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DBMS > Apache Phoenix vs. Derby vs. GridDB vs. Hawkular Metrics

System Properties Comparison Apache Phoenix vs. Derby vs. GridDB vs. Hawkular Metrics

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Editorial information provided by DB-Engines
NameApache Phoenix  Xexclude from comparisonDerby infooften called Apache Derby, originally IBM Cloudscape; contained in the Java SDK as JavaDB  Xexclude from comparisonGridDB  Xexclude from comparisonHawkular Metrics  Xexclude from comparison
DescriptionA scale-out RDBMS with evolutionary schema built on Apache HBaseFull-featured RDBMS with a small footprint, either embedded into a Java application or used as a database server.Scalable in-memory time series database optimized for IoT and Big DataHawkular metrics is the metric storage of the Red Hat sponsored Hawkular monitoring system. It is based on Cassandra.
Primary database modelRelational DBMSRelational DBMSTime Series DBMSTime Series DBMS
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
Score4.71
Rank#69  Overall
#37  Relational DBMS
Score1.95
Rank#128  Overall
#10  Time Series DBMS
Score0.00
Rank#379  Overall
#40  Time Series DBMS
Websitephoenix.apache.orgdb.apache.org/­derbygriddb.netwww.hawkular.org
Technical documentationphoenix.apache.orgdb.apache.org/­derby/­manuals/­index.htmldocs.griddb.netwww.hawkular.org/­hawkular-metrics/­docs/­user-guide
DeveloperApache Software FoundationApache Software FoundationToshiba CorporationCommunity supported by Red Hat
Initial release2014199720132014
Current release5.0-HBase2, July 2018 and 4.15-HBase1, December 201910.17.1.0, November 20235.1, August 2022
License infoCommercial or Open SourceOpen Source infoApache Version 2.0Open Source infoApache version 2Open Source infoAGPL version 3 and Apache License, version 2.0 , commercial license (standard and advanced editions) also availableOpen Source infoApache 2.0
Cloud-based only infoOnly available as a cloud servicenononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaJavaC++Java
Server operating systemsLinux
Unix
Windows
All OS with a Java VMLinuxLinux
OS X
Windows
Data schemeyes infolate-bound, schema-on-read capabilitiesyesyesschema-free
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.noyesnono
Secondary indexesyesyesyesno
SQL infoSupport of SQLyesyesSQL92, SQL-like TQL (Toshiba Query Language)no
APIs and other access methodsJDBCJDBCJDBC
ODBC
Proprietary protocol
RESTful HTTP/JSON API
HTTP REST
Supported programming languagesC
C#
C++
Go
Groovy
Java
PHP
Python
Scala
JavaC
C++
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
Ruby
Go
Java
Python
Ruby
Server-side scripts infoStored proceduresuser defined functionsJava Stored Proceduresnono
Triggersnoyesyesyes infovia Hawkular Alerting
Partitioning methods infoMethods for storing different data on different nodesShardingnoneShardingSharding infobased on Cassandra
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication
Source-replica replication
Source-replica replicationSource-replica replicationselectable replication factor infobased on Cassandra
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
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate Consistency or Eventual ConsistencyImmediate ConsistencyImmediate consistency within container, eventual consistency across containersEventual Consistency infobased on Cassandra
Immediate Consistency infobased on Cassandra
Foreign keys infoReferential integritynoyesnono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACIDACID at container levelno
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.yesyesyesno
User concepts infoAccess controlAccess Control Lists (using HBase ACL) for RBAC, integration with Apache Ranger for RBAC & ABAC, multi-tenancyfine grained access rights according to SQL-standardAccess rights for users can be defined per databaseno
More information provided by the system vendor
Apache PhoenixDerby infooften called Apache Derby, originally IBM Cloudscape; contained in the Java SDK as JavaDBGridDBHawkular Metrics
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
Apache PhoenixDerby infooften called Apache Derby, originally IBM Cloudscape; contained in the Java SDK as JavaDBGridDBHawkular Metrics
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