DBMS > GBase vs. Microsoft Azure Synapse Analytics vs. mSQL vs. Sphinx

System Properties Comparison GBase vs. Microsoft Azure Synapse Analytics vs. mSQL vs. Sphinx

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Editorial information provided by DB-Engines

Name

Description

Widely used RDBMS in China, including analytical, transactional, distributed transactional, and cloud-native data warehousing.

Elastic, large scale data warehouse service leveraging the broad eco-system of SQL Server

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

Search engine

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

Score	1.11
Rank	#173	Overall
	#78	Relational DBMS

Score	18.98
Rank	#31	Overall
	#19	Relational DBMS

Score	1.26
Rank	#163	Overall
	#74	Relational DBMS

Score	5.97
Rank	#56	Overall
	#5	Search engines

Website

www.gbase.cn

azure.microsoft.com/services/synapse-analytics

hughestech.com.au/products/msql

sphinxsearch.com

Technical documentation

docs.microsoft.com/azure/synapse-analytics

sphinxsearch.com/docs

Developer

General Data Technology Co., Ltd.

Microsoft

Hughes Technologies

Sphinx Technologies Inc.

Initial release

2004

2016

1994

2001

Current release

GBase 8a, GBase 8s, GBase 8c

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

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, Java, Python

C++

Server operating systems

Linux

hosted

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.

yes

Secondary indexes

yes

full-text index on all search fields

SQL

Support of SQL

Standard with numerous extensions

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

ADO.NET
C API
JDBC
ODBC

ADO.NET
JDBC
ODBC

JDBC
ODBC

Proprietary protocol

Supported programming languages

C#
Java
PHP

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

Transact SQL

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

horizontal partitioning (by range, list and hash) and vertical partitioning

Sharding, 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

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

docs.microsoft.com/en-us/azure/synapse-analytics/sql-data-warehouse/sql-data-warehouse-table-constraints

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.

In-memory capabilities

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

User concepts

Access control

yes

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More resources

DB-Engines blog posts

The DB-Engines ranking includes now search engines
4 February 2013, Paul Andlinger

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