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DBMS > Amazon DocumentDB vs. Apache Phoenix vs. DataFS vs. Kdb

System Properties Comparison Amazon DocumentDB vs. Apache Phoenix vs. DataFS vs. Kdb

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Editorial information provided by DB-Engines
NameAmazon DocumentDB  Xexclude from comparisonApache Phoenix  Xexclude from comparisonDataFS  Xexclude from comparisonKdb  Xexclude from comparison
DescriptionFast, scalable, highly available, and fully managed MongoDB-compatible database serviceA scale-out RDBMS with evolutionary schema built on Apache HBaseAll data is stored inside objects which are linked by so-called link attributes. Objects consist of classes which can be extended and de-extended at runtime. Graphs can be defined with a struct.High performance Time Series DBMS
Primary database modelDocument storeRelational DBMSObject oriented DBMSTime Series DBMS
Vector DBMS
Secondary database modelsGraph DBMSRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.91
Rank#131  Overall
#24  Document stores
Score2.06
Rank#123  Overall
#58  Relational DBMS
Score0.09
Rank#360  Overall
#17  Object oriented DBMS
Score7.71
Rank#49  Overall
#2  Time Series DBMS
#1  Vector DBMS
Websiteaws.amazon.com/­documentdbphoenix.apache.orgnewdatabase.comkx.com
Technical documentationaws.amazon.com/­documentdb/­resourcesphoenix.apache.orgdev.mobiland.com/­Overview.xspcode.kx.com
DeveloperApache Software FoundationMobiland AGKx Systems, a division of First Derivatives plc
Initial release2019201420182000 infokdb was released 2000, kdb+ in 2003
Current release5.0-HBase2, July 2018 and 4.15-HBase1, December 20191.1.263, October 20223.6, May 2018
License infoCommercial or Open SourcecommercialOpen Source infoApache Version 2.0commercialcommercial infofree 32-bit version
Cloud-based only infoOnly available as a cloud serviceyesnonono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaq
Server operating systemshostedLinux
Unix
Windows
WindowsLinux
OS X
Solaris
Windows
Data schemeschema-freeyes infolate-bound, schema-on-read capabilitiesClasses, Structs, and Lists are written in proprietary DataTypeDefinitionLanguage (.dtdl) and Objects consisting of those are written in proprietary DataAccessDefinitionLanguage (.dadl)yes
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.nononoyes
Secondary indexesyesyesnoyes infotable attribute 'grouped'
SQL infoSupport of SQLnoyesnoSQL-like query language (q)
APIs and other access methodsproprietary protocol using JSON (MongoDB compatible)JDBC.NET Client API
Proprietary client DLL
WinRT client
HTTP API
JDBC
Jupyter
Kafka
ODBC
WebSocket
Supported programming languagesGo
Java
JavaScript (Node.js)
PHP
Python
C
C#
C++
Go
Groovy
Java
PHP
Python
Scala
.Net
C
C#
C++
VB.Net
C
C#
C++
Go
J
Java
JavaScript
Lua
MatLab
Perl
PHP
Python
R
Scala
Server-side scripts infoStored proceduresnouser defined functionsuser defined functions
Triggersnonono, except callback-events from server when changes happenedyes infowith views
Partitioning methods infoMethods for storing different data on different nodesnoneShardingProprietary Sharding systemhorizontal partitioning
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
Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsno infomay be implemented via Amazon Elastic MapReduce (Amazon EMR)Hadoop integrationnono infosimilar paradigm used for internal processing
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate Consistency or Eventual ConsistencyImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integrityno infotypically not used, however similar functionality with DBRef possiblenoyesyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataAtomic single-document operationsACIDACIDno
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.yesnoyes
User concepts infoAccess controlAccess rights for users and rolesAccess Control Lists (using HBase ACL) for RBAC, integration with Apache Ranger for RBAC & ABAC, multi-tenancyWindows-Profilerights management via user accounts
More information provided by the system vendor
Amazon DocumentDBApache PhoenixDataFSKdb
Specific characteristicsIntegrated columnar database & programming system for streaming, real time and historical...
» more
Competitive advantagesprovides seamless scalability; runs on industry standard server platforms; is top-ranked...
» more
Typical application scenariostick database streaming sensor data massive intelligence applications oil and gas...
» more
Key customersGoldman Sachs Morgan Stanley Merrill Lynch J.P. Morgan Deutsche Bank IEX Securities...
» more
Market metricskdb+ performance and reliability proven by our customers in critical infrastructure...
» more
Licensing and pricing modelsupon request
» more

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More resources
Amazon DocumentDBApache PhoenixDataFSKdb
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