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DBMS > Microsoft SQL Server vs. Netezza vs. Vertica

System Properties Comparison Microsoft SQL Server vs. Netezza vs. Vertica

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Editorial information provided by DB-Engines
NameMicrosoft SQL Server  Xexclude from comparisonNetezza infoAlso called PureData System for Analytics by IBM  Xexclude from comparisonVertica infoOpenText™ Vertica™  Xexclude from comparison
DescriptionMicrosofts flagship relational DBMSData warehouse and analytics appliance part of IBM PureSystemsCloud or off-cloud analytical database and query engine for structured and semi-structured streaming and batch data. Machine learning platform with built-in algorithms, data preparation capabilities, and model evaluation and management via SQL or Python.
Primary database modelRelational DBMSRelational DBMSRelational DBMS infoColumn oriented
Secondary database modelsDocument store
Graph DBMS
Spatial DBMS
Spatial DBMS
Time Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score802.09
Rank#3  Overall
#3  Relational DBMS
Score7.34
Rank#48  Overall
#30  Relational DBMS
Score10.02
Rank#42  Overall
#26  Relational DBMS
Websitewww.microsoft.com/­en-us/­sql-serverwww.ibm.com/­products/­netezzawww.vertica.com
Technical documentationlearn.microsoft.com/­en-US/­sql/­sql-serververtica.com/­documentation
DeveloperMicrosoftIBMOpenText infopreviously Micro Focus and Hewlett Packard
Initial release198920002005
Current releaseSQL Server 2022, November 202212.0.3, January 2023
License infoCommercial or Open Sourcecommercial inforestricted free version is availablecommercialcommercial infoLimited community edition free
Cloud-based only infoOnly available as a cloud servicenonono infoon-premises, all major clouds - Amazon AWS, Microsoft Azure, Google Cloud Platform and containers
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
SQLServer Flex @ STACKIT offers a managed version of SQL Server with adjustable CPU, RAM, storage amount and speed, in enterprise grade to perfectly match all application requirements. All services are 100% GDPR-compliant.
Implementation languageC++C++
Server operating systemsLinux
Windows
Linux infoincluded in applianceLinux
Data schemeyesyesYes, but also semi-structure/unstructured data storage, and complex hierarchical data (like Parquet) stored and/or queried.
Typing infopredefined data types such as float or dateyesyesyes
XML support infoSome form of processing data in XML format, e.g. support for XML data structures, and/or support for XPath, XQuery or XSLT.yesno
Secondary indexesyesyesNo Indexes Required. Different internal optimization strategy, but same functionality included.
SQL infoSupport of SQLyesyesFull 1999 standard plus machine learning, time series and geospatial. Over 650 functions.
APIs and other access methodsADO.NET
JDBC
ODBC
OLE DB
Tabular Data Stream (TDS)
JDBC
ODBC
OLE DB
ADO.NET
JDBC
Kafka Connector
ODBC
RESTful HTTP API
Spark Connector
vSQL infocharacter-based, interactive, front-end utility
Supported programming languagesC#
C++
Delphi
Go
Java
JavaScript (Node.js)
PHP
Python
R
Ruby
Visual Basic
C
C++
Fortran
Java
Lua
Perl
Python
R
C#
C++
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
R
Server-side scripts infoStored proceduresTransact SQL, .NET languages, R, Python and (with SQL Server 2019) Javayesyes, PostgreSQL PL/pgSQL, with minor differences
Triggersyesnoyes, called Custom Alerts
Partitioning methods infoMethods for storing different data on different nodestables can be distributed across several files (horizontal partitioning); sharding through federationShardinghorizontal partitioning, hierarchical partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesyes, but depending on the SQL-Server EditionSource-replica replicationMulti-source replication infoOne, or more copies of data replicated across nodes, or object-store used for repository.
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyesno infoBi-directional Spark integration
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integrityyesnoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACIDACID
Concurrency infoSupport for concurrent manipulation of datayesyesyes
Durability infoSupport for making data persistentyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesno
User concepts infoAccess controlfine grained access rights according to SQL-standardUsers with fine-grained authorization conceptfine grained access rights according to SQL-standard; supports Kerberos, LDAP, Ident and hash

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More resources
Microsoft SQL ServerNetezza infoAlso called PureData System for Analytics by IBMVertica infoOpenText™ Vertica™
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Conferences, events and webinars

PASS Data Community Summit
Seattle, Washington, 4-8 November 2024

Recent citations in the news

Load balancing strategies for Amazon RDS for SQL Server read replicas to scale read workloads and reduce latency
7 October 2024, AWS Blog

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21 August 2024, ITPro

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3 July 2019, The Register

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Postgres pioneer Michael Stonebraker promises to upend the database once more
26 December 2023, The Register

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