DBMS > atoti vs. IBM Db2 warehouse vs. Microsoft SQL Server vs. Sphinx

System Properties Comparison atoti vs. IBM Db2 warehouse vs. Microsoft SQL Server vs. Sphinx

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Editorial information provided by DB-Engines

Name

Description

An in-memory DBMS combining transactional and analytical processing to handle the aggregation of ever-changing data.

Cloud-based data warehousing service

Microsofts flagship relational DBMS

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

Primary database model

Object oriented DBMS

Relational DBMS

Search engine

Secondary database models

Document store
Graph DBMS
Spatial DBMS

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

Score	0.61
Rank	#243	Overall
	#10	Object oriented DBMS

Score	1.37
Rank	#160	Overall
	#74	Relational DBMS

Score	821.56
Rank	#3	Overall
	#3	Relational DBMS

Score	5.95
Rank	#55	Overall
	#5	Search engines

Website

atoti.io

www.ibm.com/products/db2/warehouse

www.microsoft.com/en-us/sql-server

sphinxsearch.com

Technical documentation

docs.atoti.io

learn.microsoft.com/en-US/sql/sql-server

sphinxsearch.com/docs

Developer

ActiveViam

IBM

Microsoft

Sphinx Technologies Inc.

Initial release

2014

1989

2001

Current release

SQL Server 2022, November 2022

3.5.1, February 2023

License

Commercial or Open Source

commercial

free versions available

commercial

restricted free version is available

Open Source

GPL version 2, commercial licence available

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

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Implementation language

Java

C++

Server operating systems

hosted

Linux
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.

Import/export of XML data possible

yes

Secondary indexes

yes

full-text index on all search fields

SQL

Support of SQL

Multidimensional Expressions (MDX)

yes

SQL-like query language (SphinxQL)

APIs and other access methods

.NET Client API
JDBC
ODBC
OLE DB

ADO.NET
JDBC
ODBC
OLE DB
Tabular Data Stream (TDS)

Proprietary protocol

Supported programming languages

Java
JavaScript (Node.js)
Perl
PHP
Python
R
Ruby

C#
C++
Delphi
Go
Java
JavaScript (Node.js)
PHP
Python
R
Ruby
Visual Basic

C++

unofficial client library
Java
Perl

unofficial client library
PHP
Python
Ruby

unofficial client library

Server-side scripts

Stored procedures

Python

PL/SQL, SQL PL

Transact SQL, .NET languages, R, Python and (with SQL Server 2019) Java

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding, horizontal partitioning

Sharding

tables can be distributed across several files (horizontal partitioning); sharding through federation

Sharding

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

Replication methods

Methods for redundantly storing data on multiple nodes

yes

yes, but depending on the SQL-Server Edition

none

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

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, multi-version concurrency control (MVCC)

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

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