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DBMS > Amazon DocumentDB vs. Apache Phoenix vs. FileMaker vs. GridDB

System Properties Comparison Amazon DocumentDB vs. Apache Phoenix vs. FileMaker vs. GridDB

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Editorial information provided by DB-Engines
NameAmazon DocumentDB  Xexclude from comparisonApache Phoenix  Xexclude from comparisonFileMaker  Xexclude from comparisonGridDB  Xexclude from comparison
DescriptionFast, scalable, highly available, and fully managed MongoDB-compatible database serviceA scale-out RDBMS with evolutionary schema built on Apache HBaseFileMaker is a cross-platform RDBMS that includes a GUI frontend.Scalable in-memory time series database optimized for IoT and Big Data
Primary database modelDocument storeRelational DBMSRelational DBMSTime Series DBMS
Secondary database modelsKey-value store
Relational 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
Score47.91
Rank#20  Overall
#14  Relational DBMS
Score2.09
Rank#120  Overall
#10  Time Series DBMS
Websiteaws.amazon.com/­documentdbphoenix.apache.orgwww.claris.com/­filemakergriddb.net
Technical documentationaws.amazon.com/­documentdb/­resourcesphoenix.apache.orgwww.claris.com/­resources/­documentationdocs.griddb.net
DeveloperApache Software FoundationClaris infoa subsidiary of AppleToshiba Corporation
Initial release2019201419832013
Current release5.0-HBase2, July 2018 and 4.15-HBase1, December 201919.4.1, November 20215.1, August 2022
License infoCommercial or Open SourcecommercialOpen Source infoApache Version 2.0commercialOpen Source infoAGPL version 3 and Apache License, version 2.0 , commercial license (standard and advanced editions) also available
Cloud-based only infoOnly available as a cloud serviceyesnonono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJavaC++
Server operating systemshostedLinux
Unix
Windows
iOS infoclient part only
Linux
OS X
Windows
Linux
Data schemeschema-freeyes infolate-bound, schema-on-read capabilitiesyesyes
Typing infopredefined data types such as float or dateyesyesyesyes infonumerical, string, blob, geometry, boolean, timestamp
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.nonoyes infoA http query request can return the data in XML formatno
Secondary indexesyesyesyesyes
SQL infoSupport of SQLnoyesyes infovia pluginsSQL92, SQL-like TQL (Toshiba Query Language)
APIs and other access methodsproprietary protocol using JSON (MongoDB compatible)JDBCFilemaker WebDirect
JDBC
ODBC
JDBC
ODBC
Proprietary protocol
RESTful HTTP/JSON API
Supported programming languagesGo
Java
JavaScript (Node.js)
PHP
Python
C
C#
C++
Go
Groovy
Java
PHP
Python
Scala
PHPC
C++
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
Ruby
Server-side scripts infoStored proceduresnouser defined functionsyesno
Triggersnonoyesyes
Partitioning methods infoMethods for storing different data on different nodesnoneShardingnoneSharding
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, warm standby infosince Version 14Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsno infomay be implemented via Amazon Elastic MapReduce (Amazon EMR)Hadoop integrationnoConnector for using GridDB as an input source and output destination for Hadoop MapReduce jobs
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate Consistency or Eventual ConsistencyImmediate consistency within container, eventual consistency across containers
Foreign keys infoReferential integrityno infotypically not used, however similar functionality with DBRef possiblenoyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataAtomic single-document operationsACIDnoACID at container level
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.yesyes
User concepts infoAccess controlAccess rights for users and rolesAccess Control Lists (using HBase ACL) for RBAC, integration with Apache Ranger for RBAC & ABAC, multi-tenancysimple rights management via user accounts and connection to external directory servicesAccess rights for users can be defined per database
More information provided by the system vendor
Amazon DocumentDBApache PhoenixFileMakerGridDB
Specific characteristicsGridDB is a highly scalable, in-memory time series database optimized for IoT and...
» more
Competitive advantages1. Optimized for IoT Equipped with Toshiba's proprietary key-container data model...
» more
Typical application scenariosFactory IoT, Automative Industry, Energy, BEMS, Smart Community, Monitoring system.
» more
Key customersDenso International [see use case ] An Electric Power company [see use case ] Ishinomaki...
» more
Market metricsGitHub trending repository
» more
Licensing and pricing modelsOpen Source license (AGPL v3 & Apache v2) Commercial license (subscription)
» more

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More resources
Amazon DocumentDBApache PhoenixFileMakerGridDB
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