DBMS > Drizzle vs. H2 vs. Kdb vs. SpatiaLite

System Properties Comparison Drizzle vs. H2 vs. Kdb vs. SpatiaLite

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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.

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

High performance Time Series DBMS

Spatial extension of SQLite

Primary database model

Relational DBMS

Time Series DBMS
Vector DBMS

Spatial DBMS

Secondary database models

Spatial DBMS

Relational DBMS

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

Score	8.13
Rank	#49	Overall
	#31	Relational DBMS

Score	7.55
Rank	#53	Overall
	#3	Time Series DBMS
	#1	Vector DBMS

Score	1.60
Rank	#149	Overall
	#3	Spatial DBMS

Website

www.h2database.com

kx.com

www.gaia-gis.it/fossil/libspatialite/index

Technical documentation

www.h2database.com/html/main.html

code.kx.com

www.gaia-gis.it/gaia-sins/spatialite_topics.html

Developer

Drizzle project, originally started by Brian Aker

Thomas Mueller

Kx Systems, a division of First Derivatives plc

Alessandro Furieri

Initial release

2008

2005

2000

kdb was released 2000, kdb+ in 2003

2008

Current release

7.2.4, September 2012

2.2.220, July 2023

3.6, May 2018

5.0.0, August 2020

License

Commercial or Open Source

Open Source

GNU GPL

Open Source

dual-licence (Mozilla public license, Eclipse public license)

commercial

free 32-bit version

Open Source

MPL 1.1, GPL v2.0 or LGPL v2.1

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++

Server operating systems

FreeBSD
Linux
OS X

All OS with a Java VM

Linux
OS X
Solaris
Windows

server-less

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.

yes

Secondary indexes

yes

table attribute 'grouped'

yes

SQL

Support of SQL

yes

with proprietary extensions

yes

SQL-like query language (q)

yes

APIs and other access methods

JDBC

JDBC
ODBC

HTTP API
JDBC
Jupyter
Kafka
ODBC
WebSocket

Supported programming languages

C
C++
Java
PHP

Java

C
C#
C++
Go
J
Java
JavaScript
Lua
MatLab
Perl
PHP
Python
R
Scala

Server-side scripts

Stored procedures

Java Stored Procedures and User-Defined Functions

user defined functions

Triggers

hooks for callbacks inside the server can be used.

yes

with views

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

horizontal partitioning

none

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication
Source-replica replication

With clustering: 2 database servers on different computers operate on identical copies of a database

Source-replica replication

none

MapReduce

Offers an API for user-defined Map/Reduce methods

similar paradigm used for internal processing

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

yes, multi-version concurrency control (MVCC)

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

Pluggable authentication mechanisms

e.g. LDAP, HTTP

fine grained access rights according to SQL-standard

rights management via user accounts

More information provided by the system vendor

Specific characteristics

Integrated columnar database & programming system for streaming, real time and historical...
» more

Competitive advantages

provides seamless scalability; runs on industry standard server platforms; is top-ranked...
» more

Typical application scenarios

tick database streaming sensor data massive intelligence applications oil and gas...
» more

Key customers

Goldman Sachs Morgan Stanley Merrill Lynch J.P. Morgan Deutsche Bank IEX Securities...
» more

Market metrics

kdb+ performance and reliability proven by our customers in critical infrastructure...
» more

Licensing and pricing models

upon request
» more

We invite representatives of system vendors to contact us for updating and extending the system information,
and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.

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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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6 April 2021, Matthias Gelbmann

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