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DBMS > Kinetica vs. ObjectBox vs. Vertica vs. VictoriaMetrics

System Properties Comparison Kinetica vs. ObjectBox vs. Vertica vs. VictoriaMetrics

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Editorial information provided by DB-Engines
NameKinetica  Xexclude from comparisonObjectBox  Xexclude from comparisonVertica infoOpenText™ Vertica™  Xexclude from comparisonVictoriaMetrics  Xexclude from comparison
DescriptionFully vectorized database across both GPUs and CPUsExtremely fast embedded database for small devices, IoT and MobileCloud 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.A fast, cost-effective and scalable Time Series DBMS and monitoring solution
Primary database modelRelational DBMSObject oriented DBMSRelational DBMS infoColumn orientedTime Series DBMS
Secondary database modelsSpatial DBMS
Time Series DBMS
Time Series DBMSSpatial DBMS
Time Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.66
Rank#234  Overall
#107  Relational DBMS
Score1.29
Rank#166  Overall
#5  Object oriented DBMS
Score10.06
Rank#42  Overall
#26  Relational DBMS
Score1.23
Rank#172  Overall
#15  Time Series DBMS
Websitewww.kinetica.comobjectbox.iowww.vertica.comvictoriametrics.com
Technical documentationdocs.kinetica.comdocs.objectbox.iovertica.com/­documentationdocs.victoriametrics.com
github.com/­VictoriaMetrics/­VictoriaMetrics/­wiki
DeveloperKineticaObjectBox LimitedOpenText infopreviously Micro Focus and Hewlett PackardVictoriaMetrics
Initial release2012201720052018
Current release7.1, August 202112.0.3, January 2023v1.91, May 2023
License infoCommercial or Open SourcecommercialOpen Source infoApache License 2.0commercial infoLimited community edition freeOpen Source infoApache Version 2.0
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

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Implementation languageC, C++C and C++C++Go
Server operating systemsLinuxAndroid
iOS
Linux
macOS
Windows
LinuxFreeBSD
Linux
macOS
OpenBSD
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.nononono
Secondary indexesyesyesNo Indexes Required. Different internal optimization strategy, but same functionality included.
SQL infoSupport of SQLSQL-like DML and DDL statementsnoFull 1999 standard plus machine learning, time series and geospatial. Over 650 functions.no
APIs and other access methodsJDBC
ODBC
RESTful HTTP API
Proprietary native APIADO.NET
JDBC
Kafka Connector
ODBC
RESTful HTTP API
Spark Connector
vSQL infocharacter-based, interactive, front-end utility
Graphite protocol
InfluxDB Line Protocol
OpenTSDB
Prometheus Query API
Prometheus Remote Read/Write
Supported programming languagesC++
Java
JavaScript (Node.js)
Python
C
C++
Dart
Go
Java
JavaScript infoplanned (as of Jan 2019)
Kotlin
Python infoplanned (as of Jan 2019)
Swift
C#
C++
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
R
Server-side scripts infoStored proceduresuser defined functionsnoyes, PostgreSQL PL/pgSQL, with minor differencesno
Triggersyes infotriggers when inserted values for one or more columns fall within a specified rangenoyes, called Custom Alertsno
Partitioning methods infoMethods for storing different data on different nodesShardingnonehorizontal partitioning, hierarchical partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesSource-replica replicationonline/offline synchronization between client and serverMulti-source replication infoOne, or more copies of data replicated across nodes, or object-store used for repository.Synchronous 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 Consistency or Eventual Consistency depending on configurationImmediate ConsistencyImmediate ConsistencyEventual Consistency
Foreign keys infoReferential integrityyesyesyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDACIDno
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 infoGPU vRAM or System RAMnonono
User concepts infoAccess controlAccess rights for users and roles on table levelyesfine grained access rights according to SQL-standard; supports Kerberos, LDAP, Ident and hash
More information provided by the system vendor
KineticaObjectBoxVertica infoOpenText™ Vertica™VictoriaMetrics
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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