DBMS > Cubrid vs. LeanXcale vs. Microsoft Azure SQL Database vs. Newts

System Properties Comparison Cubrid vs. LeanXcale vs. Microsoft Azure SQL Database vs. Newts

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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

Database as a Service offering with high compatibility to Microsoft SQL Server

Time Series DBMS based on Cassandra

Primary database model

Relational DBMS

Key-value store
Relational DBMS

Relational DBMS

Time Series DBMS

Secondary database models

Document store
Graph DBMS
Spatial DBMS

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

Score	1.04
Rank	#187	Overall
	#87	Relational DBMS

Score	0.36
Rank	#280	Overall
	#40	Key-value stores
	#129	Relational DBMS

Score	76.78
Rank	#16	Overall
	#11	Relational DBMS

Score	0.07
Rank	#375	Overall
	#41	Time Series DBMS

Website

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

www.leanxcale.com

azure.microsoft.com/en-us/products/azure-sql/database

opennms.github.io/newts

Technical documentation

cubrid.org/manuals

docs.microsoft.com/en-us/azure/azure-sql

github.com/OpenNMS/newts/wiki

Developer

CUBRID Corporation, CUBRID Foundation

LeanXcale

Microsoft

OpenNMS Group

Initial release

2008

2015

2010

2014

Current release

11.0, January 2021

V12

License

Commercial or Open Source

Open Source

Apache Version 2.0

commercial

Open Source

Apache 2.0

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

C++

Java

Server operating systems

Linux
Windows

hosted

Linux
OS X
Windows

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.

yes

Secondary indexes

yes

SQL

Support of SQL

yes

through Apache Derby

yes

APIs and other access methods

ADO.NET
JDBC
ODBC
OLE DB

JDBC
Kafka Connector
ODBC
proprietary key/value interface
Spark Connector

ADO.NET
JDBC
ODBC

HTTP REST
Java API

Supported programming languages

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

C
Java
Scala

.Net
C#
Java
JavaScript (Node.js)
PHP
Python
Ruby

Java

Server-side scripts

Stored procedures

Java Stored Procedures

Transact SQL

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

based on Cassandra

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

yes, with always 3 replicas available

selectable replication factor

based on Cassandra

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency

based on Cassandra
Immediate Consistency

based on Cassandra

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

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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