DBMS > Microsoft SQL Server vs. MonetDB vs. Oracle Berkeley DB vs. searchxml

System Properties Comparison Microsoft SQL Server vs. MonetDB vs. Oracle Berkeley DB vs. searchxml

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Editorial information provided by DB-Engines

Name

Description

Microsofts flagship relational DBMS

A relational database management system that stores data in columns

Widely used in-process key-value store

DBMS for structured and unstructured content wrapped with an application server

Primary database model

Relational DBMS

Key-value store

supports sorted and unsorted key sets
Native XML DBMS

in the Oracle Berkeley DB XML version

Native XML DBMS
Search engine

Secondary database models

Document store
Graph DBMS
Spatial DBMS

Document store
Spatial DBMS

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

Score	824.29
Rank	#3	Overall
	#3	Relational DBMS

Score	1.72
Rank	#145	Overall
	#67	Relational DBMS

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

Score	0.00
Rank	#383	Overall
	#7	Native XML DBMS
	#25	Search engines

Website

www.microsoft.com/en-us/sql-server

www.monetdb.org

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

www.searchxml.net/category/products

Technical documentation

learn.microsoft.com/en-US/sql/sql-server

www.monetdb.org/Documentation

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

www.searchxml.net/support/handouts

Developer

Microsoft

MonetDB BV

Oracle

originally developed by Sleepycat, which was acquired by Oracle

informationpartners gmbh

Initial release

1989

2004

1994

2015

Current release

SQL Server 2022, November 2022

Dec2023 (11.49), December 2023

18.1.40, May 2020

1.0

License

Commercial or Open Source

commercial

restricted free version is available

Open Source

Mozilla Public License 2.0

Open Source

commercial license available

commercial

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

C++

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

C++

Server operating systems

Linux
Windows

FreeBSD
Linux
OS X
Solaris
Windows

AIX
Android
FreeBSD
iOS
Linux
OS X
Solaris
VxWorks
Windows

Windows

Data scheme

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

yes

Secondary indexes

yes

SQL

Support of SQL

yes

SQL 2003 with some extensions

yes

SQL interfaced based on SQLite is available

APIs and other access methods

ADO.NET
JDBC
ODBC
OLE DB
Tabular Data Stream (TDS)

JDBC
native C library

MAPI library (MonetDB application programming interface)
ODBC

RESTful HTTP API
WebDAV
XQuery
XSLT

Supported programming languages

C#
C++
Delphi
Go
Java
JavaScript (Node.js)
PHP
Python
R
Ruby
Visual Basic

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

C++

most other programming languages supported via APIs

Server-side scripts

Stored procedures

Transact SQL, .NET languages, R, Python and (with SQL Server 2019) Java

yes, in SQL, C, R

yes

on the application server

Triggers

yes

only for the SQL API

Partitioning methods

Methods for storing different data on different nodes

tables can be distributed across several files (horizontal partitioning); sharding through federation

Sharding via remote tables

none

Replication methods

Methods for redundantly storing data on multiple nodes

yes, but depending on the SQL-Server Edition

none

Source-replica replication available in experimental status

Source-replica replication

yes

sychronisation to multiple collections

MapReduce

Offers an API for user-defined Map/Reduce methods

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

multiple readers, single writer

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

User concepts

Access control

fine grained access rights according to SQL-standard

Domain, group and role-based access control at the document level and for application services

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