DBMS > Cubrid vs. LeanXcale vs. LevelDB vs. Tkrzw

System Properties Comparison Cubrid vs. LeanXcale vs. LevelDB vs. Tkrzw

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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

A highly scalable full ACID SQL database with fast NoSQL data ingestion and GIS capabilities

Embeddable fast key-value storage library that provides an ordered mapping from string keys to string values

A concept of libraries, allowing an application program to store and query key-value pairs in a file. Successor of Tokyo Cabinet and Kyoto Cabinet

Primary database model

Relational DBMS

Key-value store
Relational DBMS

Key-value store

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

Score	0.97
Rank	#189	Overall
	#86	Relational DBMS

Score	0.28
Rank	#286	Overall
	#41	Key-value stores
	#130	Relational DBMS

Score	2.33
Rank	#111	Overall
	#19	Key-value stores

Score	0.00
Rank	#385	Overall
	#61	Key-value stores

Website

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

www.leanxcale.com

github.com/google/leveldb

dbmx.net/tkrzw

Technical documentation

cubrid.org/manuals

github.com/google/leveldb/blob/main/doc/index.md

Developer

CUBRID Corporation, CUBRID Foundation

LeanXcale

Google

Mikio Hirabayashi

Initial release

2008

2015

2011

2020

Current release

11.0, January 2021

1.23, February 2021

0.9.3, August 2020

License

Commercial or Open Source

Open Source

Apache Version 2.0

commercial

Open Source

BSD

Open Source

Apache Version 2.0

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

C++

Server operating systems

Linux
Windows

Illumos
Linux
OS X
Windows

Linux
macOS

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

through Apache Derby

APIs and other access methods

ADO.NET
JDBC
ODBC
OLE DB

JDBC
Kafka Connector
ODBC
proprietary key/value interface
Spark Connector

Supported programming languages

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

C
Java
Scala

C++
Go
Java

3rd party binding
JavaScript (Node.js)

3rd party binding
Python

3rd party binding

C++
Java
Python
Ruby

Server-side scripts

Stored procedures

Java Stored Procedures

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

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

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

with automatic compression on writes

yes

In-memory capabilities

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

yes

using specific database classes

User concepts

Access control

fine grained access rights according to SQL-standard

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More resources

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