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DBMS > Apache Druid vs. Hawkular Metrics vs. Microsoft Azure Table Storage vs. Warp 10

System Properties Comparison Apache Druid vs. Hawkular Metrics vs. Microsoft Azure Table Storage vs. Warp 10

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Editorial information provided by DB-Engines
NameApache Druid  Xexclude from comparisonHawkular Metrics  Xexclude from comparisonMicrosoft Azure Table Storage  Xexclude from comparisonWarp 10  Xexclude from comparison
DescriptionOpen-source analytics data store designed for sub-second OLAP queries on high dimensionality and high cardinality dataHawkular metrics is the metric storage of the Red Hat sponsored Hawkular monitoring system. It is based on Cassandra.A Wide Column Store for rapid development using massive semi-structured datasetsTimeSeries DBMS specialized on timestamped geo data based on LevelDB or HBase
Primary database modelRelational DBMS
Time Series DBMS
Time Series DBMSWide column storeTime Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score3.29
Rank#95  Overall
#49  Relational DBMS
#7  Time Series DBMS
Score0.04
Rank#374  Overall
#38  Time Series DBMS
Score4.92
Rank#73  Overall
#6  Wide column stores
Score0.08
Rank#358  Overall
#35  Time Series DBMS
Websitedruid.apache.orgwww.hawkular.orgazure.microsoft.com/­en-us/­services/­storage/­tableswww.warp10.io
Technical documentationdruid.apache.org/­docs/­latest/­designwww.hawkular.org/­hawkular-metrics/­docs/­user-guidewww.warp10.io/­content/­02_Getting_started
DeveloperApache Software Foundation and contributorsCommunity supported by Red HatMicrosoftSenX
Initial release2012201420122015
Current release29.0.1, April 2024
License infoCommercial or Open SourceOpen Source infoApache license v2Open Source infoApache 2.0commercialOpen Source infoApache License 2.0
Cloud-based only infoOnly available as a cloud servicenonoyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaJavaJava
Server operating systemsLinux
OS X
Unix
Linux
OS X
Windows
hostedLinux
OS X
Windows
Data schemeyes infoschema-less columns are supportedschema-freeschema-freeschema-free
Typing infopredefined data types such as float or dateyesyesyesyes
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 SQLSQL for queryingnonono
APIs and other access methodsJDBC
RESTful HTTP/JSON API
HTTP RESTRESTful HTTP APIHTTP API
Jupyter
WebSocket
Supported programming languagesClojure
JavaScript
PHP
Python
R
Ruby
Scala
Go
Java
Python
Ruby
.Net
C#
C++
Java
JavaScript (Node.js)
PHP
Python
Ruby
Server-side scripts infoStored proceduresnononoyes infoWarpScript
Triggersnoyes infovia Hawkular Alertingnono
Partitioning methods infoMethods for storing different data on different nodesSharding infomanual/auto, time-basedSharding infobased on CassandraSharding infoImplicit feature of the cloud serviceSharding infobased on HBase
Replication methods infoMethods for redundantly storing data on multiple nodesyes, via HDFS, S3 or other storage enginesselectable replication factor infobased on Cassandrayes infoimplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.selectable replication factor infobased on HBase
MapReduce infoOffers an API for user-defined Map/Reduce methodsnononono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyEventual Consistency infobased on Cassandra
Immediate Consistency infobased on Cassandra
Immediate ConsistencyImmediate Consistency infobased on HBase
Foreign keys infoReferential integritynononono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanonooptimistic lockingno
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.nononoyes
User concepts infoAccess controlRBAC using LDAP or Druid internals for users and groups for read/write by datasource and systemnoAccess rights based on private key authentication or shared access signaturesMandatory use of cryptographic tokens, containing fine-grained authorizations

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More resources
Apache DruidHawkular MetricsMicrosoft Azure Table StorageWarp 10
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