DBMS > Amazon Redshift vs. Cubrid vs. Graph Engine vs. mSQL vs. Sphinx

System Properties Comparison Amazon Redshift vs. Cubrid vs. Graph Engine vs. mSQL vs. Sphinx

Editorial information provided by DB-Engines

Name

Description

Large scale data warehouse service for use with business intelligence tools

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

A distributed in-memory data processing engine, underpinned by a strongly-typed RAM store and a general distributed computation engine

mSQL (Mini SQL) is a simple and lightweight RDBMS

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

Primary database model

Relational DBMS

Graph DBMS
Key-value store

Relational DBMS

Search engine

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

Score	19.03
Rank	#34	Overall
	#21	Relational DBMS

Score	1.31
Rank	#169	Overall
	#78	Relational DBMS

Score	0.62
Rank	#240	Overall
	#21	Graph DBMS
	#35	Key-value stores

Score	1.67
Rank	#151	Overall
	#70	Relational DBMS

Score	6.03
Rank	#60	Overall
	#6	Search engines

Website

aws.amazon.com/redshift

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

www.graphengine.io

hughestech.com.au/products/msql

sphinxsearch.com

Technical documentation

docs.aws.amazon.com/redshift

cubrid.org/manuals

www.graphengine.io/docs/manual

sphinxsearch.com/docs

Developer

Amazon (based on PostgreSQL)

CUBRID Corporation, CUBRID Foundation

Microsoft

Hughes Technologies

Sphinx Technologies Inc.

Initial release

2012

2008

2010

1994

2001

Current release

11.0, January 2021

4.4, October 2021

3.5.1, February 2023

License

Commercial or Open Source

commercial

Open Source

Apache Version 2.0

Open Source

MIT License

commercial

free licenses can be provided

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

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

Implementation language

C, C++, Java

.NET and C

C++

Server operating systems

hosted

Linux
Windows

.NET

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

FreeBSD
Linux
NetBSD
OS X
Solaris
Windows

Data scheme

yes

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

restricted

yes

full-text index on all search fields

SQL

Support of SQL

yes

does not fully support an SQL-standard

yes

A subset of ANSI SQL is implemented

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

SQL-like query language (SphinxQL)

APIs and other access methods

JDBC
ODBC

ADO.NET
JDBC
ODBC
OLE DB

RESTful HTTP API

JDBC
ODBC

Proprietary protocol

Supported programming languages

All languages supporting JDBC/ODBC

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

C#
C++
F#
Visual Basic

C
C++
Delphi
Java
Perl
PHP
Tcl

C++

unofficial client library
Java
Perl

unofficial client library
PHP
Python
Ruby

unofficial client library

Server-side scripts

Stored procedures

user defined functions

in Python

Java Stored Procedures

yes

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

horizontal partitioning

none

Sharding

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

Replication methods

Methods for redundantly storing data on multiple nodes

yes

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

none

Foreign keys

Referential integrity

yes

informational only, not enforced by the system

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

optional: either by committing a write-ahead log (WAL) to the local persistent storage or by dumping the memory to a persistent storage

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

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