DBMS > Cubrid vs. Lovefield vs. Quasardb vs. STSdb

System Properties Comparison Cubrid vs. Lovefield vs. Quasardb vs. STSdb

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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

Embeddable relational database for web apps written in pure JavaScript

Distributed, high-performance timeseries database

Key-Value Store with special method for indexing

optimized for high performance using a special indexing method

Primary database model

Relational DBMS

Time Series 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	0.33
Rank	#286	Overall
	#131	Relational DBMS

Score	0.21
Rank	#322	Overall
	#29	Time Series DBMS

Score	0.10
Rank	#357	Overall
	#51	Key-value stores

Website

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

google.github.io/lovefield

quasar.ai

github.com/STSSoft/STSdb4

Technical documentation

cubrid.org/manuals

github.com/google/lovefield/blob/master/docs/spec_index.md

doc.quasar.ai/master

Developer

CUBRID Corporation, CUBRID Foundation

Google

quasardb

STS Soft SC

Initial release

2008

2014

2009

2011

Current release

11.0, January 2021

2.1.12, February 2017

3.14.1, January 2024

4.0.8, September 2015

License

Commercial or Open Source

Open Source

Apache Version 2.0

Open Source

Apache 2.0

commercial

Free community edition, Non-profit organizations and non-commercial usage are eligible for free licenses

Open Source

GPLv2, commercial license available

Cloud-based only

Only available as a cloud service

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++

Server operating systems

Linux
Windows

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

tested with Chrome, Firefox, IE, Safari

BSD
Linux
OS X
Windows

Windows

Data scheme

yes

schema-free

yes

Typing

predefined data types such as float or date

yes

integer and binary

yes

primitive types and user defined types (classes)

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

with tags

SQL

Support of SQL

yes

SQL-like query language

via JavaScript builder pattern

SQL-like query language

APIs and other access methods

ADO.NET
JDBC
ODBC
OLE DB

HTTP API

.NET Client API

Supported programming languages

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

JavaScript

.Net
C
C#
C++
Go
Java
JavaScript (Node.js)
PHP
Python
R

C#
Java

Server-side scripts

Stored procedures

Java Stored Procedures

Triggers

yes

Using read-only observers

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

consistent hashing

none

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

none

Source-replica replication with selectable replication factor

none

MapReduce

Offers an API for user-defined Map/Reduce methods

with Hadoop integration

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate 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

yes

yes, by using IndexedDB or the cloud service Firebase Realtime Database

yes

by using LevelDB

yes

In-memory capabilities

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

yes

using MemoryDB

yes

Transient mode

User concepts

Access control

fine grained access rights according to SQL-standard

Cryptographically strong user authentication and audit trail

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