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DBMS > Apache Phoenix vs. Datomic vs. GridDB vs. OrientDB

System Properties Comparison Apache Phoenix vs. Datomic vs. GridDB vs. OrientDB

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Editorial information provided by DB-Engines
NameApache Phoenix  Xexclude from comparisonDatomic  Xexclude from comparisonGridDB  Xexclude from comparisonOrientDB  Xexclude from comparison
DescriptionA scale-out RDBMS with evolutionary schema built on Apache HBaseDatomic builds on immutable values, supports point-in-time queries and uses 3rd party systems for durabilityScalable in-memory time series database optimized for IoT and Big DataMulti-model DBMS (Document, Graph, Key/Value)
Primary database modelRelational DBMSRelational DBMSTime Series DBMSDocument store
Graph DBMS
Key-value store
Secondary database modelsKey-value store
Relational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.97
Rank#126  Overall
#59  Relational DBMS
Score1.59
Rank#150  Overall
#69  Relational DBMS
Score1.95
Rank#128  Overall
#10  Time Series DBMS
Score3.19
Rank#93  Overall
#16  Document stores
#7  Graph DBMS
#14  Key-value stores
Websitephoenix.apache.orgwww.datomic.comgriddb.netorientdb.org
Technical documentationphoenix.apache.orgdocs.datomic.comdocs.griddb.netwww.orientdb.com/­docs/­last/­index.html
DeveloperApache Software FoundationCognitectToshiba CorporationOrientDB LTD; CallidusCloud; SAP
Initial release2014201220132010
Current release5.0-HBase2, July 2018 and 4.15-HBase1, December 20191.0.6735, June 20235.1, August 20223.2.29, March 2024
License infoCommercial or Open SourceOpen Source infoApache Version 2.0commercial infolimited edition freeOpen Source infoAGPL version 3 and Apache License, version 2.0 , commercial license (standard and advanced editions) also availableOpen Source infoApache version 2
Cloud-based only infoOnly available as a cloud servicenononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaJava, ClojureC++Java
Server operating systemsLinux
Unix
Windows
All OS with a Java VMLinuxAll OS with a Java JDK (>= JDK 6)
Data schemeyes infolate-bound, schema-on-read capabilitiesyesyesschema-free infoSchema can be enforced for whole record ("schema-full") or for some fields only ("schema-hybrid")
Typing infopredefined data types such as float or dateyesyesyes infonumerical, string, blob, geometry, boolean, timestampyes
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 indexesyesyesyesyes
SQL infoSupport of SQLyesnoSQL92, SQL-like TQL (Toshiba Query Language)SQL-like query language, no joins
APIs and other access methodsJDBCRESTful HTTP APIJDBC
ODBC
Proprietary protocol
RESTful HTTP/JSON API
Tinkerpop technology stack with Blueprints, Gremlin, Pipes
Java API
RESTful HTTP/JSON API
Supported programming languagesC
C#
C++
Go
Groovy
Java
PHP
Python
Scala
Clojure
Java
C
C++
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
Ruby
.Net
C
C#
C++
Clojure
Java
JavaScript
JavaScript (Node.js)
PHP
Python
Ruby
Scala
Server-side scripts infoStored proceduresuser defined functionsyes infoTransaction FunctionsnoJava, Javascript
TriggersnoBy using transaction functionsyesHooks
Partitioning methods infoMethods for storing different data on different nodesShardingnone infoBut extensive use of caching in the application peersShardingSharding
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication
Source-replica replication
none infoBut extensive use of caching in the application peersSource-replica replicationMulti-source replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsHadoop integrationnoConnector for using GridDB as an input source and output destination for Hadoop MapReduce jobsno infocould be achieved with distributed queries
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate Consistency or Eventual ConsistencyImmediate ConsistencyImmediate consistency within container, eventual consistency across containers
Foreign keys infoReferential integritynononoyes inforelationship in graphs
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACIDACID at container levelACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyes infousing external storage systems (e.g. Cassandra, DynamoDB, PostgreSQL, Couchbase and others)yesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesyes inforecommended only for testing and developmentyes
User concepts infoAccess controlAccess Control Lists (using HBase ACL) for RBAC, integration with Apache Ranger for RBAC & ABAC, multi-tenancynoAccess rights for users can be defined per databaseAccess rights for users and roles; record level security configurable
More information provided by the system vendor
Apache PhoenixDatomicGridDBOrientDB
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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and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.

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Apache PhoenixDatomicGridDBOrientDB
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