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DBMS > Amazon DocumentDB vs. PostGIS vs. Spark SQL vs. Trafodion

System Properties Comparison Amazon DocumentDB vs. PostGIS vs. Spark SQL vs. Trafodion

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Editorial information provided by DB-Engines
NameAmazon DocumentDB  Xexclude from comparisonPostGIS  Xexclude from comparisonSpark SQL  Xexclude from comparisonTrafodion  Xexclude from comparison
Apache Trafodion has been retired in 2021. Therefore it is excluded from the DB-Engines Ranking.
DescriptionFast, scalable, highly available, and fully managed MongoDB-compatible database serviceSpatial extension of PostgreSQLSpark SQL is a component on top of 'Spark Core' for structured data processingTransactional SQL-on-Hadoop DBMS
Primary database modelDocument storeSpatial DBMSRelational DBMSRelational DBMS
Secondary database modelsRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.89
Rank#137  Overall
#24  Document stores
Score23.90
Rank#29  Overall
#1  Spatial DBMS
Score19.15
Rank#33  Overall
#20  Relational DBMS
Websiteaws.amazon.com/­documentdbpostgis.netspark.apache.org/­sqltrafodion.apache.org
Technical documentationaws.amazon.com/­documentdb/­resourcespostgis.net/­documentationspark.apache.org/­docs/­latest/­sql-programming-guide.htmltrafodion.apache.org/­documentation.html
DeveloperApache Software FoundationApache Software Foundation, originally developed by HP
Initial release2019200520142014
Current release3.4.2, February 20243.5.0 ( 2.13), September 20232.3.0, February 2019
License infoCommercial or Open SourcecommercialOpen Source infoGPL v2.0Open Source infoApache 2.0Open Source infoApache 2.0
Cloud-based only infoOnly available as a cloud serviceyesnonono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageCScalaC++, Java
Server operating systemshostedLinux
OS X
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.noyesnono
Secondary indexesyesyesnoyes
SQL infoSupport of SQLnoyesSQL-like DML and DDL statementsyes
APIs and other access methodsproprietary protocol using JSON (MongoDB compatible)JDBC
ODBC
ADO.NET
JDBC
ODBC
Supported programming languagesGo
Java
JavaScript (Node.js)
PHP
Python
Java
Python
R
Scala
All languages supporting JDBC/ODBC/ADO.Net
Server-side scripts infoStored proceduresnouser defined functionsnoJava Stored Procedures
Triggersnoyesnono
Partitioning methods infoMethods for storing different data on different nodesnoneyes infobased on PostgreSQLyes, utilizing Spark CoreSharding
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-availability zones for high availability, asynchronous replication for up to 15 read replicasyes infobased on PostgreSQLnoneyes, via HBase
MapReduce infoOffers an API for user-defined Map/Reduce methodsno infomay be implemented via Amazon Elastic MapReduce (Amazon EMR)noyes infovia user defined functions and HBase
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integrityno infotypically not used, however similar functionality with DBRef possibleyesnoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataAtomic single-document operationsACIDnoACID
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.nonono
User concepts infoAccess controlAccess rights for users and rolesyes infobased on PostgreSQLnofine grained access rights according to SQL-standard

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More resources
Amazon DocumentDBPostGISSpark SQLTrafodion
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