DBMS > Cubrid vs. HBase vs. mSQL vs. Snowflake vs. Sphinx

System Properties Comparison Cubrid vs. HBase vs. mSQL vs. Snowflake vs. Sphinx

Editorial information provided by DB-Engines

Name

Description

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

Wide-column store based on Apache Hadoop and on concepts of BigTable

mSQL (Mini SQL) is a simple and lightweight RDBMS

Cloud-based data warehousing service for structured and semi-structured data

Open source search engine for searching in data from different sources, e.g. relational databases

Primary database model

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

Score	1.31
Rank	#169	Overall
	#78	Relational DBMS

Score	31.25
Rank	#26	Overall
	#2	Wide column stores

Score	1.67
Rank	#151	Overall
	#70	Relational DBMS

Score	123.20
Rank	#9	Overall
	#6	Relational DBMS

Score	6.03
Rank	#60	Overall
	#6	Search engines

Website

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

hbase.apache.org

hughestech.com.au/products/msql

www.snowflake.com

sphinxsearch.com

Technical documentation

cubrid.org/manuals

hbase.apache.org/book.html

docs.snowflake.net/manuals/index.html

sphinxsearch.com/docs

Developer

CUBRID Corporation, CUBRID Foundation

Apache Software Foundation

Apache top-level project, originally developed by Powerset

Hughes Technologies

Snowflake Computing Inc.

Sphinx Technologies Inc.

Initial release

2008

1994

2014

2001

Current release

11.0, January 2021

2.3.4, January 2021

4.4, October 2021

3.5.1, February 2023

License

Commercial or Open Source

Open Source

Apache Version 2.0

Open Source

Apache version 2

commercial

free licenses can be provided

commercial

Open Source

GPL version 2, commercial licence available

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

C, C++, Java

Java

C++

Server operating systems

Linux
Windows

Linux
Unix
Windows

using Cygwin

AIX
HP-UX
Linux
OS X
Solaris SPARC/x86
Windows

hosted

FreeBSD
Linux
NetBSD
OS X
Solaris
Windows

Data scheme

yes

schema-free, schema definition possible

yes

support of semi-structured data formats (JSON, XML, Avro)

yes

Typing

predefined data types such as float or date

yes

options to bring your own types, AVRO

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

full-text index on all search fields

SQL

Support of SQL

yes

A subset of ANSI SQL is implemented

no subqueries, aggregate functions, views, foreign keys, triggers

yes

SQL-like query language (SphinxQL)

APIs and other access methods

ADO.NET
JDBC
ODBC
OLE DB

Java API
RESTful HTTP API
Thrift

JDBC
ODBC

CLI Client
JDBC
ODBC

Proprietary protocol

Supported programming languages

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

C
C#
C++
Groovy
Java
PHP
Python
Scala

C
C++
Delphi
Java
Perl
PHP
Tcl

JavaScript (Node.js)
Python

C++

unofficial client library
Java
Perl

unofficial client library
PHP
Python
Ruby

unofficial client library

Server-side scripts

Stored procedures

Java Stored Procedures

yes

Coprocessors in Java

user defined functions

Triggers

yes

similar concept for controling cloud resources

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

none

yes

Sharding

Partitioning is done manually, search queries against distributed index is supported

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

Multi-source replication
Source-replica replication

none

yes

none

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Immediate Consistency or Eventual Consistency

none

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

Single row ACID (across millions of columns)

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

The original contents of fields are not stored in the Sphinx index.

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 Control Lists (ACL) for RBAC, integration with Apache Ranger for RBAC & ABAC

Users with fine-grained authorization concept, user roles and pluggable authentication

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