DBMS > Derby vs. Hypertable vs. Kinetica vs. OpenQM

System Properties Comparison Derby vs. Hypertable vs. Kinetica vs. OpenQM

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Editorial information provided by DB-Engines

Name

Hypertable has stopped its further development with March 2016 and is removed from the DB-Engines ranking.

Description

Full-featured RDBMS with a small footprint, either embedded into a Java application or used as a database server.

An open source BigTable implementation based on distributed file systems such as Hadoop

Fully vectorized database across both GPUs and CPUs

QpenQM is a high-performance, self-tuning, multi-value DBMS

Primary database model

Secondary database models

Spatial DBMS
Time Series DBMS

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

Score	4.71
Rank	#69	Overall
	#37	Relational DBMS

Score	0.64
Rank	#236	Overall
	#109	Relational DBMS

Score	0.27
Rank	#298	Overall
	#10	Multivalue DBMS

Website

db.apache.org/derby

www.kinetica.com

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

Technical documentation

db.apache.org/derby/manuals/index.html

docs.kinetica.com

Developer

Apache Software Foundation

Hypertable Inc.

Kinetica

Rocket Software, originally Martin Phillips

Initial release

1997

2009

2012

1993

Current release

10.17.1.0, November 2023

0.9.8.11, March 2016

7.1, August 2021

3.4-12

License

Commercial or Open Source

Open Source

Apache version 2

Open Source

GNU version 3. Commercial license available

commercial

Open Source

GPLv2, extended commercial license available

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

Java

C++

C, C++

Server operating systems

All OS with a Java VM

Linux
OS X
Windows

an inofficial Windows port is available

Linux

AIX
FreeBSD
Linux
macOS
Raspberry Pi
Solaris
Windows

Data scheme

yes

schema-free

yes

with some exceptions

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

restricted

only exact value or prefix value scans

yes

SQL

Support of SQL

yes

SQL-like DML and DDL statements

APIs and other access methods

JDBC

C++ API
Thrift

JDBC
ODBC
RESTful HTTP API

Supported programming languages

Java

C++
Java
Perl
PHP
Python
Ruby

C++
Java
JavaScript (Node.js)
Python

.Net
Basic
C
Java
Objective C
PHP
Python

Server-side scripts

Stored procedures

Java Stored Procedures

user defined functions

yes

Triggers

yes

triggers when inserted values for one or more columns fall within a specified range

yes

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

yes

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

selectable replication factor on file system level

Source-replica replication

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Immediate Consistency or Eventual Consistency depending on configuration

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

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

GPU vRAM or System RAM

User concepts

Access control

fine grained access rights according to SQL-standard

Access rights for users and roles on table level

Access rights can be defined down to the item level

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