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DBMS > BigObject vs. Kinetica vs. Microsoft Azure Table Storage

System Properties Comparison BigObject vs. Kinetica vs. Microsoft Azure Table Storage

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Editorial information provided by DB-Engines
NameBigObject  Xexclude from comparisonKinetica  Xexclude from comparisonMicrosoft Azure Table Storage  Xexclude from comparison
DescriptionAnalytic DBMS for real-time computations and queriesFully vectorized database across both GPUs and CPUsA Wide Column Store for rapid development using massive semi-structured datasets
Primary database modelRelational DBMS infoa hierachical model (tree) can be imposedRelational DBMSWide column store
Secondary database modelsSpatial DBMS
Time Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.13
Rank#333  Overall
#147  Relational DBMS
Score0.64
Rank#236  Overall
#109  Relational DBMS
Score4.48
Rank#75  Overall
#6  Wide column stores
Websitebigobject.iowww.kinetica.comazure.microsoft.com/­en-us/­services/­storage/­tables
Technical documentationdocs.bigobject.iodocs.kinetica.com
DeveloperBigObject, Inc.KineticaMicrosoft
Initial release201520122012
Current release7.1, August 2021
License infoCommercial or Open Sourcecommercial infofree community edition availablecommercialcommercial
Cloud-based only infoOnly available as a cloud servicenonoyes
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)
Linuxhosted
Data schemeyesyesschema-free
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.nonono
Secondary indexesyesyesno
SQL infoSupport of SQLSQL-like DML and DDL statementsSQL-like DML and DDL statementsno
APIs and other access methodsfluentd
ODBC
RESTful HTTP API
JDBC
ODBC
RESTful HTTP API
RESTful HTTP API
Supported programming languagesC++
Java
JavaScript (Node.js)
Python
.Net
C#
C++
Java
JavaScript (Node.js)
PHP
Python
Ruby
Server-side scripts infoStored proceduresLuauser defined functionsno
Triggersnoyes infotriggers when inserted values for one or more columns fall within a specified rangeno
Partitioning methods infoMethods for storing different data on different nodesnoneShardingSharding infoImplicit feature of the cloud service
Replication methods infoMethods for redundantly storing data on multiple nodesnoneSource-replica replicationyes infoimplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonono
Consistency concepts infoMethods to ensure consistency in a distributed systemnoneImmediate Consistency or Eventual Consistency depending on configurationImmediate Consistency
Foreign keys infoReferential integrityyes infoautomatically between fact table and dimension tablesyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanonooptimistic locking
Concurrency infoSupport for concurrent manipulation of datayes infoRead/write lock on objects (tables, trees)yesyes
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 infoGPU vRAM or System RAMno
User concepts infoAccess controlnoAccess rights for users and roles on table levelAccess rights based on private key authentication or shared access signatures

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More resources
BigObjectKineticaMicrosoft Azure Table Storage
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