DBMS > Apache Drill vs. Cubrid vs. Dolt vs. JaguarDB

System Properties Comparison Apache Drill vs. Cubrid vs. Dolt vs. JaguarDB

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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

A MySQL compatible DBMS with Git-like versioning of data and schema

Performant, highly scalable DBMS for AI and IoT applications

Primary database model

Document store
Relational DBMS

Relational DBMS

Key-value store
Vector DBMS

Secondary database models

Document store

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	0.96
Rank	#193	Overall
	#90	Relational DBMS

Score	0.00
Rank	#383	Overall
	#60	Key-value stores
	#13	Vector DBMS

Website

drill.apache.org

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

github.com/dolthub/dolt
www.dolthub.com

www.jaguardb.com

Technical documentation

drill.apache.org/docs

cubrid.org/manuals

docs.dolthub.com

www.jaguardb.com/support.html

Developer

Apache Software Foundation

CUBRID Corporation, CUBRID Foundation

DoltHub Inc

DataJaguar, Inc.

Initial release

2012

2008

2018

2015

Current release

1.20.3, January 2023

11.0, January 2021

3.3 July 2023

License

Commercial or Open Source

Open Source

Apache Version 2

Open Source

Apache Version 2.0

Open Source

Apache Version 2.0

Open Source

GPL V3.0

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

C++

the server part. Clients available in other languages

Server operating systems

Linux
OS X
Windows

Linux
Windows

Linux
macOS
Windows

Linux

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.

Secondary indexes

yes

SQL

Support of SQL

SQL SELECT statement is SQL:2003 compliant

yes

A subset of ANSI SQL is implemented

but no views, foreign keys, triggers

APIs and other access methods

JDBC
ODBC
RESTful HTTP API

ADO.NET
JDBC
ODBC
OLE DB

CLI Client
HTTP REST

JDBC
ODBC

Supported programming languages

C++

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

Ada
C
C#
C++
D
Delphi
Eiffel
Erlang
Haskell
Java
JavaScript (Node.js)
Objective-C
OCaml
Perl
PHP
Python
Ruby
Scheme
Tcl

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

Server-side scripts

Stored procedures

user defined functions

Java Stored Procedures

yes

currently in alpha release

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

A database can be cloned to multiple locations and be used there in isolation. Data/schema changes can be pushed/pulled explicitly between locations.

Multi-source replication

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

none

Immediate Consistency

Eventual Consistency

Foreign keys

Referential integrity

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

Only one user is configurable, and must be specified in the config file at startup

rights management via user accounts

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More resources

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 improves big data SQL query engine
31 August 2021, TechTarget

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

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

provided by Google News

Dolt- A Version Controlled Database
29 January 2024, iProgrammer

Top Data Version Control Tools for Machine Learning Research in 2023
24 July 2023, MarkTechPost

Dolt, a Relational Database with Git-Like Cloning Features
19 August 2020, The New Stack

Data Versioning at Scale: Chaos and Chaos Management
10 February 2023, InfoQ.com

Radar Trends to Watch: July 2022 – O'Reilly
5 July 2022, O'Reilly Media

provided by Google News

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