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DBMS > Hawkular Metrics vs. Microsoft Azure AI Search vs. Sphinx

System Properties Comparison Hawkular Metrics vs. Microsoft Azure AI Search vs. Sphinx

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Editorial information provided by DB-Engines
NameHawkular Metrics  Xexclude from comparisonMicrosoft Azure AI Search  Xexclude from comparisonSphinx  Xexclude from comparison
DescriptionHawkular metrics is the metric storage of the Red Hat sponsored Hawkular monitoring system. It is based on Cassandra.Search-as-a-service for web and mobile app developmentOpen source search engine for searching in data from different sources, e.g. relational databases
Primary database modelTime Series DBMSSearch engineSearch engine
Secondary database modelsVector DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.00
Rank#379  Overall
#40  Time Series DBMS
Score5.59
Rank#63  Overall
#7  Search engines
Score5.98
Rank#56  Overall
#5  Search engines
Websitewww.hawkular.orgazure.microsoft.com/­en-us/­services/­searchsphinxsearch.com
Technical documentationwww.hawkular.org/­hawkular-metrics/­docs/­user-guidelearn.microsoft.com/­en-us/­azure/­searchsphinxsearch.com/­docs
DeveloperCommunity supported by Red HatMicrosoftSphinx Technologies Inc.
Initial release201420152001
Current releaseV13.5.1, February 2023
License infoCommercial or Open SourceOpen Source infoApache 2.0commercialOpen Source infoGPL version 2, commercial licence available
Cloud-based only infoOnly available as a cloud servicenoyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJavaC++
Server operating systemsLinux
OS X
Windows
hostedFreeBSD
Linux
NetBSD
OS X
Solaris
Windows
Data schemeschema-freeyesyes
Typing infopredefined data types such as float or dateyesyesno
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
Secondary indexesnoyesyes infofull-text index on all search fields
SQL infoSupport of SQLnonoSQL-like query language (SphinxQL)
APIs and other access methodsHTTP RESTRESTful HTTP APIProprietary protocol
Supported programming languagesGo
Java
Python
Ruby
C#
Java
JavaScript
Python
C++ infounofficial client library
Java
Perl infounofficial client library
PHP
Python
Ruby infounofficial client library
Server-side scripts infoStored proceduresnonono
Triggersyes infovia Hawkular Alertingnono
Partitioning methods infoMethods for storing different data on different nodesSharding infobased on CassandraSharding infoImplicit feature of the cloud serviceSharding infoPartitioning is done manually, search queries against distributed index is supported
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factor infobased on Cassandrayes infoImplicit feature of the cloud servicenone
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
Immediate Consistency
Foreign keys infoReferential integritynonono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanonono
Concurrency infoSupport for concurrent manipulation of datayesyesyes
Durability infoSupport for making data persistentyesyesyes infoThe original contents of fields are not stored in the Sphinx index.
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.nono
User concepts infoAccess controlnoyes infousing Azure authenticationno

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More resources
Hawkular MetricsMicrosoft Azure AI SearchSphinx
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