DBMS > Cubrid vs. jBASE vs. Netezza vs. Newts vs. OpenTSDB

System Properties Comparison Cubrid vs. jBASE vs. Netezza vs. Newts vs. OpenTSDB

Editorial information provided by DB-Engines

Name

Description

CUBRID is an open-source SQL-based relational database management system with object extensions for OLTP

A robust multi-value DBMS comprising development tools and middleware

Data warehouse and analytics appliance part of IBM PureSystems

Time Series DBMS based on Cassandra

Scalable Time Series DBMS based on HBase

Primary database model

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

Score	1.04
Rank	#187	Overall
	#87	Relational DBMS

Score	1.49
Rank	#156	Overall
	#3	Multivalue DBMS

Score	8.59
Rank	#45	Overall
	#29	Relational DBMS

Score	0.07
Rank	#375	Overall
	#41	Time Series DBMS

Score	1.68
Rank	#142	Overall
	#12	Time Series DBMS

Website

cubrid.com (korean)
cubrid.org (english)

www.rocketsoftware.com/products/rocket-multivalue-application-development-platform/rocket-jbase

www.ibm.com/products/netezza

opennms.github.io/newts

opentsdb.net

Technical documentation

cubrid.org/manuals

docs.rocketsoftware.com/bundle?labelkey=jbase_5.9

github.com/OpenNMS/newts/wiki

opentsdb.net/docs/build/html/index.html

Developer

CUBRID Corporation, CUBRID Foundation

Rocket Software (formerly Zumasys)

IBM

OpenNMS Group

currently maintained by Yahoo and other contributors

Initial release

2008

1991

2000

2014

2011

Current release

11.0, January 2021

5.7

License

Commercial or Open Source

Open Source

Apache Version 2.0

commercial

Open Source

Apache 2.0

Open Source

LGPL

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, C++, Java

Java

Server operating systems

Linux
Windows

AIX
Linux
Windows

Linux

included in appliance

Linux
OS X
Windows

Linux
Windows

Data scheme

yes

schema-free

yes

schema-free

Typing

predefined data types such as float or date

yes

optional

yes

numeric data for metrics, strings for tags

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

yes

Embedded SQL for jBASE in BASIC

yes

APIs and other access methods

ADO.NET
JDBC
ODBC
OLE DB

JDBC
ODBC
Proprietary protocol
RESTful HTTP API
SOAP-based API

JDBC
ODBC
OLE DB

HTTP REST
Java API

HTTP API
Telnet API

Supported programming languages

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

.Net
Basic
Jabbascript
Java

C
C++
Fortran
Java
Lua
Perl
Python
R

Java

Erlang
Go
Java
Python
R
Ruby

Server-side scripts

Stored procedures

Java Stored Procedures

yes

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

based on Cassandra

Sharding

based on HBase

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

yes

Source-replica replication

selectable replication factor

based on Cassandra

selectable replication factor

based on HBase

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency

based on Cassandra
Immediate Consistency

based on Cassandra

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

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

Access rights can be defined down to the item level

Users with fine-grained authorization concept

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More resources

DB-Engines blog posts

Time Series DBMS are the database category with the fastest increase in popularity
4 July 2016, Matthias Gelbmann

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