DBMS > Hypertable vs. IBM Cloudant vs. MariaDB vs. MonetDB vs. Oracle Berkeley DB

System Properties Comparison Hypertable vs. IBM Cloudant vs. MariaDB vs. MonetDB vs. Oracle Berkeley DB

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

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

Database as a Service offering based on Apache CouchDB

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.

A relational database management system that stores data in columns

Widely used in-process key-value store

Primary database model

supports sorted and unsorted key sets
Native XML DBMS

in the Oracle Berkeley DB XML version

Secondary database models

Document store
Graph DBMS

with OQGraph storage engine
Spatial DBMS

Document store
Spatial DBMS

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

Score	2.85
Rank	#95	Overall
	#18	Document stores

Score	83.44
Rank	#15	Overall
	#10	Relational DBMS

Score	1.72
Rank	#135	Overall
	#62	Relational DBMS

Score	1.88
Rank	#130	Overall
	#23	Key-value stores
	#3	Native XML DBMS

Website

www.ibm.com/products/cloudant

mariadb.com

Site of MariaDB Corporation
mariadb.org

Site of MariaDB Foundation

www.monetdb.org

www.oracle.com/database/technologies/related/berkeleydb.html

Technical documentation

cloud.ibm.com/docs/Cloudant

mariadb.com/kb/en/library

www.monetdb.org/Documentation

docs.oracle.com/cd/E17076_05/html/index.html

Developer

Hypertable Inc.

IBM, Apache Software Foundation

IBM acquired Cloudant in February 2014

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

The lead developer Monty Widenius is the original author of MySQL

MonetDB BV

Oracle

originally developed by Sleepycat, which was acquired by Oracle

Initial release

2009

2010

2009

Fork of MySQL, which was first released in 1995

2004

1994

Current release

0.9.8.11, March 2016

11.5.2, August 2024

Dec2023 (11.49), December 2023

18.1.40, May 2020

License

Commercial or Open Source

Open Source

GNU version 3. Commercial license available

commercial

Open Source

GPL version 2, commercial enterprise subscription available

Open Source

Mozilla Public License 2.0

Open Source

commercial license available

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

Providers of DBaaS offerings, please contact us to be listed.

STACKIT MariaDB offers MariaDB in a fully managed version in enterprise grade, 100% GDPR-compliant.

Implementation language

C++

Erlang

C and C++

C, Java, C++ (depending on the Berkeley DB edition)

Server operating systems

Linux
OS X
Windows

an inofficial Windows port is available

hosted

FreeBSD
Linux
Solaris
Windows

ColumnStore storage engine not available on Windows

FreeBSD
Linux
OS X
Solaris
Windows

AIX
Android
FreeBSD
iOS
Linux
OS X
Solaris
VxWorks
Windows

Data scheme

schema-free

yes

Dynamic columns are supported

yes

schema-free

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

only with the Berkeley DB XML edition

Secondary indexes

restricted

only exact value or prefix value scans

yes

SQL

Support of SQL

yes

with proprietary extensions

yes

SQL 2003 with some extensions

yes

SQL interfaced based on SQLite is available

APIs and other access methods

C++ API
Thrift

RESTful HTTP/JSON API

ADO.NET
JDBC
ODBC
Proprietary native API

JDBC
native C library

MAPI library (MonetDB application programming interface)
ODBC

Supported programming languages

C++
Java
Perl
PHP
Python
Ruby

C#
Java
JavaScript
Objective-C
PHP
Ruby

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

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

.Net

Figaro is a .Net framework assembly that extends Berkeley DB XML into an embeddable database engine for .NET
others

Third-party libraries to manipulate Berkeley DB files are available for many languages
C
C#
C++
Java
JavaScript (Node.js)

3rd party binding
Perl
Python
Tcl

Server-side scripts

Stored procedures

View functions (Map-Reduce) in JavaScript

yes

PL/SQL compatibility added with version 10.3

yes, in SQL, C, R

Triggers

yes

only for the SQL API

Partitioning methods

Methods for storing different data on different nodes

Sharding

several options for horizontal partitioning and Sharding

Sharding via remote tables

none

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor on file system level

Multi-source replication
Source-replica replication

none

Source-replica replication available in experimental status

Source-replica replication

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

Immediate Consistency

Foreign keys

Referential integrity

yes

not for MyISAM storage engine

yes

Transaction concepts

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

atomic operations within a document possible

ACID

not for MyISAM storage engine

ACID

Concurrency

Support for concurrent manipulation of data

yes

Optimistic locking

yes

Durability

Support for making data persistent

yes

not for in-memory storage engine

yes

In-memory capabilities

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

yes

with MEMORY storage engine

yes

User concepts

Access control

Access rights for users can be defined per database

fine grained access rights according to SQL-standard

More information provided by the system vendor

Specific characteristics

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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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