DBMS > Bangdb vs. Geode vs. MarkLogic vs. mSQL

System Properties Comparison Bangdb vs. Geode vs. MarkLogic vs. mSQL

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Editorial information provided by DB-Engines

Name

Description

Converged and high performance database for device data, events, time series, document and graph

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

Operational and transactional Enterprise NoSQL database

mSQL (Mini SQL) is a simple and lightweight RDBMS

Primary database model

Document store
Graph DBMS
Time Series DBMS

Key-value store

Document store
Native XML DBMS
RDF store

as of version 7
Search engine

Relational DBMS

Secondary database models

Spatial DBMS

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

Score	0.08
Rank	#347	Overall
	#47	Document stores
	#34	Graph DBMS
	#31	Time Series DBMS

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

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

Website

bangdb.com

geode.apache.org

www.marklogic.com

hughestech.com.au/products/msql

Technical documentation

docs.bangdb.com

geode.apache.org/docs

docs.marklogic.com

Developer

Sachin Sinha, BangDB

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

MarkLogic Corp.

Hughes Technologies

Initial release

2012

2002

2001

1994

Current release

BangDB 2.0, October 2021

1.1, February 2017

11.0, December 2022

4.4, October 2021

License

Commercial or Open Source

Open Source

BSD 3

Open Source

Apache Version 2; commercial licenses available as Gemfire

commercial

restricted free version is available

commercial

free licenses can be provided

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

Providers of DBaaS offerings, please contact us to be listed.

Implementation language

C, C++

Java

C++

Server operating systems

Linux

All OS with a Java VM

the JDK (8 or later) is also required

Linux
OS X
Windows

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

Data scheme

schema-free

Schema can be enforced

yes

Typing

predefined data types such as float or date

yes: string, long, double, int, geospatial, stream, events

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

secondary, composite, nested, reverse, geospatial

yes

SQL

Support of SQL

SQL like support with command line tool

SQL-like query language (OQL)

yes

SQL92

A subset of ANSI SQL is implemented

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

APIs and other access methods

Proprietary protocol
RESTful HTTP API

Java Client API
Memcached protocol
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

Supported programming languages

C
C#
C++
Java
Python

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

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

C
C++
Delphi
Java
Perl
PHP
Tcl

Server-side scripts

Stored procedures

user defined functions

yes

via XQuery or JavaScript

Triggers

yes, Notifications (with Streaming only)

yes

Cache Event Listeners

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding (enterprise version only). P2P based virtual network overlay with consistent hashing and chord algorithm

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor, Knob for CAP (enterprise version only)

Multi-source replication

yes

none

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

Tunable consistency, set CAP knob accordingly

Eventual Consistency

Immediate Consistency

none

Foreign keys

Referential integrity

Transaction concepts

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

ACID

yes, on a single node

ACID

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

Concurrency

Support for concurrent manipulation of data

yes, optimistic concurrency control

yes

Durability

Support for making data persistent

yes, implements WAL (Write ahead log) as well

yes

In-memory capabilities

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

yes, run db with in-memory only mode

yes

yes, with Range Indexes

User concepts

Access control

yes (enterprise version only)

Access rights per client and object definable

Role-based access control at the document and subdocument levels

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