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

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

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Editorial information provided by DB-Engines
NameAmazon DocumentDB  Xexclude from comparisonHBase  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 serviceWide-column store based on Apache Hadoop and on concepts of BigTableSpark SQL is a component on top of 'Spark Core' for structured data processingTransactional SQL-on-Hadoop DBMS
Primary database modelDocument storeWide column storeRelational DBMSRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.91
Rank#131  Overall
#24  Document stores
Score27.97
Rank#26  Overall
#2  Wide column stores
Score18.04
Rank#33  Overall
#20  Relational DBMS
Websiteaws.amazon.com/­documentdbhbase.apache.orgspark.apache.org/­sqltrafodion.apache.org
Technical documentationaws.amazon.com/­documentdb/­resourceshbase.apache.org/­book.htmlspark.apache.org/­docs/­latest/­sql-programming-guide.htmltrafodion.apache.org/­documentation.html
DeveloperApache Software Foundation infoApache top-level project, originally developed by PowersetApache Software FoundationApache Software Foundation, originally developed by HP
Initial release2019200820142014
Current release2.3.4, January 20213.5.0 ( 2.13), September 20232.3.0, February 2019
License infoCommercial or Open SourcecommercialOpen Source infoApache version 2Open 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 languageJavaScalaC++, Java
Server operating systemshostedLinux
Unix
Windows infousing Cygwin
Linux
OS X
Windows
Linux
Data schemeschema-freeschema-free, schema definition possibleyesyes
Typing infopredefined data types such as float or dateyesoptions to bring your own types, AVROyesyes
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.nononono
Secondary indexesyesnonoyes
SQL infoSupport of SQLnonoSQL-like DML and DDL statementsyes
APIs and other access methodsproprietary protocol using JSON (MongoDB compatible)Java API
RESTful HTTP API
Thrift
JDBC
ODBC
ADO.NET
JDBC
ODBC
Supported programming languagesGo
Java
JavaScript (Node.js)
PHP
Python
C
C#
C++
Groovy
Java
PHP
Python
Scala
Java
Python
R
Scala
All languages supporting JDBC/ODBC/ADO.Net
Server-side scripts infoStored proceduresnoyes infoCoprocessors in JavanoJava Stored Procedures
Triggersnoyesnono
Partitioning methods infoMethods for storing different data on different nodesnoneShardingyes, 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 replicasMulti-source replication
Source-replica replication
noneyes, via HBase
MapReduce infoOffers an API for user-defined Map/Reduce methodsno infomay be implemented via Amazon Elastic MapReduce (Amazon EMR)yesyes infovia user defined functions and HBase
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate Consistency or Eventual ConsistencyImmediate Consistency
Foreign keys infoReferential integrityno infotypically not used, however similar functionality with DBRef possiblenonoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataAtomic single-document operationsSingle row ACID (across millions of columns)noACID
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.yesnono
User concepts infoAccess controlAccess rights for users and rolesAccess Control Lists (ACL) for RBAC, integration with Apache Ranger for RBAC & ABACnofine grained access rights according to SQL-standard

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More resources
Amazon DocumentDBHBaseSpark SQLTrafodion
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