DBMS > Bangdb vs. Drizzle vs. H2 vs. Hypertable vs. MariaDB

System Properties Comparison Bangdb vs. Drizzle vs. H2 vs. Hypertable vs. MariaDB

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.

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

Description

Converged and high performance database for device data, events, time series, document and graph

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.

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

MySQL application compatible open source RDBMS, enhanced with high availability, security, interoperability and performance capabilities. MariaDB ColumnStore provides a column-oriented storage engine and MariaDB Xpand supports distributed SQL.

Primary database model

Document store
Graph DBMS
Time Series DBMS

Relational DBMS

Wide column store

Relational DBMS

Secondary database models

Spatial DBMS

Document store
Graph DBMS

with OQGraph storage engine
Spatial DBMS

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

Score	0.15
Rank	#334	Overall
	#45	Document stores
	#31	Graph DBMS
	#31	Time Series DBMS

Score	8.22
Rank	#50	Overall
	#32	Relational DBMS

Score	93.81
Rank	#13	Overall
	#9	Relational DBMS

Website

bangdb.com

www.h2database.com

mariadb.com

Site of MariaDB Corporation
mariadb.org

Site of MariaDB Foundation

Technical documentation

docs.bangdb.com

www.h2database.com/html/main.html

mariadb.com/kb/en/library

Developer

Sachin Sinha, BangDB

Drizzle project, originally started by Brian Aker

Thomas Mueller

Hypertable Inc.

MariaDB Corporation Ab (MariaDB Enterprise),
MariaDB Foundation (community MariaDB Server)

The lead developer Monty Widenius is the original author of MySQL

Initial release

2012

2008

2005

2009

Fork of MySQL, which was first released in 1995

Current release

BangDB 2.0, October 2021

7.2.4, September 2012

2.2.220, July 2023

0.9.8.11, March 2016

11.3.2, February 2024

License

Commercial or Open Source

Open Source

BSD 3

Open Source

GNU GPL

Open Source

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

Open Source

GNU version 3. Commercial license available

Open Source

GPL version 2, commercial enterprise subscription 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

C, C++

C++

Java

C++

C and C++

Server operating systems

Linux

FreeBSD
Linux
OS X

All OS with a Java VM

Linux
OS X
Windows

an inofficial Windows port is available

FreeBSD
Linux
Solaris
Windows

ColumnStore storage engine not available on Windows

Data scheme

schema-free

yes

schema-free

yes

Dynamic columns are supported

Typing

predefined data types such as float or date

yes: string, long, double, int, geospatial, stream, events

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

secondary, composite, nested, reverse, geospatial

yes

restricted

only exact value or prefix value scans

yes

SQL

Support of SQL

SQL like support with command line tool

yes

with proprietary extensions

yes

with proprietary extensions

APIs and other access methods

Proprietary protocol
RESTful HTTP API

JDBC

JDBC
ODBC

C++ API
Thrift

ADO.NET
JDBC
ODBC
Proprietary native API

Supported programming languages

C
C#
C++
Java
Python

C
C++
Java
PHP

Java

C++
Java
Perl
PHP
Python
Ruby

Ada
C
C#
C++
D
Eiffel
Erlang
Go
Haskell
Java
JavaScript (Node.js)
Objective-C
OCaml
Perl
PHP
Python
Ruby
Scheme
Tcl

Server-side scripts

Stored procedures

Java Stored Procedures and User-Defined Functions

yes

PL/SQL compatibility added with version 10.3

Triggers

yes, Notifications (with Streaming only)

hooks for callbacks inside the server can be used.

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding (enterprise version only). P2P based virtual network overlay with consistent hashing and chord algorithm

Sharding

none

Sharding

several options for horizontal partitioning and Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor, Knob for CAP (enterprise version only)

Multi-source replication
Source-replica replication

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

selectable replication factor on file system level

Multi-source replication
Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Tunable consistency, set CAP knob accordingly

Immediate Consistency

Foreign keys

Referential integrity

yes

not for MyISAM storage engine

Transaction concepts

Support to ensure data integrity after non-atomic manipulations of data

ACID

not for MyISAM storage engine

Concurrency

Support for concurrent manipulation of data

yes, optimistic concurrency control

yes

yes, multi-version concurrency control (MVCC)

yes

Durability

Support for making data persistent

yes, implements WAL (Write ahead log) as well

yes

not for in-memory storage engine

In-memory capabilities

Is there an option to define some or all structures to be held in-memory only.

yes, run db with in-memory only mode

yes

with MEMORY storage engine

User concepts

Access control

yes (enterprise version only)

Pluggable authentication mechanisms

e.g. LDAP, HTTP

fine grained access rights according to SQL-standard

More information provided by the system vendor

Specific characteristics

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Competitive advantages

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Typical application scenarios

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Key customers

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Market metrics

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Licensing and pricing models

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