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

System Properties Comparison Apache Drill vs. Cubrid vs. DolphinDB 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

DolphinDB is a high performance Time Series DBMS. It is integrated with an easy-to-use fully featured programming language and a high-volume high-velocity streaming analytics system. It offers operational simplicity, scalability, fault tolerance, and concurrency.

Spatial extension of PostgreSQL

Primary database model

Document store
Relational DBMS

Relational DBMS

Time Series DBMS

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	4.13
Rank	#80	Overall
	#6	Time Series DBMS

Score	22.69
Rank	#29	Overall
	#1	Spatial DBMS

Website

drill.apache.org

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

www.dolphindb.com

postgis.net

Technical documentation

drill.apache.org/docs

cubrid.org/manuals

docs.dolphindb.cn/en/help200/index.html

postgis.net/documentation

Developer

Apache Software Foundation

CUBRID Corporation, CUBRID Foundation

DolphinDB, Inc

Initial release

2012

2008

2018

2005

Current release

1.20.3, January 2023

11.0, January 2021

v2.00.4, January 2022

3.4.2, February 2024

License

Commercial or Open Source

Open Source

Apache Version 2

Open Source

Apache Version 2.0

commercial

free community version available

Open Source

GPL v2.0

Cloud-based only

Only available as a cloud service

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Database as a Service

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Implementation language

C, C++, Java

C++

Server operating systems

Linux
OS X
Windows

Linux
Windows

Data scheme

schema-free

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

yes

APIs and other access methods

JDBC
ODBC
RESTful HTTP API

ADO.NET
JDBC
ODBC
OLE DB

JDBC
JSON over HTTP
Kafka
MQTT (Message Queue Telemetry Transport)
ODBC
OPC DA
OPC UA
RabbitMQ
WebSocket

Supported programming languages

C++

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

C#
C++
Go
Java
JavaScript
MatLab
Python
R
Rust

Server-side scripts

Stored procedures

user defined functions

Java Stored Procedures

yes

user defined functions

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

horizontal partitioning

yes

based on PostgreSQL

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

yes

based on PostgreSQL

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

none

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

yes

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

yes

User concepts

Access control

Depending on the underlying data source

fine grained access rights according to SQL-standard

Administrators, Users, Groups

yes

based on PostgreSQL

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More resources

DB-Engines blog posts

Spatial database management systems
6 April 2021, Matthias Gelbmann

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Recent citations in the news

Apache Drill case study: A tutorial on processing CSV files
9 June 2016, TheServerSide.com

Analyse Kafka messages with SQL queries using Apache Drill
23 September 2019, Towards Data Science

Apache Drill Poised to Crack Tough Data Challenges
19 May 2015, Datanami

Apache Drill Eliminates ETL, Data Transformation for MapR Database
11 April 2016, The New Stack

Drill Mines Diverse Data Sets, Google Style
20 May 2015, The Next Platform

provided by Google News

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