DBMS > Geode vs. IBM Db2 Event Store vs. MarkLogic vs. mSQL vs. MySQL

System Properties Comparison Geode vs. IBM Db2 Event Store vs. MarkLogic vs. mSQL vs. MySQL

Editorial information provided by DB-Engines

Name

Description

Geode is a distributed data container, pooling memory, CPU, network resources, and optionally local disk across multiple processes

Distributed Event Store optimized for Internet of Things use cases

Operational and transactional Enterprise NoSQL database

mSQL (Mini SQL) is a simple and lightweight RDBMS

Widely used open source RDBMS

Primary database model

Key-value store

Event Store
Time Series DBMS

Document store
Native XML DBMS
RDF store

as of version 7
Search engine

Relational DBMS

Key/Value like access via memcached API

Secondary database models

Document store
Spatial DBMS

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

Score	1.92
Rank	#131	Overall
	#23	Key-value stores

Score	0.19
Rank	#323	Overall
	#2	Event Stores
	#28	Time Series DBMS

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

Score	1.27
Rank	#167	Overall
	#77	Relational DBMS

Score	1083.74
Rank	#2	Overall
	#2	Relational DBMS

Website

geode.apache.org

www.ibm.com/products/db2-event-store

www.marklogic.com

hughestech.com.au/products/msql

www.mysql.com

Technical documentation

geode.apache.org/docs

www.ibm.com/docs/en/db2-event-store

docs.marklogic.com

dev.mysql.com/doc

Developer

Originally developed by Gemstone. They outsourced the project to Apache in 2015 but still deliver a commercial version as Gemfire.

IBM

MarkLogic Corp.

Hughes Technologies

Oracle

since 2010, originally MySQL AB, then Sun

Initial release

2002

2017

2001

1994

1995

Current release

1.1, February 2017

2.0

11.0, December 2022

4.4, October 2021

8.4.0, April 2024

License

Commercial or Open Source

Open Source

Apache Version 2; commercial licenses available as Gemfire

commercial

free developer edition available

commercial

restricted free version is available

commercial

free licenses can be provided

Open Source

GPL version 2. Commercial licenses with extended functionallity are available

Cloud-based only

Only available as a cloud service

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Implementation language

Java

C and C++

C++

C and C++

Server operating systems

All OS with a Java VM

the JDK (8 or later) is also required

Linux

Linux, macOS, Windows for the developer addition

Linux
OS X
Windows

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

FreeBSD
Linux
OS X
Solaris
Windows

Data scheme

schema-free

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

SQL-like query language (OQL)

yes

through the embedded Spark runtime

yes

SQL92

A subset of ANSI SQL is implemented

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

yes

with proprietary extensions

APIs and other access methods

Java Client API
Memcached protocol
RESTful HTTP API

ADO.NET
DB2 Connect
JDBC
ODBC
RESTful HTTP API

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

JDBC
ODBC

ADO.NET
JDBC
ODBC
Proprietary native API

Supported programming languages

.Net
All JVM based languages
C++
Groovy
Java
Scala

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

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

C
C++
Delphi
Java
Perl
PHP
Tcl

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

Server-side scripts

Stored procedures

user defined functions

yes

via XQuery or JavaScript

yes

proprietary syntax

Triggers

yes

Cache Event Listeners

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

horizontal partitioning, sharding with MySQL Cluster or MySQL Fabric

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication

Active-active shard replication

yes

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

Eventual Consistency

Immediate Consistency

none

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

yes, on a single node

ACID

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

ACID

not for MyISAM storage engine

Concurrency

Support for concurrent manipulation of data

yes

No - written data is immutable

yes

table locks or row locks depending on storage engine

Durability

Support for making data persistent

yes

Yes - Synchronous writes to local disk combined with replication and asynchronous writes in parquet format to permanent shared storage

yes

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

User concepts

Access control

Access rights per client and object definable

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

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