DBMS > Apache Drill vs. HugeGraph vs. MonetDB vs. OrientDB vs. SQLite

System Properties Comparison Apache Drill vs. HugeGraph vs. MonetDB vs. OrientDB vs. SQLite

Editorial information provided by DB-Engines

Name

Description

Schema-free SQL Query Engine for Hadoop, NoSQL and Cloud Storage

A fast-speed and highly-scalable Graph DBMS

A relational database management system that stores data in columns

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

Widely used embeddable, in-process RDBMS

Primary database model

Document store
Relational DBMS

Graph DBMS

Relational DBMS

Document store
Graph DBMS
Key-value store

Relational DBMS

Secondary database models

Document store
Spatial DBMS

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

Score	1.95
Rank	#127	Overall
	#23	Document stores
	#60	Relational DBMS

Score	0.13
Rank	#336	Overall
	#32	Graph DBMS

Score	1.72
Rank	#145	Overall
	#67	Relational DBMS

Score	3.19
Rank	#93	Overall
	#16	Document stores
	#7	Graph DBMS
	#14	Key-value stores

Score	114.32
Rank	#10	Overall
	#7	Relational DBMS

Website

drill.apache.org

github.com/hugegraph
hugegraph.apache.org

www.monetdb.org

orientdb.org

www.sqlite.org

Technical documentation

drill.apache.org/docs

hugegraph.apache.org/docs

www.monetdb.org/Documentation

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

www.sqlite.org/docs.html

Developer

Apache Software Foundation

Baidu

MonetDB BV

OrientDB LTD; CallidusCloud; SAP

Dwayne Richard Hipp

Initial release

2012

2018

2004

2010

2000

Current release

1.20.3, January 2023

0.9

Dec2023 (11.49), December 2023

3.2.29, March 2024

3.45.3 (15 April 2024), April 2024

License

Commercial or Open Source

Open Source

Apache Version 2

Open Source

Apache Version 2.0

Open Source

Mozilla Public License 2.0

Open Source

Apache version 2

Open Source

Public Domain

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

Java

Server operating systems

Linux
OS X
Windows

Linux
macOS
Unix

FreeBSD
Linux
OS X
Solaris
Windows

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

server-less

Data scheme

schema-free

yes

schema-free

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

yes

dynamic column types

Typing

predefined data types such as float or date

yes

not rigid because of 'dynamic typing' concept.

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

also supports composite index and range index

yes

SQL

Support of SQL

SQL SELECT statement is SQL:2003 compliant

yes

SQL 2003 with some extensions

SQL-like query language, no joins

yes

SQL-92 is not fully supported

APIs and other access methods

JDBC
ODBC
RESTful HTTP API

Java API
RESTful HTTP API
TinkerPop Gremlin

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

Supported programming languages

C++

Groovy
Java
Python

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

Server-side scripts

Stored procedures

user defined functions

asynchronous Gremlin script jobs

yes, in SQL, C, R

Java, Javascript

Triggers

yes

Hooks

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

yes

depending on used storage backend, e.g. Cassandra and HBase

Sharding via remote tables

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

yes

depending on used storage backend, e.g. Cassandra and HBase

none

Source-replica replication available in experimental status

Multi-source replication

none

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

via hugegraph-spark

could be achieved with distributed queries

Consistency concepts

Methods to ensure consistency in a distributed system

none

Eventual Consistency

Foreign keys

Referential integrity

yes

edges in graph

yes

relationship in graphs

yes

Transaction concepts

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

ACID

Concurrency

Support for concurrent manipulation of data

yes

via file-system locks

Durability

Support for making data persistent

Depending on the underlying data source

yes

In-memory capabilities

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

Depending on the underlying data source

yes

User concepts

Access control

Depending on the underlying data source

Users, roles and permissions

fine grained access rights according to SQL-standard

Access rights for users and roles; record level security configurable

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