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DBMS > Hawkular Metrics vs. InterSystems Caché vs. Spark SQL

System Properties Comparison Hawkular Metrics vs. InterSystems Caché vs. Spark SQL

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Editorial information provided by DB-Engines
NameHawkular Metrics  Xexclude from comparisonInterSystems Caché  Xexclude from comparisonSpark SQL  Xexclude from comparison
Caché is a deprecated database engine which is substituted with InterSystems IRIS. It therefore is removed from the DB-Engines Ranking.
DescriptionHawkular metrics is the metric storage of the Red Hat sponsored Hawkular monitoring system. It is based on Cassandra.A multi-model DBMS and application serverSpark SQL is a component on top of 'Spark Core' for structured data processing
Primary database modelTime Series DBMSKey-value store
Object oriented DBMS
Relational DBMS
Relational DBMS
Secondary database modelsDocument store
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.00
Rank#379  Overall
#40  Time Series DBMS
Score18.96
Rank#33  Overall
#20  Relational DBMS
Websitewww.hawkular.orgwww.intersystems.com/­products/­cachespark.apache.org/­sql
Technical documentationwww.hawkular.org/­hawkular-metrics/­docs/­user-guidedocs.intersystems.comspark.apache.org/­docs/­latest/­sql-programming-guide.html
DeveloperCommunity supported by Red HatInterSystemsApache Software Foundation
Initial release201419972014
Current release2018.1.4, May 20203.5.0 ( 2.13), September 2023
License infoCommercial or Open SourceOpen Source infoApache 2.0commercialOpen Source infoApache 2.0
Cloud-based only infoOnly available as a cloud servicenonono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJavaScala
Server operating systemsLinux
OS X
Windows
AIX
HP Open VMS
HP-UX
Linux
OS X
Solaris
Windows
Linux
OS X
Windows
Data schemeschema-freedepending on used data modelyes
Typing infopredefined data types such as float or dateyesyesyes
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
Secondary indexesnoyesno
SQL infoSupport of SQLnoyesSQL-like DML and DDL statements
APIs and other access methodsHTTP REST.NET Client API
JDBC
ODBC
RESTful HTTP API
JDBC
ODBC
Supported programming languagesGo
Java
Python
Ruby
C#
C++
Java
Java
Python
R
Scala
Server-side scripts infoStored proceduresnoyesno
Triggersyes infovia Hawkular Alertingyesno
Partitioning methods infoMethods for storing different data on different nodesSharding infobased on Cassandranoneyes, utilizing Spark Core
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factor infobased on CassandraSource-replica replicationnone
MapReduce infoOffers an API for user-defined Map/Reduce methodsnono
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual Consistency infobased on Cassandra
Immediate Consistency infobased on Cassandra
Immediate Consistency
Foreign keys infoReferential integritynoyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDno
Concurrency infoSupport for concurrent manipulation of datayesyesyes
Durability infoSupport for making data persistentyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyesno
User concepts infoAccess controlnoAccess rights for users, groups and rolesno

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Hawkular MetricsInterSystems CachéSpark SQL
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