DBMS > GeoMesa vs. Graph Engine vs. mSQL vs. OrientDB

System Properties Comparison GeoMesa vs. Graph Engine vs. mSQL vs. OrientDB

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Editorial information provided by DB-Engines

Name

Description

GeoMesa is a distributed spatio-temporal DBMS based on various systems as storage layer.

A distributed in-memory data processing engine, underpinned by a strongly-typed RAM store and a general distributed computation engine

mSQL (Mini SQL) is a simple and lightweight RDBMS

Multi-model DBMS (Document, Graph, Key/Value)

Primary database model

Spatial DBMS

Graph DBMS
Key-value store

Relational DBMS

Document store
Graph DBMS
Key-value store

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

Score	0.86
Rank	#205	Overall
	#4	Spatial DBMS

Score	0.67
Rank	#232	Overall
	#21	Graph DBMS
	#34	Key-value stores

Score	1.27
Rank	#169	Overall
	#76	Relational DBMS

Score	3.25
Rank	#89	Overall
	#16	Document stores
	#6	Graph DBMS
	#13	Key-value stores

Website

www.geomesa.org

www.graphengine.io

hughestech.com.au/products/msql

orientdb.org

Technical documentation

www.geomesa.org/documentation/stable/user/index.html

www.graphengine.io/docs/manual

www.orientdb.com/docs/last/index.html

Developer

CCRi and others

Microsoft

Hughes Technologies

OrientDB LTD; CallidusCloud; SAP

Initial release

2014

2010

1994

2010

Current release

5.0.0, May 2024

4.4, October 2021

3.2.29, March 2024

License

Commercial or Open Source

Open Source

Apache License 2.0

Open Source

MIT License

commercial

free licenses can be provided

Open Source

Apache version 2

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

Scala

.NET and C

Java

Server operating systems

.NET

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

All OS with a Java JDK (>= JDK 6)

Data scheme

yes

schema-free

Schema can be enforced for whole record ("schema-full") or for some fields only ("schema-hybrid")

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.

Secondary indexes

yes

SQL

Support of SQL

A subset of ANSI SQL is implemented

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

SQL-like query language, no joins

APIs and other access methods

RESTful HTTP API

JDBC
ODBC

Tinkerpop technology stack with Blueprints, Gremlin, Pipes
Java API
RESTful HTTP/JSON API

Supported programming languages

C#
C++
F#
Visual Basic

C
C++
Delphi
Java
Perl
PHP
Tcl

.Net
C
C#
C++
Clojure
Java
JavaScript
JavaScript (Node.js)
PHP
Python
Ruby
Scala

Server-side scripts

Stored procedures

yes

Java, Javascript

Triggers

Hooks

Partitioning methods

Methods for storing different data on different nodes

depending on storage layer

horizontal partitioning

none

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

depending on storage layer

none

Multi-source replication

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

could be achieved with distributed queries

Consistency concepts

Methods to ensure consistency in a distributed system

depending on storage layer

none

Foreign keys

Referential integrity

yes

relationship in graphs

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

optional: either by committing a write-ahead log (WAL) to the local persistent storage or by dumping the memory to a persistent storage

yes

In-memory capabilities

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

depending on storage layer

yes

User concepts

Access control

yes

depending on the DBMS used for storage

Access rights for users and roles; record level security configurable

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More resources

DB-Engines blog posts

Spatial database management systems
6 April 2021, Matthias Gelbmann

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Graph DBMS increased their popularity by 500% within the last 2 years
3 March 2015, Paul Andlinger

Graph DBMSs are gaining in popularity faster than any other database category
21 January 2014, Matthias Gelbmann

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Recent citations in the news

Trinity
30 October 2010, Microsoft

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13 February 2017, InfoWorld

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21 January 2022, Open Source For You

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20 September 2019, Towards Data Science

ArangoDB raises $10 million for NoSQL database management
14 March 2019, VentureBeat

The 12 Best Graph Databases to Consider for 2024
22 October 2023, Solutions Review

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14 August 2013, iProgrammer

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