DBMS > LeanXcale vs. Microsoft SQL Server vs. mSQL vs. Oracle Berkeley DB vs. Oracle Rdb

System Properties Comparison LeanXcale vs. Microsoft SQL Server vs. mSQL vs. Oracle Berkeley DB vs. Oracle Rdb

Editorial information provided by DB-Engines

Name

Description

A highly scalable full ACID SQL database with fast NoSQL data ingestion and GIS capabilities

Microsofts flagship relational DBMS

mSQL (Mini SQL) is a simple and lightweight RDBMS

Widely used in-process key-value store

Primary database model

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

Relational DBMS

Secondary database models

Document store
Graph DBMS
Spatial DBMS

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

Score	0.36
Rank	#280	Overall
	#40	Key-value stores
	#129	Relational DBMS

Score	821.56
Rank	#3	Overall
	#3	Relational DBMS

Score	1.27
Rank	#169	Overall
	#76	Relational DBMS

Score	2.01
Rank	#126	Overall
	#21	Key-value stores
	#3	Native XML DBMS

Score	1.14
Rank	#178	Overall
	#80	Relational DBMS

Website

www.leanxcale.com

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

hughestech.com.au/products/msql

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

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

Technical documentation

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

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

www.oracle.com/database/technologies/related/rdb-doc.html

Developer

LeanXcale

Microsoft

Hughes Technologies

Oracle

originally developed by Sleepycat, which was acquired by Oracle

Oracle, originally developed by Digital Equipment Corporation (DEC)

Initial release

2015

1989

1994

1984

Current release

SQL Server 2022, November 2022

4.4, October 2021

18.1.40, May 2020

7.4.1.1, 2021

License

Commercial or Open Source

commercial

restricted free version is available

commercial

free licenses can be provided

Open Source

commercial license available

commercial

Cloud-based only

Only available as a cloud service

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Implementation language

C++

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

Server operating systems

Linux
Windows

AIX
HP-UX
Linux
OS X
Solaris SPARC/x86
Windows

AIX
Android
FreeBSD
iOS
Linux
OS X
Solaris
VxWorks
Windows

HP Open VMS

Data scheme

yes

schema-free

Flexible Schema (defined schema, partial schema, 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

SQL

Support of SQL

yes

through Apache Derby

yes

A subset of ANSI SQL is implemented

no subqueries, aggregate functions, views, foreign keys, triggers

yes

SQL interfaced based on SQLite is available

yes

APIs and other access methods

JDBC
Kafka Connector
ODBC
proprietary key/value interface
Spark Connector

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

JDBC
ODBC

Supported programming languages

C
Java
Scala

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

C
C++
Delphi
Java
Perl
PHP
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

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

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

none

Replication methods

Methods for redundantly storing data on multiple nodes

yes, but depending on the SQL-Server Edition

none

Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

none

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

yes, on a single node

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

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