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DBMS > EXASOL vs. Microsoft SQL Server vs. Vertica

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

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Editorial information provided by DB-Engines
NameEXASOL  Xexclude from comparisonMicrosoft SQL Server  Xexclude from comparisonVertica infoVertica Analytics Platform  Xexclude from comparison
DescriptionHigh-performance, in-memory, MPP database specifically designed for in-memory analytics.Microsofts flagship relational DBMSCloud 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
Score2.73
Rank#128  Overall
#65  Relational DBMS
Score920.09
Rank#3  Overall
#3  Relational DBMS
Score15.98
Rank#40  Overall
#24  Relational DBMS
Websitewww.exasol.comwww.microsoft.com/­en-us/­sql-serverwww.vertica.com
Technical documentationwww.exasol.com/­resourcesdocs.microsoft.com/­en-US/­sql/­sql-serververtica.com/­documentation
DeveloperExasolMicrosoftOpenText infopreviously Micro Focus and Hewlett Packard
Initial release200019892005
Current releaseSQL Server 2022, November 202212.0.3, January 2023
License infoCommercial or Open Sourcecommercialcommercial inforestricted free version is availablecommercial 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 SaaS.
Implementation languageC++C++
Server operating systemsLinux
Windows
Linux
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.noyesno
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 methods.Net
JDBC
ODBC
WebSocket
ADO.NET
JDBC
ODBC
OLE DB
Tabular Data Stream (TDS)
ADO.NET
JDBC
Kafka Connector
ODBC
RESTful HTTP API
Spark Connector
vSQL infocharacter-based, interactive, front-end utility
Supported programming languagesJava
Lua
Python
R
C#
C++
Delphi
Go
Java
JavaScript (Node.js)
PHP
Python
R
Ruby
Visual Basic
C#
C++
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
R
Server-side scripts infoStored proceduresuser defined functionsTransact SQL, .NET languages, R, Python and (with SQL Server 2019) Javayes, PostgreSQL PL/pgSQL, with minor differences
Triggersyesyesyes, called Custom Alerts
Partitioning methods infoMethods for storing different data on different nodesShardingtables can be distributed across several files (horizontal partitioning); sharding through federationhorizontal 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 methodsyes infoHadoop integrationnono infoBi-directional Spark integration
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integrityyesyesyes
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 controlAccess rights for users, groups and roles according to SQL-standardfine grained access rights according to SQL-standardfine grained access rights according to SQL-standard; supports Kerberos, LDAP, Ident and hash
More information provided by the system vendor
EXASOLMicrosoft SQL ServerVertica infoVertica Analytics Platform
Specific characteristicsDeploy-anywhere database for large-scale analytical deployments. Deploy off-cloud,...
» 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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and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.

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More resources
EXASOLMicrosoft SQL ServerVertica infoVertica Analytics Platform
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