DBMS > Cubrid vs. Google BigQuery vs. jBASE vs. SQL.JS vs. SQream DB

System Properties Comparison Cubrid vs. Google BigQuery vs. jBASE vs. SQL.JS vs. SQream DB

Editorial information provided by DB-Engines

Name

Description

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

Large scale data warehouse service with append-only tables

A robust multi-value DBMS comprising development tools and middleware

Port of SQLite to JavaScript

a GPU-based, columnar RDBMS for big data analytics workloads

Primary database model

Relational DBMS

Multivalue DBMS

Relational DBMS

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

Score	1.20
Rank	#169	Overall
	#78	Relational DBMS

Score	60.38
Rank	#19	Overall
	#13	Relational DBMS

Score	1.41
Rank	#159	Overall
	#3	Multivalue DBMS

Score	0.53
Rank	#252	Overall
	#116	Relational DBMS

Score	0.70
Rank	#227	Overall
	#104	Relational DBMS

Website

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

cloud.google.com/bigquery

www.rocketsoftware.com/products/rocket-multivalue-application-development-platform/rocket-jbase

sql.js.org

sqream.com

Technical documentation

cubrid.org/manuals

cloud.google.com/bigquery/docs

docs.rocketsoftware.com/bundle?labelkey=jbase_5.9

sql.js.org/documentation/index.html

docs.sqream.com

Developer

CUBRID Corporation, CUBRID Foundation

Google

Rocket Software (formerly Zumasys)

Alon Zakai

enhancements implemented by others

SQream Technologies

Initial release

2008

2010

1991

2012

2017

Current release

11.0, January 2021

5.7

2022.1.6, December 2022

License

Commercial or Open Source

Open Source

Apache Version 2.0

commercial

Open Source

commercial

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

Providers of DBaaS offerings, please contact us to be listed.

Implementation language

C, C++, Java

JavaScript

C++, CUDA, Haskell, Java, Scala

Server operating systems

Linux
Windows

hosted

AIX
Linux
Windows

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

Linux

Data scheme

yes

schema-free

yes

Typing

predefined data types such as float or date

yes

optional

yes

yes, ANSI Standard SQL Types

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

yes

Embedded SQL for jBASE in BASIC

yes

SQL-92 is not fully supported

yes

APIs and other access methods

ADO.NET
JDBC
ODBC
OLE DB

RESTful HTTP/JSON API

JDBC
ODBC
Proprietary protocol
RESTful HTTP API
SOAP-based API

JavaScript API

.Net
JDBC
ODBC

Supported programming languages

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

.Net
Java
JavaScript
Objective-C
PHP
Python
Ruby

.Net
Basic
Jabbascript
Java

JavaScript

C++
Java
JavaScript (Node.js)
Python

Server-side scripts

Stored procedures

Java Stored Procedures

user defined functions

in JavaScript

yes

user defined functions in Python

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

none

horizontal and vertical partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

yes

none

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

none

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

Since BigQuery is designed for querying 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

Access privileges (owner, writer, reader) on dataset, table or view level

Google Cloud Identity & Access Management (IAM)

Access rights can be defined down to the item level

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