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DBMS > Amazon DocumentDB vs. BigObject vs. Kinetica

System Properties Comparison Amazon DocumentDB vs. BigObject vs. Kinetica

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Editorial information provided by DB-Engines
NameAmazon DocumentDB  Xexclude from comparisonBigObject  Xexclude from comparisonKinetica  Xexclude from comparison
DescriptionFast, scalable, highly available, and fully managed MongoDB-compatible database serviceAnalytic DBMS for real-time computations and queriesFully vectorized database across both GPUs and CPUs
Primary database modelDocument storeRelational 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
Score1.91
Rank#132  Overall
#24  Document stores
Score0.13
Rank#333  Overall
#147  Relational DBMS
Score0.64
Rank#236  Overall
#109  Relational DBMS
Websiteaws.amazon.com/­documentdbbigobject.iowww.kinetica.com
Technical documentationaws.amazon.com/­documentdb/­resourcesdocs.bigobject.iodocs.kinetica.com
DeveloperBigObject, Inc.Kinetica
Initial release201920152012
Current release7.1, August 2021
License infoCommercial or Open Sourcecommercialcommercial infofree community edition availablecommercial
Cloud-based only infoOnly available as a cloud serviceyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageC, C++
Server operating systemshostedLinux infodistributed as a docker-image
OS X infodistributed as a docker-image (boot2docker)
Windows infodistributed as a docker-image (boot2docker)
Linux
Data schemeschema-freeyesyes
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 indexesyesyesyes
SQL infoSupport of SQLnoSQL-like DML and DDL statementsSQL-like DML and DDL statements
APIs and other access methodsproprietary protocol using JSON (MongoDB compatible)fluentd
ODBC
RESTful HTTP API
JDBC
ODBC
RESTful HTTP API
Supported programming languagesGo
Java
JavaScript (Node.js)
PHP
Python
C++
Java
JavaScript (Node.js)
Python
Server-side scripts infoStored proceduresnoLuauser defined functions
Triggersnonoyes infotriggers when inserted values for one or more columns fall within a specified range
Partitioning methods infoMethods for storing different data on different nodesnonenoneSharding
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-availability zones for high availability, asynchronous replication for up to 15 read replicasnoneSource-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsno infomay be implemented via Amazon Elastic MapReduce (Amazon EMR)nono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencynoneImmediate Consistency or Eventual Consistency depending on configuration
Foreign keys infoReferential integrityno infotypically not used, however similar functionality with DBRef possibleyes infoautomatically between fact table and dimension tablesyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataAtomic single-document operationsnono
Concurrency infoSupport for concurrent manipulation of datayesyes infoRead/write lock on objects (tables, trees)yes
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 RAM
User concepts infoAccess controlAccess rights for users and rolesnoAccess rights for users and roles on table level

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More resources
Amazon DocumentDBBigObjectKinetica
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