DBMS > GBase vs. Graph Engine vs. Teradata vs. Warp 10

System Properties Comparison GBase vs. Graph Engine vs. Teradata vs. Warp 10

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Editorial information provided by DB-Engines

Name

Description

Widely used RDBMS in China, including analytical, transactional, distributed transactional, and cloud-native data warehousing.

A distributed in-memory data processing engine, underpinned by a strongly-typed RAM store and a general distributed computation engine

A hybrid cloud data analytics software platform (Teradata Vantage)

TimeSeries DBMS specialized on timestamped geo data based on LevelDB or HBase

Primary database model

Relational DBMS

Graph DBMS
Key-value store

Relational DBMS

Time Series 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	1.05
Rank	#186	Overall
	#86	Relational DBMS

Score	0.67
Rank	#232	Overall
	#21	Graph DBMS
	#34	Key-value stores

Score	44.87
Rank	#22	Overall
	#15	Relational DBMS

Score	0.14
Rank	#344	Overall
	#32	Time Series DBMS

Website

Technical documentation

www.graphengine.io/docs/manual

docs.teradata.com

www.warp10.io/content/02_Getting_started

Developer

General Data Technology Co., Ltd.

Microsoft

Teradata

SenX

Initial release

2004

2010

1984

2015

Current release

GBase 8a, GBase 8s, GBase 8c

Teradata Vantage 1.0 MU2, January 2019

License

Commercial or Open Source

commercial

Open Source

MIT License

commercial

Open Source

Apache License 2.0

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, Java, Python

.NET and C

Java

Server operating systems

Linux

.NET

hosted
Linux

Linux
OS X
Windows

Data scheme

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

Standard with numerous extensions

yes

SQL 2016 + extensions

APIs and other access methods

ADO.NET
C API
JDBC
ODBC

RESTful HTTP API

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

HTTP API
Jupyter
WebSocket

Supported programming languages

C#
C++
F#
Visual Basic

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

Server-side scripts

Stored procedures

user defined functions

yes

UDFs, stored procedures, table functions in parallel

yes

WarpScript

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

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

horizontal partitioning

Sharding

Hashing

Sharding

based on HBase

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Multi-source replication
Source-replica replication

selectable replication factor

based on HBase

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

based on HBase

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

Durability

Support for making data persistent

yes

optional: either by committing a write-ahead log (WAL) to the local persistent storage or by dumping the memory to a persistent storage

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

yes

fine grained access rights according to SQL-standard

Mandatory use of cryptographic tokens, containing fine-grained authorizations

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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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