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DBMS > Amazon CloudSearch vs. Sphinx vs. Splice Machine vs. Ultipa

System Properties Comparison Amazon CloudSearch vs. Sphinx vs. Splice Machine vs. Ultipa

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Editorial information provided by DB-Engines
NameAmazon CloudSearch  Xexclude from comparisonSphinx  Xexclude from comparisonSplice Machine  Xexclude from comparisonUltipa  Xexclude from comparison
DescriptionA hosted search engine service by Amazon with the data stored in Amazons cloudOpen 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 SparkHigh performance Graph DBMS supporting HTAP high availability cluster deployment
Primary database modelSearch engineSearch engineRelational DBMSGraph DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.81
Rank#137  Overall
#12  Search engines
Score5.95
Rank#55  Overall
#5  Search engines
Score0.54
Rank#252  Overall
#115  Relational DBMS
Score0.19
Rank#330  Overall
#30  Graph DBMS
Websiteaws.amazon.com/­cloudsearchsphinxsearch.comsplicemachine.comwww.ultipa.com
Technical documentationdocs.aws.amazon.com/­cloudsearchsphinxsearch.com/­docssplicemachine.com/­how-it-workswww.ultipa.com/­document
DeveloperAmazonSphinx Technologies Inc.Splice MachineUltipa
Initial release2012200120142019
Current release3.5.1, February 20233.1, March 2021
License infoCommercial or Open SourcecommercialOpen Source infoGPL version 2, commercial licence availableOpen Source infoAGPL 3.0, commercial license availablecommercial
Cloud-based only infoOnly available as a cloud serviceyesnonono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageC++Java
Server operating systemshostedFreeBSD
Linux
NetBSD
OS X
Solaris
Windows
Linux
OS X
Solaris
Windows
Data schemeyesyesyes
Typing infopredefined data types such as float or dateyesnoyes
Secondary indexesyes infoall search fields are automatically indexedyes infofull-text index on all search fieldsyes
SQL infoSupport of SQLnoSQL-like query language (SphinxQL)yes
APIs and other access methodsHTTP APIProprietary protocolJDBC
Native Spark Datasource
ODBC
RESTful HTTP API
Supported programming languagesC++ infounofficial client library
Java
Perl infounofficial client library
PHP
Python
Ruby infounofficial client library
C#
C++
Java
JavaScript (Node.js)
Python
R
Scala
C++
Go
Java
JavaScript (Node.js)
Python
Server-side scripts infoStored proceduresnonoyes infoJava
Triggersnonoyes
Partitioning methods infoMethods for storing different data on different nodesyes infoautomatic partitioning across Amazon Search Instance as requiredSharding 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 nodesyes infomanaged transparently by AWSnoneMulti-source replication
Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonoYes, via Full Spark Integration
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate Consistency
Foreign keys infoReferential integritynonoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanonoACID
Concurrency infoSupport for concurrent manipulation of datayesyesyes, multi-version concurrency control (MVCC)
Durability infoSupport for making data persistentyesyes 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.yes
User concepts infoAccess controlauthentication via encrypted signaturesnoAccess rights for users, groups and roles according to SQL-standard

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More resources
Amazon CloudSearchSphinxSplice MachineUltipa
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