DBMS > Drizzle vs. HyperSQL vs. Microsoft SQL Server vs. Oracle Berkeley DB vs. SAP SQL Anywhere

System Properties Comparison Drizzle vs. HyperSQL vs. Microsoft SQL Server vs. Oracle Berkeley DB vs. SAP SQL Anywhere

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.

Description

MySQL fork with a pluggable micro-kernel and with an emphasis of performance over compatibility.

Multithreaded, transactional RDBMS written in Java

also known as HSQLDB

Microsofts flagship relational DBMS

Widely used in-process key-value store

RDBMS database and synchronization technologies for server, desktop, remote office, and mobile environments

Primary database model

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	3.49
Rank	#87	Overall
	#47	Relational DBMS

Score	824.29
Rank	#3	Overall
	#3	Relational DBMS

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

Score	4.25
Rank	#79	Overall
	#43	Relational DBMS

Website

hsqldb.org

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

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

www.sap.com/products/technology-platform/sql-anywhere.html

Technical documentation

hsqldb.org/web/hsqlDocsFrame.html

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

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

help.sap.com/docs/SAP_SQL_Anywhere

Developer

Drizzle project, originally started by Brian Aker

Microsoft

Oracle

originally developed by Sleepycat, which was acquired by Oracle

SAP

formerly Sybase

Initial release

2008

2001

1989

1994

1992

Current release

7.2.4, September 2012

2.7.2, June 2023

SQL Server 2022, November 2022

18.1.40, May 2020

17, July 2015

License

Commercial or Open Source

Open Source

GNU GPL

Open Source

based on BSD license

commercial

restricted free version is available

Open Source

commercial license available

commercial

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

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Implementation language

C++

Java

C++

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

Server operating systems

FreeBSD
Linux
OS X

All OS with a Java VM

Embedded (into Java applications) and Client-Server operating modes

Linux
Windows

AIX
Android
FreeBSD
iOS
Linux
OS X
Solaris
VxWorks
Windows

AIX
HP-UX
Linux
OS X
Solaris
Windows

Data scheme

yes

schema-free

yes

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

with proprietary extensions

yes

SQL interfaced based on SQLite is available

yes

APIs and other access methods

JDBC

HTTP API

JDBC via HTTP
JDBC
ODBC

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

ADO.NET
HTTP API
JDBC
ODBC

Supported programming languages

C
C++
Java
PHP

All languages supporting JDBC/ODBC
Java

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

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

Server-side scripts

Stored procedures

Java, SQL

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

yes, in C/C++, Java, .Net or Perl

Triggers

hooks for callbacks inside the server can be used.

yes

only for the SQL API

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

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

none

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication
Source-replica replication

none

yes, but depending on the SQL-Server Edition

Source-replica replication

Database mirroring

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

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

Pluggable authentication mechanisms

e.g. LDAP, HTTP

fine grained access rights according to SQL-standard

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