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DBMS > Amazon DocumentDB vs. Drizzle vs. JaguarDB vs. Kinetica vs. Microsoft Azure Table Storage

System Properties Comparison Amazon DocumentDB vs. Drizzle vs. JaguarDB vs. Kinetica vs. Microsoft Azure Table Storage

Editorial information provided by DB-Engines
NameAmazon DocumentDB  Xexclude from comparisonDrizzle  Xexclude from comparisonJaguarDB  Xexclude from comparisonKinetica  Xexclude from comparisonMicrosoft Azure Table Storage  Xexclude from comparison
Drizzle has published its last release in September 2012. The open-source project is discontinued and Drizzle is excluded from the DB-Engines ranking.
DescriptionFast, scalable, highly available, and fully managed MongoDB-compatible database serviceMySQL fork with a pluggable micro-kernel and with an emphasis of performance over compatibility.Performant, highly scalable DBMS for AI and IoT applicationsFully vectorized database across both GPUs and CPUsA Wide Column Store for rapid development using massive semi-structured datasets
Primary database modelDocument storeRelational DBMSKey-value store
Vector DBMS
Relational DBMSWide column store
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
Score0.00
Rank#383  Overall
#60  Key-value stores
#13  Vector DBMS
Score0.64
Rank#236  Overall
#109  Relational DBMS
Score4.48
Rank#75  Overall
#6  Wide column stores
Websiteaws.amazon.com/­documentdbwww.jaguardb.comwww.kinetica.comazure.microsoft.com/­en-us/­services/­storage/­tables
Technical documentationaws.amazon.com/­documentdb/­resourceswww.jaguardb.com/­support.htmldocs.kinetica.com
DeveloperDrizzle project, originally started by Brian AkerDataJaguar, Inc.KineticaMicrosoft
Initial release20192008201520122012
Current release7.2.4, September 20123.3 July 20237.1, August 2021
License infoCommercial or Open SourcecommercialOpen Source infoGNU GPLOpen Source infoGPL V3.0commercialcommercial
Cloud-based only infoOnly available as a cloud serviceyesnononoyes
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageC++C++ infothe server part. Clients available in other languagesC, C++
Server operating systemshostedFreeBSD
Linux
OS X
LinuxLinuxhosted
Data schemeschema-freeyesyesyesschema-free
Typing infopredefined data types such as float or dateyesyesyesyesyes
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 indexesyesyesyesyesno
SQL infoSupport of SQLnoyes infowith proprietary extensionsA subset of ANSI SQL is implemented infobut no views, foreign keys, triggersSQL-like DML and DDL statementsno
APIs and other access methodsproprietary protocol using JSON (MongoDB compatible)JDBCJDBC
ODBC
JDBC
ODBC
RESTful HTTP API
RESTful HTTP API
Supported programming languagesGo
Java
JavaScript (Node.js)
PHP
Python
C
C++
Java
PHP
C
C++
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
Scala
C++
Java
JavaScript (Node.js)
Python
.Net
C#
C++
Java
JavaScript (Node.js)
PHP
Python
Ruby
Server-side scripts infoStored proceduresnononouser defined functionsno
Triggersnono infohooks for callbacks inside the server can be used.noyes infotriggers when inserted values for one or more columns fall within a specified rangeno
Partitioning methods infoMethods for storing different data on different nodesnoneShardingShardingShardingSharding infoImplicit feature of the cloud service
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
Multi-source replicationSource-replica replicationyes infoimplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.
MapReduce infoOffers an API for user-defined Map/Reduce methodsno infomay be implemented via Amazon Elastic MapReduce (Amazon EMR)nononono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyEventual ConsistencyImmediate Consistency or Eventual Consistency depending on configurationImmediate Consistency
Foreign keys infoReferential integrityno infotypically not used, however similar functionality with DBRef possibleyesnoyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataAtomic single-document operationsACIDnonooptimistic locking
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentyesyesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyes infoGPU vRAM or System RAMno
User concepts infoAccess controlAccess rights for users and rolesPluggable authentication mechanisms infoe.g. LDAP, HTTPrights management via user accountsAccess rights for users and roles on table levelAccess rights based on private key authentication or shared access signatures

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More resources
Amazon DocumentDBDrizzleJaguarDBKineticaMicrosoft Azure Table Storage
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