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DBMS > Apache Druid vs. FatDB vs. GridDB vs. Hawkular Metrics

System Properties Comparison Apache Druid vs. FatDB vs. GridDB vs. Hawkular Metrics

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Editorial information provided by DB-Engines
NameApache Druid  Xexclude from comparisonFatDB  Xexclude from comparisonGridDB  Xexclude from comparisonHawkular Metrics  Xexclude from comparison
FatDB/FatCloud has ceased operations as a company with February 2014. FatDB is discontinued and excluded from the ranking.
DescriptionOpen-source analytics data store designed for sub-second OLAP queries on high dimensionality and high cardinality dataA .NET NoSQL DBMS that can integrate with and extend SQL 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 DBMS
Time Series DBMS
Document store
Key-value store
Time Series DBMSTime Series DBMS
Secondary database modelsKey-value store
Relational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score3.34
Rank#88  Overall
#48  Relational DBMS
#7  Time Series DBMS
Score1.95
Rank#128  Overall
#10  Time Series DBMS
Score0.00
Rank#379  Overall
#40  Time Series DBMS
Websitedruid.apache.orggriddb.netwww.hawkular.org
Technical documentationdruid.apache.org/­docs/­latest/­designdocs.griddb.netwww.hawkular.org/­hawkular-metrics/­docs/­user-guide
DeveloperApache Software Foundation and contributorsFatCloudToshiba CorporationCommunity supported by Red Hat
Initial release2012201220132014
Current release29.0.1, April 20245.1, August 2022
License infoCommercial or Open SourceOpen Source infoApache license v2commercialOpen 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 languageJavaC#C++Java
Server operating systemsLinux
OS X
Unix
WindowsLinuxLinux
OS X
Windows
Data schemeyes infoschema-less columns are supportedschema-freeyesschema-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.nonono
Secondary indexesyesyesyesno
SQL infoSupport of SQLSQL for queryingno infoVia inetgration in SQL ServerSQL92, SQL-like TQL (Toshiba Query Language)no
APIs and other access methodsJDBC
RESTful HTTP/JSON API
.NET Client API
LINQ
RESTful HTTP API
RPC
Windows WCF Bindings
JDBC
ODBC
Proprietary protocol
RESTful HTTP/JSON API
HTTP REST
Supported programming languagesClojure
JavaScript
PHP
Python
R
Ruby
Scala
C#C
C++
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
Ruby
Go
Java
Python
Ruby
Server-side scripts infoStored proceduresnoyes infovia applicationsnono
Triggersnoyes infovia applicationsyesyes infovia Hawkular Alerting
Partitioning methods infoMethods for storing different data on different nodesSharding infomanual/auto, time-basedShardingShardingSharding infobased on Cassandra
Replication methods infoMethods for redundantly storing data on multiple nodesyes, via HDFS, S3 or other storage enginesselectable replication factorSource-replica replicationselectable replication factor infobased on Cassandra
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyesConnector for using GridDB as an input source and output destination for Hadoop MapReduce jobsno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyEventual Consistency
Immediate Consistency
Immediate consistency within container, eventual consistency across containersEventual Consistency infobased on Cassandra
Immediate Consistency infobased on Cassandra
Foreign keys infoReferential integritynononono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanonoACID 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.noyesno
User concepts infoAccess controlRBAC using LDAP or Druid internals for users and groups for read/write by datasource and systemno infoCan implement custom security layer via applicationsAccess rights for users can be defined per databaseno
More information provided by the system vendor
Apache DruidFatDBGridDBHawkular 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 DruidFatDBGridDBHawkular Metrics
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