DBMS > Derby vs. MarkLogic vs. MySQL vs. Sadas Engine vs. VoltDB

System Properties Comparison Derby vs. MarkLogic vs. MySQL vs. Sadas Engine vs. VoltDB

Editorial information provided by DB-Engines

Name

Description

Full-featured RDBMS with a small footprint, either embedded into a Java application or used as a database server.

Operational and transactional Enterprise NoSQL database

Widely used open source RDBMS

SADAS Engine is a columnar DBMS specifically designed for high performance in data warehouse environments

Distributed In-Memory NewSQL RDBMS

Used for OLTP applications with a high frequency of relatively simple transactions, that can hold all their data in memory

Primary database model

Relational DBMS

Document store
Native XML DBMS
RDF store

as of version 7
Search engine

Relational DBMS

Key/Value like access via memcached API

Relational DBMS

Secondary database models

Document store
Spatial DBMS

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

Score	4.71
Rank	#69	Overall
	#37	Relational DBMS

Score	5.92
Rank	#58	Overall
	#10	Document stores
	#1	Native XML DBMS
	#1	RDF stores
	#6	Search engines

Score	1083.74
Rank	#2	Overall
	#2	Relational DBMS

Score	0.00
Rank	#383	Overall
	#158	Relational DBMS

Score	1.44
Rank	#158	Overall
	#73	Relational DBMS

Website

Technical documentation

db.apache.org/derby/manuals/index.html

docs.marklogic.com

dev.mysql.com/doc

www.sadasengine.com/en/sadas-engine-download-free-trial-and-documentation/#documentation

docs.voltdb.com

Developer

Apache Software Foundation

MarkLogic Corp.

Oracle

since 2010, originally MySQL AB, then Sun

SADAS s.r.l.

VoltDB Inc.

Initial release

1997

2001

1995

2006

2010

Current release

10.17.1.0, November 2023

11.0, December 2022

8.4.0, April 2024

8.0

11.3, April 2022

License

Commercial or Open Source

Open Source

Apache version 2

commercial

restricted free version is available

Open Source

GPL version 2. Commercial licenses with extended functionallity are available

commercial

free trial version available

Open Source

AGPL for Community Edition, commercial license for Enterprise, AWS, and Pro Editions

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

Java

C++

C and C++

C++

Java, C++

Server operating systems

All OS with a Java VM

Linux
OS X
Windows

FreeBSD
Linux
OS X
Solaris
Windows

AIX
Linux
Windows

Linux
OS X

for development

Data scheme

yes

schema-free

Schema can be enforced

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

Secondary indexes

yes

SQL

Support of SQL

yes

SQL92

yes

with proprietary extensions

yes

only a subset of SQL 99

APIs and other access methods

JDBC

Java API
Node.js Client API
ODBC
proprietary Optic API

Proprietary Query API, introduced with version 9
RESTful HTTP API
SPARQL
WebDAV
XDBC
XQuery
XSLT

ADO.NET
JDBC
ODBC
Proprietary native API

JDBC
ODBC
Proprietary protocol

Java API
JDBC
RESTful HTTP/JSON API

Supported programming languages

Java

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

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

.Net
C
C#
C++
Groovy
Java
PHP
Python

C#
C++
Erlang

not officially supported
Go
Java
JavaScript

Node.js
PHP
Python

Server-side scripts

Stored procedures

Java Stored Procedures

yes

via XQuery or JavaScript

yes

proprietary syntax

Java

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

horizontal partitioning, sharding with MySQL Cluster or MySQL Fabric

horizontal partitioning

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

yes

Multi-source replication
Source-replica replication

none

Multi-source replication
Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

via Hadoop Connector, HDFS Direct Access and in-database MapReduce jobs

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Foreign keys

Referential integrity

yes

not for MyISAM storage engine

yes

FOREIGN KEY constraints are not supported

Transaction concepts

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

ACID

can act as a resource manager in an XA/JTA transaction

ACID

not for MyISAM storage engine

ACID

Transactions are executed single-threaded within stored procedures

Concurrency

Support for concurrent manipulation of data

yes

table locks or row locks depending on storage engine

yes

Data access is serialized by the server

Durability

Support for making data persistent

yes

Snapshots and command logging

In-memory capabilities

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

yes

yes, with Range Indexes

yes

managed by 'Learn by Usage'

User concepts

Access control

fine grained access rights according to SQL-standard

Role-based access control at the document and subdocument levels

Users with fine-grained authorization concept

no user groups or roles

Access rights for users, groups and roles according to SQL-standard

Users and roles with access to stored procedures

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