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DBMS > Kinetica vs. Rockset vs. StarRocks vs. Vertica

System Properties Comparison Kinetica vs. Rockset vs. StarRocks vs. Vertica

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Editorial information provided by DB-Engines
NameKinetica  Xexclude from comparisonRockset  Xexclude from comparisonStarRocks  Xexclude from comparisonVertica infoOpenText™ Vertica™  Xexclude from comparison
DescriptionFully vectorized database across both GPUs and CPUsA scalable, reliable search and analytics service in the cloud, built on RocksDBAn open source, high-performance columnar analytical database that enables real-time, multi-dimensional, and highly concurrent data analytics infoForked from Apache DorisCloud 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 storeRelational DBMSRelational DBMS infoColumn oriented
Secondary database modelsSpatial DBMS
Time Series DBMS
Relational DBMS
Search engine
Spatial 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
Score0.82
Rank#212  Overall
#36  Document stores
Score0.93
Rank#198  Overall
#93  Relational DBMS
Score10.06
Rank#42  Overall
#26  Relational DBMS
Websitewww.kinetica.comrockset.comwww.starrocks.iowww.vertica.com
Technical documentationdocs.kinetica.comdocs.rockset.comdocs.starrocks.io/­en-us/­latest/­introduction/­StarRocks_introvertica.com/­documentation
DeveloperKineticaRocksetThe Linux Foundation infosince Feb 2023OpenText infopreviously Micro Focus and Hewlett Packard
Initial release2012201920202005
Current release7.1, August 20212.5.3, March 202312.0.3, January 2023
License infoCommercial or Open SourcecommercialcommercialOpen Source infoApache Version 2.0commercial infoLimited community edition free
Cloud-based only infoOnly available as a cloud servicenoyesnono 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++C++C++, JavaC++
Server operating systemsLinuxhostedLinuxLinux
Data schemeyesschema-freeyesYes, 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 dateyesdynamic typingyesyes
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.nono infoingestion from XML files supportednono
Secondary indexesyesall fields are automatically indexedyesNo Indexes Required. Different internal optimization strategy, but same functionality included.
SQL infoSupport of SQLSQL-like DML and DDL statementsRead-only SQL queries, including JOINsyesFull 1999 standard plus machine learning, time series and geospatial. Over 650 functions.
APIs and other access methodsJDBC
ODBC
RESTful HTTP API
HTTP RESTJDBC
MySQL protocol
ADO.NET
JDBC
Kafka Connector
ODBC
RESTful HTTP API
Spark Connector
vSQL infocharacter-based, interactive, front-end utility
Supported programming languagesC++
Java
JavaScript (Node.js)
Python
Go
Java
JavaScript (Node.js)
Python
JavaC#
C++
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
R
Server-side scripts infoStored proceduresuser defined functionsnouser defined functionsyes, PostgreSQL PL/pgSQL, with minor differences
Triggersyes infotriggers when inserted values for one or more columns fall within a specified rangenonoyes, called Custom Alerts
Partitioning methods infoMethods for storing different data on different nodesShardingAutomatic shardinghorizontal partitioning (by range and hash)horizontal partitioning, hierarchical partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesSource-replica replicationyesMulti-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 methodsnononono infoBi-directional Spark integration
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate Consistency or Eventual Consistency depending on configurationEventual ConsistencyImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integrityyesnonoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanononoACID
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 RAMnono
User concepts infoAccess controlAccess rights for users and roles on table levelAccess rights for users and organizations can be defined via Rockset consoleRole based access control and fine grained access rightsfine grained access rights according to SQL-standard; supports Kerberos, LDAP, Ident and hash
More information provided by the system vendor
KineticaRocksetStarRocksVertica 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,...
» more
Licensing and pricing modelsCost-based models and subscription-based models are both available. One license is...
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KineticaRocksetStarRocksVertica infoOpenText™ Vertica™
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