DBMS > EsgynDB vs. MonetDB vs. OrientDB vs. SQLite vs. Tarantool

System Properties Comparison EsgynDB vs. MonetDB vs. OrientDB vs. SQLite vs. Tarantool

Editorial information provided by DB-Engines

Name

Description

Enterprise-class SQL-on-Hadoop solution, powered by Apache Trafodion

A relational database management system that stores data in columns

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

Widely used embeddable, in-process RDBMS

In-memory computing platform with a flexible data schema for efficiently building high-performance applications

Primary database model

Relational DBMS

Document store
Graph DBMS
Key-value store

Relational DBMS

Key-value store

Secondary database models

Document store
Spatial DBMS

Document store
Relational DBMS
Spatial DBMS

with Tarantool/GIS extension

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

Score	0.19
Rank	#292	Overall
	#137	Relational DBMS

Score	1.79
Rank	#129	Overall
	#63	Relational DBMS

Score	5.21
Rank	#78	Overall
	#15	Document stores
	#5	Graph DBMS
	#12	Key-value stores

Score	138.87
Rank	#10	Overall
	#7	Relational DBMS

Score	1.53
Rank	#144	Overall
	#27	Key-value stores

Website

Technical documentation

www.monetdb.org/Documentation

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

www.sqlite.org/docs.html

www.tarantool.io/en/doc

Developer

Esgyn

MonetDB BV

OrientDB LTD; CallidusCloud; SAP

Dwayne Richard Hipp

Initial release

2015

2004

2010

2000

2008

Current release

Jul2021-SP2, July 2021

3.1.9, February 2021

3.39.1 (13 July 2022), July 2022

2.4.2, July 2020

License

Commercial or Open Source

commercial

Open Source

Mozilla Public License 2.0

Open Source

Apache version 2

Open Source

Public Domain

Open Source

BSD

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++, Java

Java

C and C++

Server operating systems

Linux

FreeBSD
Linux
OS X
Solaris
Windows

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

server-less

BSD
Linux
macOS

Data scheme

yes

schema-free

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

yes

dynamic column types

schema-free, schema definition possible

Typing

predefined data types such as float or date

yes

not rigid because of 'dynamic typing' concept.

string, double, decimal, uuid, integer, blob, boolean

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

yes

SQL 2003 with some extensions

SQL-like query language, no joins

yes

SQL-92 is not fully supported

Full-featured ANSI SQL support

APIs and other access methods

ADO.NET
JDBC
ODBC

JDBC
native C library

MAPI library (MonetDB application programming interface)
ODBC

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

ADO.NET

inofficial driver
JDBC

inofficial driver
ODBC

inofficial driver

Open binary protocol

Supported programming languages

All languages supporting JDBC/ODBC/ADO.Net

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

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

Actionscript
Ada
Basic
C
C#
C++
D
Delphi
Forth
Fortran
Haskell
Java
JavaScript
Lisp
Lua
MatLab
Objective-C
OCaml
Perl
PHP
PL/SQL
Python
R
Ruby
Scala
Scheme
Smalltalk
Tcl

C
C#
C++
Erlang
Go
Java
JavaScript
Lua
Perl
PHP
Python
Rust

Server-side scripts

Stored procedures

Java Stored Procedures

yes, in SQL, C, R

Java, Javascript

Lua, C and SQL stored procedures

Triggers

yes

Hooks

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

Sharding via remote tables

Sharding

none

Hash sharding based on virtual buckets

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication between multi datacenters

none

Source-replica replication available in experimental status

Multi-source replication

none

Multi-source replication
Source-replica 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

Immediate Consistency

Foreign keys

Referential integrity

yes

relationship in graphs

yes

yes, with SQL

Transaction concepts

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

ACID

ACID, read commited

Concurrency

Support for concurrent manipulation of data

yes

via file-system locks

yes, cooperative multitasking

Durability

Support for making data persistent

yes

yes, regular snapshots on disk, write ahead logging

In-memory capabilities

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

yes

yes, full featured in-memory storage engine with persistence

User concepts

Access control

fine grained access rights according to SQL-standard

Access rights for users and roles; record level security configurable

Access rights for users and roles

More information provided by the system vendor

Specific characteristics

Column-store In-memory optimized GeoSpatial support JSON document support
» more

Competitive advantages

Scalable architecture - vertical data organization and in-memory optimization guarantee...
» more

Typical application scenarios

Analytical database, Data warehouse, OLAP Data mining Scientific database
» more

Key customers

Numascale , Spinque , SecurActive , CHS , NOZHUP
» more

Licensing and pricing models

Free and open-source software, Mozilla Public License 2.0 Commercial support available
» more

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