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DBMS > IBM Db2 warehouse vs. MarkLogic vs. Vertica

System Properties Comparison IBM Db2 warehouse vs. MarkLogic vs. Vertica

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Editorial information provided by DB-Engines
NameIBM Db2 warehouse infoformerly named IBM dashDB  Xexclude from comparisonMarkLogic  Xexclude from comparisonVertica infoOpenText™ Vertica™  Xexclude from comparison
DescriptionCloud-based data warehousing serviceOperational and transactional Enterprise NoSQL databaseCloud 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 DBMSDocument store
Native XML DBMS
RDF store infoas of version 7
Search engine
Relational DBMS infoColumn oriented
Secondary database modelsSpatial DBMS
Time Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.34
Rank#166  Overall
#76  Relational DBMS
Score6.50
Rank#56  Overall
#10  Document stores
#1  Native XML DBMS
#1  RDF stores
#5  Search engines
Score11.40
Rank#43  Overall
#27  Relational DBMS
Websitewww.ibm.com/­products/­db2/­warehousewww.marklogic.comwww.vertica.com
Technical documentationdocs.marklogic.comvertica.com/­documentation
DeveloperIBMMarkLogic Corp.OpenText infopreviously Micro Focus and Hewlett Packard
Initial release201420012005
Current release11.0, December 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 serviceyesnono infoon-premises, all major clouds - Amazon AWS, Microsoft Azure, Google Cloud Platform and containers
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC++C++
Server operating systemshostedLinux
OS X
Windows
Linux
Data schemeyesschema-free infoSchema can be enforcedYes, 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.no infoImport/export of XML data possibleyesno
Secondary indexesyesyesNo Indexes Required. Different internal optimization strategy, but same functionality included.
SQL infoSupport of SQLyesyes infoSQL92Full 1999 standard plus machine learning, time series and geospatial. Over 650 functions.
APIs and other access methods.NET Client API
JDBC
ODBC
OLE DB
Java API
Node.js Client API
ODBC
proprietary Optic API infoProprietary Query API, introduced with version 9
RESTful HTTP API
SPARQL
WebDAV
XDBC
XQuery
XSLT
ADO.NET
JDBC
Kafka Connector
ODBC
RESTful HTTP API
Spark Connector
vSQL infocharacter-based, interactive, front-end utility
Supported programming languagesJava
JavaScript (Node.js)
Perl
PHP
Python
R
Ruby
C
C#
C++
Java
JavaScript (Node.js)
Perl
PHP
Python
Ruby
C#
C++
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
R
Server-side scripts infoStored proceduresPL/SQL, SQL PLyes infovia XQuery or JavaScriptyes, PostgreSQL PL/pgSQL, with minor differences
Triggersyesyesyes, called Custom Alerts
Partitioning methods infoMethods for storing different data on different nodesShardingShardinghorizontal partitioning, hierarchical partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesyesyesMulti-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 methodsnoyes infovia Hadoop Connector, HDFS Direct Access and in-database MapReduce jobsno 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 dataACIDACID infocan act as a resource manager in an XA/JTA transactionACID
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.yesyes, with Range Indexesno
User concepts infoAccess controlfine grained access rights according to SQL-standardRole-based access control at the document and subdocument levelsfine grained access rights according to SQL-standard; supports Kerberos, LDAP, Ident and hash
More information provided by the system vendor
IBM Db2 warehouse infoformerly named IBM dashDBMarkLogicVertica infoOpenText™ Vertica™
Specific characteristicsDeploy-anywhere database for large-scale analytical deployments. Deploy off-cloud,...
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Competitive advantagesFast, scalable, and capable of high concurrency. Separation of compute/storage leverages...
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Typical application scenariosCommunication and network analytics, Embedded analytics, Fraud monitoring and Risk...
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Key customersAbiba Systems, Adform, adMarketplace, AmeriPride, Anritsu, AOL, Avito, Auckland Transport,...
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Licensing and pricing modelsCost-based models and subscription-based models are both available. One license is...
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More resources
IBM Db2 warehouse infoformerly named IBM dashDBMarkLogicVertica infoOpenText™ Vertica™
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