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DBMS > BigObject vs. Kinetica

System Properties Comparison BigObject vs. Kinetica

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Editorial information provided by DB-Engines
NameBigObject  Xexclude from comparisonKinetica  Xexclude from comparison
DescriptionAnalytic DBMS for real-time computations and queriesFully vectorized database across both GPUs and CPUs
Primary database modelRelational DBMS infoa hierachical model (tree) can be imposedRelational DBMS
Secondary database modelsSpatial DBMS
Time Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.17
Rank#333  Overall
#146  Relational DBMS
Score0.74
Rank#229  Overall
#105  Relational DBMS
Websitebigobject.iowww.kinetica.com
Technical documentationdocs.bigobject.iodocs.kinetica.com
DeveloperBigObject, Inc.Kinetica
Initial release20152012
Current release7.1, August 2021
License infoCommercial or Open Sourcecommercial infofree community edition availablecommercial
Cloud-based only infoOnly available as a cloud servicenono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageC, C++
Server operating systemsLinux infodistributed as a docker-image
OS X infodistributed as a docker-image (boot2docker)
Windows infodistributed as a docker-image (boot2docker)
Linux
Data schemeyesyes
Typing infopredefined data types such as float or dateyesyes
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
Secondary indexesyesyes
SQL infoSupport of SQLSQL-like DML and DDL statementsSQL-like DML and DDL statements
APIs and other access methodsfluentd
ODBC
RESTful HTTP API
JDBC
ODBC
RESTful HTTP API
Supported programming languagesC++
Java
JavaScript (Node.js)
Python
Server-side scripts infoStored proceduresLuauser defined functions
Triggersnoyes infotriggers when inserted values for one or more columns fall within a specified range
Partitioning methods infoMethods for storing different data on different nodesnoneSharding
Replication methods infoMethods for redundantly storing data on multiple nodesnoneSource-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnono
Consistency concepts infoMethods to ensure consistency in a distributed systemnoneImmediate Consistency or Eventual Consistency depending on configuration
Foreign keys infoReferential integrityyes infoautomatically between fact table and dimension tablesyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanono
Concurrency infoSupport for concurrent manipulation of datayes infoRead/write lock on objects (tables, trees)yes
Durability infoSupport for making data persistentyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesyes infoGPU vRAM or System RAM
User concepts infoAccess controlnoAccess rights for users and roles on table level

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More resources
BigObjectKinetica
Recent citations in the news

Transforming spatiotemporal data analysis with GPUs and generative AI
30 October 2023, InfoWorld

Kinetica Unveils First SQL-GPT for Telecom, Transforming Natural Language into SQL Fine-Tuned for the Telco Industry
7 December 2023, GlobeNewswire

ChatGPT Gives Kinetica a Natural Language Interface for Speedy Analytics Database
2 May 2023, Datanami

Kinetica Could Boost Nvidia In $70B Big Data Market
12 October 2018, Forbes

Review: Kinetica analyzes billions of rows in real time
29 April 2019, InfoWorld

provided by Google News



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