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DBMS > Hawkular Metrics vs. Prometheus vs. Spark SQL vs. Warp 10

System Properties Comparison Hawkular Metrics vs. Prometheus vs. Spark SQL vs. Warp 10

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Editorial information provided by DB-Engines
NameHawkular Metrics  Xexclude from comparisonPrometheus  Xexclude from comparisonSpark SQL  Xexclude from comparisonWarp 10  Xexclude from comparison
DescriptionHawkular metrics is the metric storage of the Red Hat sponsored Hawkular monitoring system. It is based on Cassandra.Open-source Time Series DBMS and monitoring systemSpark SQL is a component on top of 'Spark Core' for structured data processingTimeSeries DBMS specialized on timestamped geo data based on LevelDB or HBase
Primary database modelTime Series DBMSTime Series DBMSRelational DBMSTime Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.04
Rank#374  Overall
#38  Time Series DBMS
Score7.92
Rank#51  Overall
#2  Time Series DBMS
Score19.15
Rank#33  Overall
#20  Relational DBMS
Score0.08
Rank#358  Overall
#35  Time Series DBMS
Websitewww.hawkular.orgprometheus.iospark.apache.org/­sqlwww.warp10.io
Technical documentationwww.hawkular.org/­hawkular-metrics/­docs/­user-guideprometheus.io/­docsspark.apache.org/­docs/­latest/­sql-programming-guide.htmlwww.warp10.io/­content/­02_Getting_started
DeveloperCommunity supported by Red HatApache Software FoundationSenX
Initial release2014201520142015
Current release3.5.0 ( 2.13), September 2023
License infoCommercial or Open SourceOpen Source infoApache 2.0Open Source infoApache 2.0Open Source infoApache 2.0Open 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 languageJavaGoScalaJava
Server operating systemsLinux
OS X
Windows
Linux
Windows
Linux
OS X
Windows
Linux
OS X
Windows
Data schemeschema-freeyesyesschema-free
Typing infopredefined data types such as float or dateyesNumeric data onlyyesyes
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.nono infoImport of XML data possiblenono
Secondary indexesnononono
SQL infoSupport of SQLnonoSQL-like DML and DDL statementsno
APIs and other access methodsHTTP RESTRESTful HTTP/JSON APIJDBC
ODBC
HTTP API
Jupyter
WebSocket
Supported programming languagesGo
Java
Python
Ruby
.Net
C++
Go
Haskell
Java
JavaScript (Node.js)
Python
Ruby
Java
Python
R
Scala
Server-side scripts infoStored proceduresnononoyes infoWarpScript
Triggersyes infovia Hawkular Alertingnonono
Partitioning methods infoMethods for storing different data on different nodesSharding infobased on CassandraShardingyes, utilizing Spark CoreSharding infobased on HBase
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factor infobased on Cassandrayes infoby Federationnoneselectable replication factor infobased on HBase
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonono
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual Consistency infobased on Cassandra
Immediate Consistency infobased on Cassandra
noneImmediate Consistency infobased on HBase
Foreign keys infoReferential integritynononono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanononono
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 controlnononoMandatory use of cryptographic tokens, containing fine-grained authorizations

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Hawkular MetricsPrometheusSpark SQLWarp 10
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