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DBMS > Memcached vs. Microsoft Azure Data Explorer vs. SiteWhere vs. Sphinx

System Properties Comparison Memcached vs. Microsoft Azure Data Explorer vs. SiteWhere vs. Sphinx

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Editorial information provided by DB-Engines
NameMemcached  Xexclude from comparisonMicrosoft Azure Data Explorer  Xexclude from comparisonSiteWhere  Xexclude from comparisonSphinx  Xexclude from comparison
DescriptionIn-memory key-value store, originally intended for cachingFully managed big data interactive analytics platformM2M integration platform for persisting/querying time series dataOpen source search engine for searching in data from different sources, e.g. relational databases
Primary database modelKey-value storeRelational DBMS infocolumn orientedTime Series DBMSSearch engine
Secondary database modelsDocument store infoIf a column is of type dynamic docs.microsoft.com/­en-us/­azure/­kusto/­query/­scalar-data-types/­dynamic then it's possible to add arbitrary JSON documents in this cell
Event Store infothis is the general usage pattern at Microsoft. Billing, Logs, Telemetry events are stored in ADX and the state of an individual entity is defined by the arg_max(timestamps)
Spatial DBMS
Search engine infosupport for complex search expressions docs.microsoft.com/­en-us/­azure/­kusto/­query/­parseoperator FTS, Geospatial docs.microsoft.com/­en-us/­azure/­kusto/­query/­geo-point-to-geohash-function distributed search -> ADX acts as a distributed search engine
Time Series DBMS infosee docs.microsoft.com/­en-us/­azure/­data-explorer/­time-series-analysis
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score19.42
Rank#32  Overall
#4  Key-value stores
Score4.38
Rank#77  Overall
#41  Relational DBMS
Score0.06
Rank#356  Overall
#35  Time Series DBMS
Score5.98
Rank#56  Overall
#5  Search engines
Websitewww.memcached.orgazure.microsoft.com/­services/­data-explorergithub.com/­sitewhere/­sitewheresphinxsearch.com
Technical documentationgithub.com/­memcached/­memcached/­wikidocs.microsoft.com/­en-us/­azure/­data-explorersitewhere1.sitewhere.io/­index.htmlsphinxsearch.com/­docs
DeveloperDanga Interactive infooriginally developed by Brad Fitzpatrick for LiveJournalMicrosoftSiteWhereSphinx Technologies Inc.
Initial release2003201920102001
Current release1.6.27, May 2024cloud service with continuous releases3.5.1, February 2023
License infoCommercial or Open SourceOpen Source infoBSD licensecommercialOpen Source infoCommon Public Attribution License Version 1.0Open Source infoGPL version 2, commercial licence available
Cloud-based only infoOnly available as a cloud servicenoyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageCJavaC++
Server operating systemsFreeBSD
Linux
OS X
Unix
Windows
hostedLinux
OS X
Windows
FreeBSD
Linux
NetBSD
OS X
Solaris
Windows
Data schemeschema-freeFixed schema with schema-less datatypes (dynamic)predefined schemeyes
Typing infopredefined data types such as float or datenoyes infobool, datetime, dynamic, guid, int, long, real, string, timespan, double: docs.microsoft.com/­en-us/­azure/­kusto/­query/­scalar-data-typesyesno
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.yesno
Secondary indexesnoall fields are automatically indexednoyes infofull-text index on all search fields
SQL infoSupport of SQLnoKusto Query Language (KQL), SQL subsetnoSQL-like query language (SphinxQL)
APIs and other access methodsProprietary protocolMicrosoft SQL Server communication protocol (MS-TDS)
RESTful HTTP API
HTTP RESTProprietary protocol
Supported programming languages.Net
C
C++
ColdFusion
Erlang
Java
Lisp
Lua
OCaml
Perl
PHP
Python
Ruby
.Net
Go
Java
JavaScript (Node.js)
PowerShell
Python
R
C++ infounofficial client library
Java
Perl infounofficial client library
PHP
Python
Ruby infounofficial client library
Server-side scripts infoStored proceduresnoYes, possible languages: KQL, Python, Rno
Triggersnoyes infosee docs.microsoft.com/­en-us/­azure/­kusto/­management/­updatepolicyno
Partitioning methods infoMethods for storing different data on different nodesnoneSharding infoImplicit feature of the cloud serviceSharding infobased on HBaseSharding infoPartitioning is done manually, search queries against distributed index is supported
Replication methods infoMethods for redundantly storing data on multiple nodesnone infoRepcached, a Memcached patch, provides this functionallityyes infoImplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.selectable replication factor infobased on HBasenone
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoSpark connector (open source): github.com/­Azure/­azure-kusto-sparknono
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual Consistency
Immediate Consistency
Immediate Consistency
Foreign keys infoReferential integritynononono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanononono
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentnoyesyesyes 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 controlyes infousing SASL (Simple Authentication and Security Layer) protocolAzure Active Directory AuthenticationUsers with fine-grained authorization conceptno

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More resources
MemcachedMicrosoft Azure Data ExplorerSiteWhereSphinx
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