DBMS > Amazon Redshift vs. mSQL vs. Sphinx vs. Tigris

System Properties Comparison Amazon Redshift vs. mSQL vs. Sphinx vs. Tigris

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Editorial information provided by DB-Engines

Name

Description

Large scale data warehouse service for use with business intelligence tools

mSQL (Mini SQL) is a simple and lightweight RDBMS

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

A horizontally scalable, ACID transactional, document database available both as a fully managed cloud service and for deployment on self-managed infrastructure

Primary database model

Relational DBMS

Search engine

Document store
Key-value store
Search engine
Time Series DBMS

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

Score	17.94
Rank	#34	Overall
	#21	Relational DBMS

Score	1.27
Rank	#167	Overall
	#77	Relational DBMS

Score	5.98
Rank	#56	Overall
	#5	Search engines

Score	0.02
Rank	#369	Overall
	#51	Document stores
	#55	Key-value stores
	#24	Search engines
	#38	Time Series DBMS

Website

aws.amazon.com/redshift

hughestech.com.au/products/msql

sphinxsearch.com

www.tigrisdata.com

Technical documentation

docs.aws.amazon.com/redshift

sphinxsearch.com/docs

www.tigrisdata.com/docs

Developer

Amazon (based on PostgreSQL)

Hughes Technologies

Sphinx Technologies Inc.

Tigris Data, Inc.

Initial release

2012

1994

2001

2022

Current release

4.4, October 2021

3.5.1, February 2023

License

Commercial or Open Source

commercial

free licenses can be provided

Open Source

GPL version 2, commercial licence available

Open Source

Apache Version 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++

Server operating systems

hosted

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

FreeBSD
Linux
NetBSD
OS X
Solaris
Windows

Linux
macOS
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

yes

SQL

Support of SQL

yes

does not fully support an SQL-standard

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

Proprietary protocol

CLI Client
gRPC
RESTful HTTP API

Supported programming languages

All languages supporting JDBC/ODBC

C
C++
Delphi
Java
Perl
PHP
Tcl

C++

unofficial client library
Java
Perl

unofficial client library
PHP
Python
Ruby

unofficial client library

Go
Java
JavaScript (Node.js)

Server-side scripts

Stored procedures

user defined functions

in Python

Triggers

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

Sharding

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

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

yes

none

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

none

Immediate Consistency

Foreign keys

Referential integrity

yes

informational only, not enforced by the system

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

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

yes, using FoundationDB

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 rights for users and roles

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