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DBMS > Microsoft SQL Server vs. VelocityDB vs. Vertica

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

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Editorial information provided by DB-Engines
NameMicrosoft SQL Server  Xexclude from comparisonVelocityDB  Xexclude from comparisonVertica infoVertica Analytics Platform  Xexclude from comparison
DescriptionMicrosofts flagship relational DBMSA .NET Object Database that can be embedded/distributed and extended to a graph data model (VelocityGraph)Cloud or on-premises 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 DBMSGraph DBMS
Object oriented DBMS
Relational 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
Score944.96
Rank#3  Overall
#3  Relational DBMS
Score0.01
Rank#348  Overall
#36  Graph DBMS
#18  Object oriented DBMS
Score20.13
Rank#37  Overall
#23  Relational DBMS
Websitewww.microsoft.com/­en-us/­sql-servervelocitydb.comwww.vertica.com
Technical documentationdocs.microsoft.com/­en-US/­sql/­sql-servervelocitydb.com/­UserGuidevertica.com/­documentation
DeveloperMicrosoftVelocityDB IncMicro Focus infoprior to that Hewlett Packard
Initial release198920112005
Current releaseSQL Server 2019, November 20197.x11.1, February 2022
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.
Vertica Accelerator’s high-performance analytics and machine learning with SQL or Python is available as a managed service.
Implementation languageC++C#C++
Server operating systemsLinux
Windows
Any that supports .NETLinux
Data schemeyesyesyes, but unstructured data can be stored in specific Flex-Tables
Typing infopredefined data types such as float or dateyesyesyes: BINARY, BOOLEAN, CHAR, VARCHAR, LONG VARCHAR, DATE, TIME, TIMESTAMP, INTERVAL, INTERVAL DAY TO SECOND, INTERVAL YEAR TO MONTH, DOUBLE PRECISION, FLOAT, INTEGER, BIGINT, SMALLINT,NUMERIC, DECIMAL, NUMBER, MONEY,GEOMETRY
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.yesnono
Secondary indexesyesyesNo Indexes Required
SQL infoSupport of SQLyesnoFull 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)
.NetADO.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
.NetC#
C++
Java
Perl
PHP
Python
R
Server-side scripts infoStored proceduresTransact SQL, .NET languages, R, Python and (with SQL Server 2019) Javanoyes, PostgreSQL PL/pgSQL, with minor differences
TriggersyesCallbacks are triggered when data changesyes, 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 EditionMulti-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 methodsnonono infoBi-directional Spark integration
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate 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.yesyesno
User concepts infoAccess controlfine grained access rights according to SQL-standardBased on Windows Authenticationfine grained access rights according to SQL-standard; supports Kerberos, LDAP, Ident and hash
More information provided by the system vendor
Microsoft SQL ServerVelocityDBVertica infoVertica Analytics Platform
Specific characteristicsDeploy-anywhere database for large-scale analytical deployments. Deploy on-premises,...
» more
Competitive advantagesFast, scalable and capable of high concurrency. Separation of compute/storage leverages...
» more
Typical application scenariosCommunication and network analytics, Embedded analytics, Fraud monitoring and Risk...
» more
Key customersAbiba Systems, Adform, adMarketplace, AmeriPride, Anritsu, AOL, Avito, Auckland Transport,...
» more
Licensing and pricing modelsCost-based models and subscription-based models are both available. One license is...
» more

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More resources
Microsoft SQL ServerVelocityDBVertica infoVertica Analytics Platform
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