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DBMS > MonetDB vs. Tkrzw vs. Vertica vs. Yaacomo

System Properties Comparison MonetDB vs. Tkrzw vs. Vertica vs. Yaacomo

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Editorial information provided by DB-Engines
NameMonetDB  Xexclude from comparisonTkrzw infoSuccessor of Tokyo Cabinet and Kyoto Cabinet  Xexclude from comparisonVertica infoOpenText™ Vertica™  Xexclude from comparisonYaacomo  Xexclude from comparison
Yaacomo seems to be discontinued and is removed from the DB-Engines ranking
DescriptionA relational database management system that stores data in columnsA concept of libraries, allowing an application program to store and query key-value pairs in a file. Successor of Tokyo Cabinet and Kyoto CabinetCloud 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.OpenCL based in-memory RDBMS, designed for efficiently utilizing the hardware via parallel computing
Primary database modelRelational DBMSKey-value storeRelational DBMS infoColumn orientedRelational DBMS
Secondary database modelsDocument store
Spatial DBMS
Spatial DBMS
Time Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.72
Rank#148  Overall
#68  Relational DBMS
Score0.09
Rank#354  Overall
#51  Key-value stores
Score11.40
Rank#43  Overall
#27  Relational DBMS
Websitewww.monetdb.orgdbmx.net/­tkrzwwww.vertica.comyaacomo.com
Technical documentationwww.monetdb.org/­Documentationvertica.com/­documentation
DeveloperMonetDB BVMikio HirabayashiOpenText infopreviously Micro Focus and Hewlett PackardQ2WEB GmbH
Initial release2004202020052009
Current releaseDec2023 (11.49), December 20230.9.3, August 202012.0.3, January 2023
License infoCommercial or Open SourceOpen Source infoMozilla Public License 2.0Open Source infoApache Version 2.0commercial infoLimited community edition freecommercial
Cloud-based only infoOnly available as a cloud servicenonono infoon-premises, all major clouds - Amazon AWS, Microsoft Azure, Google Cloud Platform and containersno
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageCC++C++
Server operating systemsFreeBSD
Linux
OS X
Solaris
Windows
Linux
macOS
LinuxAndroid
Linux
Windows
Data schemeyesschema-freeYes, but also semi-structure/unstructured data storage, and complex hierarchical data (like Parquet) stored and/or queried.yes
Typing infopredefined data types such as float or dateyesnoyesyes
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.nonono
Secondary indexesyesNo Indexes Required. Different internal optimization strategy, but same functionality included.yes
SQL infoSupport of SQLyes infoSQL 2003 with some extensionsnoFull 1999 standard plus machine learning, time series and geospatial. Over 650 functions.yes
APIs and other access methodsJDBC
native C library infoMAPI library (MonetDB application programming interface)
ODBC
ADO.NET
JDBC
Kafka Connector
ODBC
RESTful HTTP API
Spark Connector
vSQL infocharacter-based, interactive, front-end utility
JDBC
ODBC
Supported programming languagesC
C++
Java
JavaScript (Node.js)
Perl
PHP
Python
R
Ruby
C++
Java
Python
Ruby
C#
C++
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
R
Server-side scripts infoStored proceduresyes, in SQL, C, Rnoyes, PostgreSQL PL/pgSQL, with minor differences
Triggersyesnoyes, called Custom Alertsyes
Partitioning methods infoMethods for storing different data on different nodesSharding via remote tablesnonehorizontal partitioning, hierarchical partitioninghorizontal partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesnone infoSource-replica replication available in experimental statusnoneMulti-source replication infoOne, or more copies of data replicated across nodes, or object-store used for repository.Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonono infoBi-directional Spark integrationno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integrityyesnoyesyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACIDACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yes infousing specific database classesnoyes
User concepts infoAccess controlfine grained access rights according to SQL-standardnofine grained access rights according to SQL-standard; supports Kerberos, LDAP, Ident and hashfine grained access rights according to SQL-standard
More information provided by the system vendor
MonetDBTkrzw infoSuccessor of Tokyo Cabinet and Kyoto CabinetVertica infoOpenText™ Vertica™Yaacomo
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
MonetDBTkrzw infoSuccessor of Tokyo Cabinet and Kyoto CabinetVertica infoOpenText™ Vertica™Yaacomo
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