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DBMS > Hawkular Metrics vs. Hive vs. Sphinx vs. Splice Machine

System Properties Comparison Hawkular Metrics vs. Hive vs. Sphinx vs. Splice Machine

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Editorial information provided by DB-Engines
NameHawkular Metrics  Xexclude from comparisonHive  Xexclude from comparisonSphinx  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.data warehouse software for querying and managing large distributed datasets, built on HadoopOpen source search engine for searching in data from different sources, e.g. relational databasesOpen-Source SQL RDBMS for Operational and Analytical use cases with native Machine Learning, powered by Hadoop and Spark
Primary database modelTime Series DBMSRelational DBMSSearch engineRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.00
Rank#379  Overall
#40  Time Series DBMS
Score61.17
Rank#18  Overall
#12  Relational DBMS
Score5.98
Rank#56  Overall
#5  Search engines
Score0.54
Rank#250  Overall
#114  Relational DBMS
Websitewww.hawkular.orghive.apache.orgsphinxsearch.comsplicemachine.com
Technical documentationwww.hawkular.org/­hawkular-metrics/­docs/­user-guidecwiki.apache.org/­confluence/­display/­Hive/­Homesphinxsearch.com/­docssplicemachine.com/­how-it-works
DeveloperCommunity supported by Red HatApache Software Foundation infoinitially developed by FacebookSphinx Technologies Inc.Splice Machine
Initial release2014201220012014
Current release3.1.3, April 20223.5.1, February 20233.1, March 2021
License infoCommercial or Open SourceOpen Source infoApache 2.0Open Source infoApache Version 2Open Source infoGPL version 2, commercial licence availableOpen 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 languageJavaJavaC++Java
Server operating systemsLinux
OS X
Windows
All OS with a Java VMFreeBSD
Linux
NetBSD
OS X
Solaris
Windows
Linux
OS X
Solaris
Windows
Data schemeschema-freeyesyesyes
Typing infopredefined data types such as float or dateyesyesnoyes
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.no
Secondary indexesnoyesyes infofull-text index on all search fieldsyes
SQL infoSupport of SQLnoSQL-like DML and DDL statementsSQL-like query language (SphinxQL)yes
APIs and other access methodsHTTP RESTJDBC
ODBC
Thrift
Proprietary protocolJDBC
Native Spark Datasource
ODBC
Supported programming languagesGo
Java
Python
Ruby
C++
Java
PHP
Python
C++ infounofficial client library
Java
Perl infounofficial client library
PHP
Python
Ruby infounofficial client library
C#
C++
Java
JavaScript (Node.js)
Python
R
Scala
Server-side scripts infoStored proceduresnoyes infouser defined functions and integration of map-reducenoyes infoJava
Triggersyes infovia Hawkular Alertingnonoyes
Partitioning methods infoMethods for storing different data on different nodesSharding infobased on CassandraShardingSharding infoPartitioning is done manually, search queries against distributed index is supportedShared Nothhing Auto-Sharding, Columnar Partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factor infobased on Cassandraselectable replication factornoneMulti-source replication
Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyes infoquery execution via MapReducenoYes, via Full Spark Integration
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual Consistency infobased on Cassandra
Immediate Consistency infobased on Cassandra
Eventual ConsistencyImmediate Consistency
Foreign keys infoReferential integritynononoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanononoACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes, multi-version concurrency control (MVCC)
Durability infoSupport for making data persistentyesyesyes infoThe original contents of fields are not stored in the Sphinx index.yes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyes
User concepts infoAccess controlnoAccess rights for users, groups and rolesnoAccess rights for users, groups and roles according to SQL-standard

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More resources
Hawkular MetricsHiveSphinxSplice Machine
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