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DBMS > Hawkular Metrics vs. Kdb vs. RRDtool vs. Splice Machine

System Properties Comparison Hawkular Metrics vs. Kdb vs. RRDtool vs. Splice Machine

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Editorial information provided by DB-Engines
NameHawkular Metrics  Xexclude from comparisonKdb  Xexclude from comparisonRRDtool  Xexclude from comparisonSplice Machine  Xexclude from comparison
DescriptionHawkular metrics is the metric storage of the Red Hat sponsored Hawkular monitoring system. It is based on Cassandra.High performance Time Series DBMSIndustry standard data logging and graphing tool for time series data. RRD is an acronym for round-robin database. infoThe data is stored in a circular buffer, thus the system storage footprint remains constant over time.Open-Source SQL RDBMS for Operational and Analytical use cases with native Machine Learning, powered by Hadoop and Spark
Primary database modelTime Series DBMSTime Series DBMS
Vector DBMS
Time Series DBMSRelational DBMS
Secondary database modelsRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.00
Rank#379  Overall
#40  Time Series DBMS
Score7.55
Rank#53  Overall
#3  Time Series DBMS
#1  Vector DBMS
Score1.87
Rank#136  Overall
#11  Time Series DBMS
Score0.54
Rank#250  Overall
#114  Relational DBMS
Websitewww.hawkular.orgkx.comoss.oetiker.ch/­rrdtoolsplicemachine.com
Technical documentationwww.hawkular.org/­hawkular-metrics/­docs/­user-guidecode.kx.comoss.oetiker.ch/­rrdtool/­docsplicemachine.com/­how-it-works
DeveloperCommunity supported by Red HatKx Systems, a division of First Derivatives plcTobias OetikerSplice Machine
Initial release20142000 infokdb was released 2000, kdb+ in 200319992014
Current release3.6, May 20181.8.0, 20223.1, March 2021
License infoCommercial or Open SourceOpen Source infoApache 2.0commercial infofree 32-bit versionOpen Source infoGPL V2 and FLOSSOpen Source infoAGPL 3.0, commercial license available
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 languageJavaqC infoImplementations in Java (e.g. RRD4J) and C# availableJava
Server operating systemsLinux
OS X
Windows
Linux
OS X
Solaris
Windows
HP-UX
Linux
Linux
OS X
Solaris
Windows
Data schemeschema-freeyesyesyes
Typing infopredefined data types such as float or dateyesyesNumeric data onlyyes
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.noyesno infoExporting into and restoring from XML files possible
Secondary indexesnoyes infotable attribute 'grouped'noyes
SQL infoSupport of SQLnoSQL-like query language (q)noyes
APIs and other access methodsHTTP RESTHTTP API
JDBC
Jupyter
Kafka
ODBC
WebSocket
in-process shared library
Pipes
JDBC
Native Spark Datasource
ODBC
Supported programming languagesGo
Java
Python
Ruby
C
C#
C++
Go
J
Java
JavaScript
Lua
MatLab
Perl
PHP
Python
R
Scala
C infowith librrd library
C# infowith a different implementation of RRDTool
Java infowith a different implementation of RRDTool
JavaScript (Node.js) infowith a different implementation of RRDTool
Lua
Perl
PHP infowith a wrapper library
Python
Ruby
C#
C++
Java
JavaScript (Node.js)
Python
R
Scala
Server-side scripts infoStored proceduresnouser defined functionsnoyes infoJava
Triggersyes infovia Hawkular Alertingyes infowith viewsnoyes
Partitioning methods infoMethods for storing different data on different nodesSharding infobased on Cassandrahorizontal partitioningnoneShared Nothhing Auto-Sharding, Columnar Partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factor infobased on CassandraSource-replica replicationnoneMulti-source replication
Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnono infosimilar paradigm used for internal processingnoYes, via Full Spark Integration
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual Consistency infobased on Cassandra
Immediate Consistency infobased on Cassandra
Immediate ConsistencynoneImmediate Consistency
Foreign keys infoReferential integritynoyesnoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanononoACID
Concurrency infoSupport for concurrent manipulation of datayesyesyes infoby using the rrdcached daemonyes, multi-version concurrency control (MVCC)
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.noyesyesyes
User concepts infoAccess controlnorights management via user accountsnoAccess rights for users, groups and roles according to SQL-standard
More information provided by the system vendor
Hawkular MetricsKdbRRDtoolSplice Machine
Specific characteristicsIntegrated columnar database & programming system for streaming, real time and historical...
» more
Competitive advantagesprovides seamless scalability; runs on industry standard server platforms; is top-ranked...
» more
Typical application scenariostick database streaming sensor data massive intelligence applications oil and gas...
» more
Key customersGoldman Sachs Morgan Stanley Merrill Lynch J.P. Morgan Deutsche Bank IEX Securities...
» more
Market metricskdb+ performance and reliability proven by our customers in critical infrastructure...
» more
Licensing and pricing modelsupon request
» more

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Hawkular MetricsKdbRRDtoolSplice Machine
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