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DBMS > Amazon DocumentDB vs. BigObject vs. Fujitsu Enterprise Postgres vs. Kinetica

System Properties Comparison Amazon DocumentDB vs. BigObject vs. Fujitsu Enterprise Postgres vs. Kinetica

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Editorial information provided by DB-Engines
NameAmazon DocumentDB  Xexclude from comparisonBigObject  Xexclude from comparisonFujitsu Enterprise Postgres  Xexclude from comparisonKinetica  Xexclude from comparison
DescriptionFast, scalable, highly available, and fully managed MongoDB-compatible database serviceAnalytic DBMS for real-time computations and queriesEnterprise-grade PostgreSQL-based DBMS with security enhancements such as Transparent Data Encryption and Data Masking, plus high-availability and performance improvement features.Fully vectorized database across both GPUs and CPUs
Primary database modelDocument storeRelational DBMS infoa hierachical model (tree) can be imposedRelational DBMSRelational DBMS
Secondary database modelsDocument store
Spatial DBMS
Spatial DBMS
Time Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.91
Rank#131  Overall
#24  Document stores
Score0.19
Rank#329  Overall
#146  Relational DBMS
Score0.37
Rank#278  Overall
#128  Relational DBMS
Score0.66
Rank#234  Overall
#107  Relational DBMS
Websiteaws.amazon.com/­documentdbbigobject.iowww.postgresql.fastware.comwww.kinetica.com
Technical documentationaws.amazon.com/­documentdb/­resourcesdocs.bigobject.iowww.postgresql.fastware.com/­product-manualsdocs.kinetica.com
DeveloperBigObject, Inc.PostgreSQL Global Development Group, Fujitsu Australia Software TechnologyKinetica
Initial release201920152012
Current releaseFujitsu Enterprise Postgres 14, January 20227.1, August 2021
License infoCommercial or Open Sourcecommercialcommercial infofree community edition availablecommercialcommercial
Cloud-based only infoOnly available as a cloud serviceyesnonono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageCC, 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
Windows
Linux
Data schemeschema-freeyesyesyes
Typing infopredefined data types such as float or dateyesyesyesyes
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 indexesyesyesyesyes
SQL infoSupport of SQLnoSQL-like DML and DDL statementsyesSQL-like DML and DDL statements
APIs and other access methodsproprietary protocol using JSON (MongoDB compatible)fluentd
ODBC
RESTful HTTP API
ADO.NET
JDBC
native C library
ODBC
streaming API for large objects
JDBC
ODBC
RESTful HTTP API
Supported programming languagesGo
Java
JavaScript (Node.js)
PHP
Python
.Net
C
C++
Delphi
Java
JavaScript (Node.js)
Perl
PHP
Python
Tcl
C++
Java
JavaScript (Node.js)
Python
Server-side scripts infoStored proceduresnoLuauser defined functionsuser defined functions
Triggersnonoyesyes infotriggers when inserted values for one or more columns fall within a specified range
Partitioning methods infoMethods for storing different data on different nodesnonenonepartitioning by range, list and by hashSharding
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-availability zones for high availability, asynchronous replication for up to 15 read replicasnoneSource-replica replicationSource-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsno infomay be implemented via Amazon Elastic MapReduce (Amazon EMR)nonono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencynoneImmediate ConsistencyImmediate 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 tablesyesyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataAtomic single-document operationsnoACIDno
Concurrency infoSupport for concurrent manipulation of datayesyes infoRead/write lock on objects (tables, trees)yes, multi-version concurrency control (MVCC)yes
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.yesyes infoGPU vRAM or System RAM
User concepts infoAccess controlAccess rights for users and rolesnofine grained access rights according to SQL-standardAccess rights for users and roles on table level

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More resources
Amazon DocumentDBBigObjectFujitsu Enterprise PostgresKinetica
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