DBMS > Drizzle vs. HyperSQL vs. Kinetica vs. Transbase

System Properties Comparison Drizzle vs. HyperSQL vs. Kinetica vs. Transbase

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Editorial information provided by DB-Engines

Name

Drizzle has published its last release in September 2012. The open-source project is discontinued and Drizzle is excluded from the DB-Engines ranking.

Description

MySQL fork with a pluggable micro-kernel and with an emphasis of performance over compatibility.

Multithreaded, transactional RDBMS written in Java

also known as HSQLDB

Fully vectorized database across both GPUs and CPUs

A resource-optimized, high-performance, universally applicable RDBMS

Primary database model

Relational DBMS

Secondary database models

Spatial DBMS
Time Series DBMS

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

Score	3.14
Rank	#85	Overall
	#46	Relational DBMS

Score	0.42
Rank	#261	Overall
	#120	Relational DBMS

Score	0.05
Rank	#355	Overall
	#150	Relational DBMS

Website

hsqldb.org

www.kinetica.com

www.transaction.de/en/products/transbase.html

Technical documentation

hsqldb.org/web/hsqlDocsFrame.html

docs.kinetica.com

www.transaction.de/en/products/transbase/features.html

Developer

Drizzle project, originally started by Brian Aker

Kinetica

Transaction Software GmbH

Initial release

2008

2001

2012

1987

Current release

7.2.4, September 2012

2.7.2, June 2023

7.1, August 2021

Transbase 8.3, 2022

License

Commercial or Open Source

Open Source

GNU GPL

Open Source

based on BSD license

commercial

free development 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++

Java

C, C++

C and C++

Server operating systems

FreeBSD
Linux
OS X

All OS with a Java VM

Embedded (into Java applications) and Client-Server operating modes

Linux

FreeBSD
Linux
macOS
Solaris
Windows

Data scheme

yes

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.

Secondary indexes

yes

SQL

Support of SQL

yes

with proprietary extensions

yes

SQL-like DML and DDL statements

yes

APIs and other access methods

JDBC

HTTP API

JDBC via HTTP
JDBC
ODBC

JDBC
ODBC
RESTful HTTP API

ADO.NET
JDBC
ODBC
Proprietary native API

Supported programming languages

C
C++
Java
PHP

All languages supporting JDBC/ODBC
Java

C++
Java
JavaScript (Node.js)
Python

C
C#
C++
Java
JavaScript
Kotlin
Objective-C
PHP
Python

Server-side scripts

Stored procedures

Java, SQL

user defined functions

yes

Triggers

hooks for callbacks inside the server can be used.

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

Sharding

none

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication
Source-replica replication

none

Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

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

yes

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

Pluggable authentication mechanisms

e.g. LDAP, HTTP

fine grained access rights according to SQL-standard

Access rights for users and roles on table level

fine grained access rights according to SQL-standard

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More resources

DB-Engines blog posts

MySQL won the April ranking; did its forks follow?
1 April 2015, Paul Andlinger

Has MySQL finally lost its mojo?
1 July 2013, Matthias Gelbmann

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