DBMS > Ingres vs. Kingbase vs. Teradata vs. XTDB

System Properties Comparison Ingres vs. Kingbase vs. Teradata vs. XTDB

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Editorial information provided by DB-Engines

Name

Description

Well established RDBMS

An enterprise-class RDBMS compatible with PostgreSQL and Oracle and widely used in China.

A hybrid cloud data analytics software platform (Teradata Vantage)

A general purpose database with bitemporal SQL and Datalog and graph queries

Primary database model

Relational DBMS

Document store

Secondary database models

Document store
Spatial DBMS

Document store
Graph DBMS
Spatial DBMS
Time Series DBMS

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Score	3.80
Rank	#82	Overall
	#44	Relational DBMS

Score	0.50
Rank	#257	Overall
	#119	Relational DBMS

Score	44.87
Rank	#22	Overall
	#15	Relational DBMS

Score	0.18
Rank	#332	Overall
	#46	Document stores

Website

www.actian.com/databases/ingres

www.kingbase.com.cn

www.teradata.com

github.com/xtdb/xtdb
www.xtdb.com

Technical documentation

docs.actian.com/ingres

docs.teradata.com

www.xtdb.com/docs

Developer

Actian Corporation

BeiJing KINGBASE Information technologies inc.

Teradata

Juxt Ltd.

Initial release

1974

originally developed at University Berkely in early 1970s

1999

1984

2019

Current release

11.2, May 2022

V8.0, August 2021

Teradata Vantage 1.0 MU2, January 2019

1.19, September 2021

License

Commercial or Open Source

commercial

Open Source

MIT License

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

C and Java

Clojure

Server operating systems

AIX
HP Open VMS
HP-UX
Linux
Solaris
Windows

Linux
Windows

hosted
Linux

All OS with a Java 8 (and higher) VM
Linux

Data scheme

yes

schema-free

Typing

predefined data types such as float or date

yes

yes, extensible-data-notation format

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.

but tools for importing/exporting data from/to XML-files available

yes

Secondary indexes

yes

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

yes

SQL

Support of SQL

yes

Standard with numerous extensions

yes

SQL 2016 + extensions

limited SQL, making use of Apache Calcite

APIs and other access methods

.NET Client API
JDBC
ODBC
proprietary protocol (OpenAPI)

ADO.NET
gokb
JDBC
kdbndp
ODBC
PDI
PDO
Pro*C
psycopg2
QT

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

HTTP REST
JDBC

Supported programming languages

.Net
C
C++
Go
Java
JavaScript (Node.js)
Perl
PHP
Python

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

Clojure
Java

Server-side scripts

Stored procedures

yes

user defined functions

yes

UDFs, stored procedures, table functions in parallel

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

horizontal partitioning

Ingres Star to access multiple databases simultaneously

horizontal partitioning (by range, list and hash) and vertical partitioning

Sharding

Hashing

none

Replication methods

Methods for redundantly storing data on multiple nodes

Ingres Replicator

yes

Multi-source replication
Source-replica replication

yes, each node contains all data

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

Transaction concepts

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

ACID

Concurrency

Support for concurrent manipulation of data

yes

MVCC

yes

Durability

Support for making data persistent

yes

yes, flexibel persistency by using storage technologies like Apache Kafka, RocksDB or LMDB

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

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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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