DBMS > Apache Drill vs. Cubrid vs. OrientDB vs. PostGIS

System Properties Comparison Apache Drill vs. Cubrid vs. OrientDB vs. PostGIS

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Editorial information provided by DB-Engines

Name

Description

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

CUBRID is an open-source SQL-based relational database management system with object extensions for OLTP

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

Spatial extension of PostgreSQL

Primary database model

Document store
Relational DBMS

Relational DBMS

Document store
Graph DBMS
Key-value store

Spatial DBMS

Secondary database models

Relational 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	1.20
Rank	#169	Overall
	#78	Relational DBMS

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

Score	22.69
Rank	#29	Overall
	#1	Spatial DBMS

Website

drill.apache.org

cubrid.com (korean)
cubrid.org (english)

orientdb.org

postgis.net

Technical documentation

drill.apache.org/docs

cubrid.org/manuals

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

postgis.net/documentation

Developer

Apache Software Foundation

CUBRID Corporation, CUBRID Foundation

OrientDB LTD; CallidusCloud; SAP

Initial release

2012

2008

2010

2005

Current release

1.20.3, January 2023

11.0, January 2021

3.2.29, March 2024

3.4.2, February 2024

License

Commercial or Open Source

Open Source

Apache Version 2

Open Source

Apache Version 2.0

Open Source

Apache version 2

Open Source

GPL v2.0

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

C, C++, Java

Java

Server operating systems

Linux
OS X
Windows

Linux
Windows

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

Data scheme

schema-free

yes

schema-free

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

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 SELECT statement is SQL:2003 compliant

yes

SQL-like query language, no joins

yes

APIs and other access methods

JDBC
ODBC
RESTful HTTP API

ADO.NET
JDBC
ODBC
OLE DB

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

Supported programming languages

C++

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

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

Server-side scripts

Stored procedures

user defined functions

Java Stored Procedures

Java, Javascript

user defined functions

Triggers

yes

Hooks

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

Sharding

yes

based on PostgreSQL

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

Multi-source replication

yes

based on PostgreSQL

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

none

Immediate Consistency

Foreign keys

Referential integrity

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

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

User concepts

Access control

Depending on the underlying data source

fine grained access rights according to SQL-standard

Access rights for users and roles; record level security configurable

yes

based on PostgreSQL

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More resources

DB-Engines blog posts

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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Spatial database management systems
6 April 2021, Matthias Gelbmann

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