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

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

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Editorial information provided by DB-Engines
NameHawkular Metrics  Xexclude from comparisonSphinx  Xexclude from comparisonSplice Machine  Xexclude from comparisonVitess  Xexclude from comparison
DescriptionHawkular metrics is the metric storage of the Red Hat sponsored Hawkular monitoring system. It is based on Cassandra.Open 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 SparkScalable, distributed, cloud-native DBMS, extending MySQL
Primary database modelTime Series DBMSSearch engineRelational DBMSRelational DBMS
Secondary database modelsDocument store
Spatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.00
Rank#379  Overall
#40  Time Series DBMS
Score5.98
Rank#56  Overall
#5  Search engines
Score0.54
Rank#250  Overall
#114  Relational DBMS
Score0.82
Rank#209  Overall
#97  Relational DBMS
Websitewww.hawkular.orgsphinxsearch.comsplicemachine.comvitess.io
Technical documentationwww.hawkular.org/­hawkular-metrics/­docs/­user-guidesphinxsearch.com/­docssplicemachine.com/­how-it-worksvitess.io/­docs
DeveloperCommunity supported by Red HatSphinx Technologies Inc.Splice MachineThe Linux Foundation, PlanetScale
Initial release2014200120142013
Current release3.5.1, February 20233.1, March 202115.0.2, December 2022
License infoCommercial or Open SourceOpen Source infoApache 2.0Open Source infoGPL version 2, commercial licence availableOpen Source infoAGPL 3.0, commercial license availableOpen Source infoApache Version 2.0, commercial licenses 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 languageJavaC++JavaGo
Server operating systemsLinux
OS X
Windows
FreeBSD
Linux
NetBSD
OS X
Solaris
Windows
Linux
OS X
Solaris
Windows
Docker
Linux
macOS
Data schemeschema-freeyesyesyes
Typing infopredefined data types such as float or dateyesnoyesyes
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 indexesnoyes infofull-text index on all search fieldsyesyes
SQL infoSupport of SQLnoSQL-like query language (SphinxQL)yesyes infowith proprietary extensions
APIs and other access methodsHTTP RESTProprietary protocolJDBC
Native Spark Datasource
ODBC
ADO.NET
JDBC
MySQL protocol
ODBC
Supported programming languagesGo
Java
Python
Ruby
C++ infounofficial client library
Java
Perl infounofficial client library
PHP
Python
Ruby infounofficial client library
C#
C++
Java
JavaScript (Node.js)
Python
R
Scala
Ada
C
C#
C++
D
Delphi
Eiffel
Erlang
Haskell
Java
JavaScript (Node.js)
Objective-C
OCaml
Perl
PHP
Python
Ruby
Scheme
Tcl
Server-side scripts infoStored proceduresnonoyes infoJavayes infoproprietary syntax
Triggersyes infovia Hawkular Alertingnoyesyes
Partitioning methods infoMethods for storing different data on different nodesSharding infobased on CassandraSharding infoPartitioning is done manually, search queries against distributed index is supportedShared Nothhing Auto-Sharding, Columnar PartitioningSharding
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factor infobased on CassandranoneMulti-source replication
Source-replica replication
Multi-source replication
Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonoYes, via Full Spark Integrationno
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual Consistency infobased on Cassandra
Immediate Consistency infobased on Cassandra
Immediate ConsistencyEventual Consistency across shards
Immediate Consistency within a shard
Foreign keys infoReferential integritynonoyesyes infonot for MyISAM storage engine
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanonoACIDACID at shard level
Concurrency infoSupport for concurrent manipulation of datayesyesyes, multi-version concurrency control (MVCC)yes infotable locks or row locks depending on storage engine
Durability infoSupport for making data persistentyesyes infoThe original contents of fields are not stored in the Sphinx index.yesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyesyes
User concepts infoAccess controlnonoAccess rights for users, groups and roles according to SQL-standardUsers with fine-grained authorization concept infono user groups or roles

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Hawkular MetricsSphinxSplice MachineVitess
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