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DBMS > Amazon DocumentDB vs. Coveo vs. Kyligence Enterprise vs. Spark SQL vs. Sphinx

System Properties Comparison Amazon DocumentDB vs. Coveo vs. Kyligence Enterprise vs. Spark SQL vs. Sphinx

Editorial information provided by DB-Engines
NameAmazon DocumentDB  Xexclude from comparisonCoveo  Xexclude from comparisonKyligence Enterprise  Xexclude from comparisonSpark SQL  Xexclude from comparisonSphinx  Xexclude from comparison
DescriptionFast, scalable, highly available, and fully managed MongoDB-compatible database serviceAI-powered hosted search, recommendation and personalization platform providing tools for both low-code and full-code developmentA distributed analytics engine for big data, built on top of Apache KylinSpark 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 modelDocument storeSearch engineRelational DBMSRelational DBMSSearch engine
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.91
Rank#131  Overall
#24  Document stores
Score2.11
Rank#118  Overall
#11  Search engines
Score0.46
Rank#266  Overall
#124  Relational DBMS
Score18.04
Rank#33  Overall
#20  Relational DBMS
Score5.95
Rank#55  Overall
#5  Search engines
Websiteaws.amazon.com/­documentdbwww.coveo.comkyligence.io/­kyligence-enterprisespark.apache.org/­sqlsphinxsearch.com
Technical documentationaws.amazon.com/­documentdb/­resourcesdocs.coveo.comspark.apache.org/­docs/­latest/­sql-programming-guide.htmlsphinxsearch.com/­docs
DeveloperCoveoKyligence, Inc.Apache Software FoundationSphinx Technologies Inc.
Initial release20192012201620142001
Current release3.5.0 ( 2.13), September 20233.5.1, February 2023
License infoCommercial or Open SourcecommercialcommercialcommercialOpen Source infoApache 2.0Open Source infoGPL version 2, commercial licence available
Cloud-based only infoOnly available as a cloud serviceyesyesnonono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaScalaC++
Server operating systemshostedhostedLinuxLinux
OS X
Windows
FreeBSD
Linux
NetBSD
OS X
Solaris
Windows
Data schemeschema-freehybrid - fields need to be configured prior to indexing, but relationships can be exploited at query time without pre-configurationyesyesyes
Typing infopredefined data types such as float or dateyesyesyesyesno
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.nononono
Secondary indexesyesyesyesnoyes infofull-text index on all search fields
SQL infoSupport of SQLnonoANSI SQL for queries (using Apache Calcite)SQL-like DML and DDL statementsSQL-like query language (SphinxQL)
APIs and other access methodsproprietary protocol using JSON (MongoDB compatible)RESTful HTTP APIJDBC
ODBC
RESTful HTTP API
JDBC
ODBC
Proprietary protocol
Supported programming languagesGo
Java
JavaScript (Node.js)
PHP
Python
C#
Java
JavaScript
Python
Java
Python
R
Scala
C++ infounofficial client library
Java
Perl infounofficial client library
PHP
Python
Ruby infounofficial client library
Server-side scripts infoStored proceduresnononono
Triggersnoyesnono
Partitioning methods infoMethods for storing different data on different nodesnoneyesyes, utilizing Spark CoreSharding 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 replicasyesnonenone
MapReduce infoOffers an API for user-defined Map/Reduce methodsno infomay be implemented via Amazon Elastic MapReduce (Amazon EMR)noyesno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integrityno infotypically not used, however similar functionality with DBRef possibleyesnono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataAtomic single-document operationsyesnono
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentyesyesyesyesyes 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 controlAccess rights for users and rolesgranular access controls, API key management, content filtersnono

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More resources
Amazon DocumentDBCoveoKyligence EnterpriseSpark SQLSphinx
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