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DBMS > GridDB vs. Hawkular Metrics vs. HBase vs. Warp 10

System Properties Comparison GridDB vs. Hawkular Metrics vs. HBase vs. Warp 10

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Editorial information provided by DB-Engines
NameGridDB  Xexclude from comparisonHawkular Metrics  Xexclude from comparisonHBase  Xexclude from comparisonWarp 10  Xexclude from comparison
DescriptionScalable 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.Wide-column store based on Apache Hadoop and on concepts of BigTableTimeSeries DBMS specialized on timestamped geo data based on LevelDB or HBase
Primary database modelTime Series DBMSTime Series DBMSWide column storeTime Series DBMS
Secondary database modelsKey-value store
Relational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.95
Rank#128  Overall
#10  Time Series DBMS
Score0.00
Rank#379  Overall
#40  Time Series DBMS
Score30.50
Rank#26  Overall
#2  Wide column stores
Score0.07
Rank#349  Overall
#32  Time Series DBMS
Websitegriddb.netwww.hawkular.orghbase.apache.orgwww.warp10.io
Technical documentationdocs.griddb.netwww.hawkular.org/­hawkular-metrics/­docs/­user-guidehbase.apache.org/­book.htmlwww.warp10.io/­content/­02_Getting_started
DeveloperToshiba CorporationCommunity supported by Red HatApache Software Foundation infoApache top-level project, originally developed by PowersetSenX
Initial release2013201420082015
Current release5.1, August 20222.3.4, January 2021
License infoCommercial or Open SourceOpen Source infoAGPL version 3 and Apache License, version 2.0 , commercial license (standard and advanced editions) also availableOpen Source infoApache 2.0Open Source infoApache version 2Open Source infoApache License 2.0
Cloud-based only infoOnly available as a cloud servicenononono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageC++JavaJavaJava
Server operating systemsLinuxLinux
OS X
Windows
Linux
Unix
Windows infousing Cygwin
Linux
OS X
Windows
Data schemeyesschema-freeschema-free, schema definition possibleschema-free
Typing infopredefined data types such as float or dateyes infonumerical, string, blob, geometry, boolean, timestampyesoptions to bring your own types, AVROyes
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 indexesyesnonono
SQL infoSupport of SQLSQL92, SQL-like TQL (Toshiba Query Language)nonono
APIs and other access methodsJDBC
ODBC
Proprietary protocol
RESTful HTTP/JSON API
HTTP RESTJava API
RESTful HTTP API
Thrift
HTTP API
Jupyter
WebSocket
Supported programming languagesC
C++
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
Ruby
Go
Java
Python
Ruby
C
C#
C++
Groovy
Java
PHP
Python
Scala
Server-side scripts infoStored proceduresnonoyes infoCoprocessors in Javayes infoWarpScript
Triggersyesyes infovia Hawkular Alertingyesno
Partitioning methods infoMethods for storing different data on different nodesShardingSharding infobased on CassandraShardingSharding infobased on HBase
Replication methods infoMethods for redundantly storing data on multiple nodesSource-replica replicationselectable replication factor infobased on CassandraMulti-source replication
Source-replica replication
selectable replication factor infobased on HBase
MapReduce infoOffers an API for user-defined Map/Reduce methodsConnector for using GridDB as an input source and output destination for Hadoop MapReduce jobsnoyesno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate consistency within container, eventual consistency across containersEventual Consistency infobased on Cassandra
Immediate Consistency infobased on Cassandra
Immediate Consistency or Eventual ConsistencyImmediate Consistency infobased on HBase
Foreign keys infoReferential integritynononono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACID at container levelnoSingle row ACID (across millions of columns)no
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.yesnoyesyes
User concepts infoAccess controlAccess rights for users can be defined per databasenoAccess Control Lists (ACL) for RBAC, integration with Apache Ranger for RBAC & ABACMandatory use of cryptographic tokens, containing fine-grained authorizations
More information provided by the system vendor
GridDBHawkular MetricsHBaseWarp 10
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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GridDBHawkular MetricsHBaseWarp 10
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