nodes

yes

with separate tools (MQ, InfoSphere)

Multi-source replication
Source-replica replication

none

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Foreign keys

Referential integrity

yes

Relationships in graphs

yes

Transaction concepts

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

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

User concepts

Access control

Role-based access control

fine grained access rights according to SQL-standard

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More resources

DB-Engines blog posts

Teradata is the most popular data warehouse DBMS
2 April 2013, Paul Andlinger

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