DBMS > CouchDB vs. Google BigQuery vs. Ignite vs. MariaDB vs. Oracle Berkeley DB

System Properties Comparison CouchDB vs. Google BigQuery vs. Ignite vs. MariaDB vs. Oracle Berkeley DB

Editorial information provided by DB-Engines

Name

Description

A native JSON - document store inspired by Lotus Notes, scalable from globally distributed server-clusters down to mobile phones.

Large scale data warehouse service with append-only tables

Apache Ignite is a memory-centric distributed database, caching, and processing platform for transactional, analytical, and streaming workloads, delivering in-memory speeds at petabyte scale.

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.

Widely used in-process key-value store

Primary database model

Document store

Relational DBMS

Key-value store
Relational DBMS

Relational DBMS

Key-value store

supports sorted and unsorted key sets
Native XML DBMS

in the Oracle Berkeley DB XML version

Secondary database models

Spatial DBMS

using the Geocouch extension

Document store
Graph DBMS

with OQGraph storage engine
Spatial DBMS

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

Score	9.30
Rank	#45	Overall
	#7	Document stores

Score	60.38
Rank	#19	Overall
	#13	Relational DBMS

Score	3.16
Rank	#96	Overall
	#15	Key-value stores
	#49	Relational DBMS

Score	93.21
Rank	#13	Overall
	#9	Relational DBMS

Score	2.21
Rank	#117	Overall
	#20	Key-value stores
	#3	Native XML DBMS

Website

couchdb.apache.org

cloud.google.com/bigquery

ignite.apache.org

mariadb.com

Site of MariaDB Corporation
mariadb.org

Site of MariaDB Foundation

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

Technical documentation

docs.couchdb.org/en/stable

cloud.google.com/bigquery/docs

apacheignite.readme.io/docs

mariadb.com/kb/en/library

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

Developer

Apache Software Foundation

Apache top-level project, originally developed by Damien Katz, a former Lotus Notes developer

Google

Apache Software Foundation

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

The lead developer Monty Widenius is the original author of MySQL

Oracle

originally developed by Sleepycat, which was acquired by Oracle

Initial release

2005

2010

2015

2009

Fork of MySQL, which was first released in 1995

1994

Current release

3.3.3, December 2023

Apache Ignite 2.6

11.3.2, February 2024

18.1.40, May 2020

License

Commercial or Open Source

Open Source

Apache version 2

commercial

Open Source

Apache 2.0

Open Source

GPL version 2, commercial enterprise subscription available

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.

Implementation language

Erlang

C++, Java, .Net

C and C++

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

Server operating systems

Android
BSD
Linux
OS X
Solaris
Windows

hosted

Linux
OS X
Solaris
Windows

FreeBSD
Linux
Solaris
Windows

ColumnStore storage engine not available on Windows

AIX
Android
FreeBSD
iOS
Linux
OS X
Solaris
VxWorks
Windows

Data scheme

schema-free

yes

Dynamic columns are supported

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

yes

via views

yes

SQL

Support of SQL

yes

ANSI-99 for query and DML statements, subset of DDL

yes

with proprietary extensions

yes

SQL interfaced based on SQLite is available

APIs and other access methods

RESTful HTTP/JSON API

HDFS API
Hibernate
JCache
JDBC
ODBC
Proprietary protocol
RESTful HTTP API
Spring Data

ADO.NET
JDBC
ODBC
Proprietary native API

Supported programming languages

C
C#
ColdFusion
Erlang
Haskell
Java
JavaScript
Lisp
Lua
Objective-C
OCaml
Perl
PHP
PL/SQL
Python
Ruby
Smalltalk

.Net
Java
JavaScript
Objective-C
PHP
Python
Ruby

C#
C++
Java
PHP
Python
Ruby
Scala

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

.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 in JavaScript

user defined functions

in JavaScript

yes (compute grid and cache interceptors can be used instead)

yes

PL/SQL compatibility added with version 10.3

Triggers

yes

yes (cache interceptors and events)

yes

only for the SQL API

Partitioning methods

Methods for storing different data on different nodes

Sharding

improved architecture with release 2.0

none

Sharding

several options for horizontal partitioning and Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication
Source-replica replication

yes (replicated cache)

Multi-source replication
Source-replica replication

Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

yes (compute grid and hadoop accelerator)

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency

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

atomic operations within a single document possible

Since BigQuery is designed for querying data

ACID

not for MyISAM storage engine

ACID

Concurrency

Support for concurrent manipulation of data

yes

strategy: 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

Access privileges (owner, writer, reader) on dataset, table or view level

Google Cloud Identity & Access Management (IAM)

Security Hooks for custom implementations

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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