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DBMS > Amazon DocumentDB vs. Sphinx

System Properties Comparison Amazon DocumentDB vs. Sphinx

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Our visitors often compare Amazon DocumentDB and Sphinx with Elasticsearch, OpenSearch and Redis.

Editorial information provided by DB-Engines
NameAmazon DocumentDB  Xexclude from comparisonSphinx  Xexclude from comparison
DescriptionFast, scalable, highly available, and fully managed MongoDB-compatible database serviceOpen source search engine for searching in data from different sources, e.g. relational databases
Primary database modelDocument storeSearch engine
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.88
Rank#124  Overall
#22  Document stores
Score5.92
Rank#58  Overall
#6  Search engines
Websiteaws.amazon.com/­documentdbsphinxsearch.com
Technical documentationaws.amazon.com/­documentdb/­resourcessphinxsearch.com/­docs
DeveloperSphinx Technologies Inc.
Initial release20192001
Current release3.5.1, February 2023
License infoCommercial or Open SourcecommercialOpen Source infoGPL version 2, commercial licence available
Cloud-based only infoOnly available as a cloud serviceyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC++
Server operating systemshostedFreeBSD
Linux
NetBSD
OS X
Solaris
Windows
Data schemeschema-freeyes
Typing infopredefined data types such as float or dateyesno
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 indexesyesyes infofull-text index on all search fields
SQL infoSupport of SQLnoSQL-like query language (SphinxQL)
APIs and other access methodsproprietary protocol using JSON (MongoDB compatible)Proprietary protocol
Supported programming languagesGo
Java
JavaScript (Node.js)
PHP
Python
C++ infounofficial client library
Java
Perl infounofficial client library
PHP
Python
Ruby infounofficial client library
Server-side scripts infoStored proceduresnono
Triggersnono
Partitioning methods infoMethods for storing different data on different nodesnoneSharding infoPartitioning is done manually, search queries against distributed index is supported
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-availability zones for high availability, asynchronous replication for up to 15 read replicasnone
MapReduce infoOffers an API for user-defined Map/Reduce methodsno infomay be implemented via Amazon Elastic MapReduce (Amazon EMR)no
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate Consistency
Foreign keys infoReferential integrityno infotypically not used, however similar functionality with DBRef possibleno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataAtomic single-document operationsno
Concurrency infoSupport for concurrent manipulation of datayesyes
Durability infoSupport for making data persistentyesyes infoThe original contents of fields are not stored in the Sphinx index.
User concepts infoAccess controlAccess rights for users and rolesno

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More resources
Amazon DocumentDBSphinx
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