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DBMS > Kinetica vs. Microsoft Azure Table Storage vs. PouchDB vs. Teradata Aster vs. Trafodion

System Properties Comparison Kinetica vs. Microsoft Azure Table Storage vs. PouchDB vs. Teradata Aster vs. Trafodion

Editorial information provided by DB-Engines
NameKinetica  Xexclude from comparisonMicrosoft Azure Table Storage  Xexclude from comparisonPouchDB  Xexclude from comparisonTeradata Aster  Xexclude from comparisonTrafodion  Xexclude from comparison
Teradata Aster has been integrated into other Teradata systems and therefore will be removed from the DB-Engines ranking.Apache Trafodion has been retired in 2021. Therefore it is excluded from the DB-Engines Ranking.
DescriptionFully vectorized database across both GPUs and CPUsA Wide Column Store for rapid development using massive semi-structured datasetsJavaScript DBMS with an API inspired by CouchDBPlatform for big data analytics on multistructured data sources and typesTransactional SQL-on-Hadoop DBMS
Primary database modelRelational DBMSWide column storeDocument storeRelational DBMSRelational DBMS
Secondary database modelsSpatial DBMS
Time Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.66
Rank#234  Overall
#107  Relational DBMS
Score4.04
Rank#77  Overall
#6  Wide column stores
Score2.34
Rank#112  Overall
#21  Document stores
Websitewww.kinetica.comazure.microsoft.com/­en-us/­services/­storage/­tablespouchdb.comtrafodion.apache.org
Technical documentationdocs.kinetica.compouchdb.com/­guidestrafodion.apache.org/­documentation.html
DeveloperKineticaMicrosoftApache Software FoundationTeradataApache Software Foundation, originally developed by HP
Initial release20122012201220052014
Current release7.1, August 20217.1.1, June 20192.3.0, February 2019
License infoCommercial or Open SourcecommercialcommercialOpen SourcecommercialOpen Source infoApache 2.0
Cloud-based only infoOnly available as a cloud servicenoyesnonono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageC, C++JavaScriptC++, Java
Server operating systemsLinuxhostedserver-less, requires a JavaScript environment (browser, Node.js)LinuxLinux
Data schemeyesschema-freeschema-freeFlexible Schema (defined schema, partial schema, schema free) infodefined schema within the relational store; partial schema or schema free in the Aster File Storeyes
Typing infopredefined data types such as float or dateyesyesnoyesyes
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.nononoyes infoin Aster File Storeno
Secondary indexesyesnoyes infovia viewsyesyes
SQL infoSupport of SQLSQL-like DML and DDL statementsnonoyesyes
APIs and other access methodsJDBC
ODBC
RESTful HTTP API
RESTful HTTP APIHTTP REST infoonly for PouchDB Server
JavaScript API
ADO.NET
JDBC
ODBC
OLE DB
ADO.NET
JDBC
ODBC
Supported programming languagesC++
Java
JavaScript (Node.js)
Python
.Net
C#
C++
Java
JavaScript (Node.js)
PHP
Python
Ruby
JavaScriptC
C#
C++
Java
Python
R
All languages supporting JDBC/ODBC/ADO.Net
Server-side scripts infoStored proceduresuser defined functionsnoView functions in JavaScriptR packagesJava Stored Procedures
Triggersyes infotriggers when inserted values for one or more columns fall within a specified rangenoyesnono
Partitioning methods infoMethods for storing different data on different nodesShardingSharding infoImplicit feature of the cloud serviceSharding infowith a proxy-based framework, named couchdb-loungeShardingSharding
Replication methods infoMethods for redundantly storing data on multiple nodesSource-replica replicationyes infoimplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.Multi-source replication infoalso with CouchDB databases
Source-replica replication infoalso with CouchDB databases
yes infoDimension tables are replicated across all nodes in the cluster. The number of replicas for the file store can be configured.yes, via HBase
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonoyesyes infoSQL Map-Reduce Frameworkyes infovia user defined functions and HBase
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate Consistency or Eventual Consistency depending on configurationImmediate ConsistencyEventual ConsistencyImmediate Consistency or Eventual Consistency depending on configurationImmediate Consistency
Foreign keys infoReferential integrityyesnononoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanooptimistic lockingnoACIDACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyesyes infoby using IndexedDB, WebSQL or LevelDB as backendyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yes infoGPU vRAM or System RAMnoyesnono
User concepts infoAccess controlAccess rights for users and roles on table levelAccess rights based on private key authentication or shared access signaturesnofine grained access rights according to SQL-standardfine grained access rights according to SQL-standard

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More resources
KineticaMicrosoft Azure Table StoragePouchDBTeradata AsterTrafodion
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