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DBMS > Amazon CloudSearch vs. Machbase Neo vs. Spark SQL vs. Sphinx

System Properties Comparison Amazon CloudSearch vs. Machbase Neo vs. Spark SQL vs. Sphinx

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Editorial information provided by DB-Engines
NameAmazon CloudSearch  Xexclude from comparisonMachbase Neo infoFormer name was Infiniflux  Xexclude from comparisonSpark SQL  Xexclude from comparisonSphinx  Xexclude from comparison
DescriptionA hosted search engine service by Amazon with the data stored in Amazons cloudTimeSeries DBMS for AIoT and BigDataSpark SQL is a component on top of 'Spark Core' for structured data processingOpen source search engine for searching in data from different sources, e.g. relational databases
Primary database modelSearch engineTime Series DBMSRelational DBMSSearch engine
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.87
Rank#140  Overall
#12  Search engines
Score0.22
Rank#324  Overall
#29  Time Series DBMS
Score19.15
Rank#33  Overall
#20  Relational DBMS
Score6.03
Rank#60  Overall
#6  Search engines
Websiteaws.amazon.com/­cloudsearchmachbase.comspark.apache.org/­sqlsphinxsearch.com
Technical documentationdocs.aws.amazon.com/­cloudsearchmachbase.com/­dbmsspark.apache.org/­docs/­latest/­sql-programming-guide.htmlsphinxsearch.com/­docs
DeveloperAmazonMachbaseApache Software FoundationSphinx Technologies Inc.
Initial release2012201320142001
Current releaseV8.0, August 20233.5.0 ( 2.13), September 20233.5.1, February 2023
License infoCommercial or Open Sourcecommercialcommercial infofree test version availableOpen Source infoApache 2.0Open Source infoGPL version 2, commercial licence available
Cloud-based only infoOnly available as a cloud serviceyesnonono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageCScalaC++
Server operating systemshostedLinux
macOS
Windows
Linux
OS X
Windows
FreeBSD
Linux
NetBSD
OS X
Solaris
Windows
Data schemeyesyesyesyes
Typing infopredefined data types such as float or dateyesyesyesno
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 indexesyes infoall search fields are automatically indexedyesnoyes infofull-text index on all search fields
SQL infoSupport of SQLnoSQL-like query languageSQL-like DML and DDL statementsSQL-like query language (SphinxQL)
APIs and other access methodsHTTP APIgRPC
HTTP REST
JDBC
MQTT (Message Queue Telemetry Transport)
ODBC
JDBC
ODBC
Proprietary protocol
Supported programming languagesC
C#
C++
Go
Java
JavaScript
PHP infovia ODBC
Python
R infovia ODBC
Scala
Java
Python
R
Scala
C++ infounofficial client library
Java
Perl infounofficial client library
PHP
Python
Ruby infounofficial client library
Server-side scripts infoStored proceduresnononono
Triggersnononono
Partitioning methods infoMethods for storing different data on different nodesyes infoautomatic partitioning across Amazon Search Instance as requiredShardingyes, utilizing Spark CoreSharding infoPartitioning is done manually, search queries against distributed index is supported
Replication methods infoMethods for redundantly storing data on multiple nodesyes infomanaged transparently by AWSselectable replication factornonenone
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonono
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 persistentyesnoyesyes 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.yes infovolatile and lookup tableno
User concepts infoAccess controlauthentication via encrypted signaturessimple password-based access controlnono

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More resources
Amazon CloudSearchMachbase Neo infoFormer name was InfinifluxSpark SQLSphinx
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