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DBMS > Amazon Neptune vs. Cubrid vs. Spark SQL vs. Sphinx

System Properties Comparison Amazon Neptune vs. Cubrid vs. Spark SQL vs. Sphinx

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Editorial information provided by DB-Engines
NameAmazon Neptune  Xexclude from comparisonCubrid  Xexclude from comparisonSpark SQL  Xexclude from comparisonSphinx  Xexclude from comparison
DescriptionFast, reliable graph database built for the cloudCUBRID is an open-source SQL-based relational database management system with object extensions for OLTPSpark 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 modelGraph DBMS
RDF store
Relational DBMSRelational DBMSSearch engine
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score2.56
Rank#109  Overall
#7  Graph DBMS
#5  RDF stores
Score1.13
Rank#163  Overall
#80  Relational DBMS
Score22.97
Rank#34  Overall
#20  Relational DBMS
Score8.01
Rank#56  Overall
#6  Search engines
Websiteaws.amazon.com/­neptunecubrid.com (korean)
cubrid.org (english)
spark.apache.org/­sqlsphinxsearch.com
Technical documentationaws.amazon.com/­neptune/­developer-resourcescubrid.org/­manualsspark.apache.org/­docs/­latest/­sql-programming-guide.htmlsphinxsearch.com/­docs
DeveloperAmazonCUBRID Corporation, CUBRID FoundationApache Software FoundationSphinx Technologies Inc.
Initial release2017200820142001
Current release11.0, January 20213.2.0, October 20213.4.1, July 2021
License infoCommercial or Open SourcecommercialOpen Source infoApache Version 2.0Open 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 languageC, C++, JavaScalaC++
Server operating systemshostedLinux
Windows
Linux
OS X
Windows
FreeBSD
Linux
NetBSD
OS X
Solaris
Windows
Data schemeschema-freeyesyesyes
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.nonono
Secondary indexesnoyesnoyes infofull-text index on all search fields
SQL infoSupport of SQLnoyesSQL-like DML and DDL statementsSQL-like query language (SphinxQL)
APIs and other access methodsRDF 1.1 / SPARQL 1.1
TinkerPop Gremlin 3.3
ADO.NET
JDBC
ODBC
OLE DB
JDBC
ODBC
Proprietary protocol
Supported programming languagesC#
Go
Java
JavaScript
PHP
Python
Ruby
Scala
C
C#
C++
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
Ruby
Java
Python
R
Scala
C++ infounofficial client library
Java
Perl infounofficial client library
PHP
Python
Ruby infounofficial client library
Server-side scripts infoStored proceduresnoJava Stored Proceduresnono
Triggersnoyesnono
Partitioning methods infoMethods for storing different data on different nodesnonenoneyes, 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 high availability, asynchronous replication for up to 15 read replicasSource-replica replicationnonenone
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integrityyes infoRelationships in graphsyesnono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACIDnono
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyes infowith encyption-at-restyesyesyes 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 roles can be defined via the AWS Identity and Access Management (IAM)fine grained access rights according to SQL-standardnono

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More resources
Amazon NeptuneCubridSpark SQLSphinx
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