DBMS > Cubrid vs. Spark SQL vs. SQL.JS vs. TerarkDB

System Properties Comparison Cubrid vs. Spark SQL vs. SQL.JS vs. TerarkDB

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Editorial information provided by DB-Engines

Name

Description

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

Spark SQL is a component on top of 'Spark Core' for structured data processing

Port of SQLite to JavaScript

A key-value store forked from RocksDB with advanced compression algorithms. It can be used standalone or as a storage engine for MySQL and MongoDB

Primary database model

Relational DBMS

Key-value store

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

Score	1.04
Rank	#187	Overall
	#87	Relational DBMS

Score	18.04
Rank	#33	Overall
	#20	Relational DBMS

Score	0.63
Rank	#241	Overall
	#112	Relational DBMS

Score	0.08
Rank	#367	Overall
	#56	Key-value stores

Website

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

spark.apache.org/sql

sql.js.org

github.com/bytedance/terarkdb

Technical documentation

cubrid.org/manuals

spark.apache.org/docs/latest/sql-programming-guide.html

sql.js.org/documentation/index.html

bytedance.larkoffice.com/docs/doccnZmYFqHBm06BbvYgjsHHcKc

Developer

CUBRID Corporation, CUBRID Foundation

Apache Software Foundation

Alon Zakai

enhancements implemented by others

ByteDance, originally Terark

Initial release

2008

2014

2012

2016

Current release

11.0, January 2021

3.5.0 ( 2.13), September 2023

License

Commercial or Open Source

Open Source

Apache Version 2.0

Open Source

Apache 2.0

Open Source

commercial

restricted open source version available

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

Scala

JavaScript

C++

Server operating systems

Linux
Windows

Linux
OS X
Windows

server-less, requires a JavaScript environment (browser, Node.js)

Data scheme

yes

schema-free

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

yes

SQL-like DML and DDL statements

yes

SQL-92 is not fully supported

APIs and other access methods

ADO.NET
JDBC
ODBC
OLE DB

JDBC
ODBC

JavaScript API

C++ API
Java API

Supported programming languages

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

Java
Python
R
Scala

JavaScript

C++
Java

Server-side scripts

Stored procedures

Java Stored Procedures

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

none

yes, utilizing Spark Core

none

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

none

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

none

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

yes

except by serializing a db to a file

yes

In-memory capabilities

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

yes

User concepts

Access control

fine grained access rights according to SQL-standard

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More resources

DB-Engines blog posts

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