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DBMS > Amazon Neptune vs. mSQL vs. Solr vs. Spark SQL vs. Sphinx

System Properties Comparison Amazon Neptune vs. mSQL vs. Solr vs. Spark SQL vs. Sphinx

Editorial information provided by DB-Engines
NameAmazon Neptune  Xexclude from comparisonmSQL infoMini SQL  Xexclude from comparisonSolr  Xexclude from comparisonSpark SQL  Xexclude from comparisonSphinx  Xexclude from comparison
DescriptionFast, reliable graph database built for the cloudmSQL (Mini SQL) is a simple and lightweight RDBMSA widely used distributed, scalable search engine based on Apache LuceneSpark 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 DBMSSearch engineRelational DBMSSearch engine
Secondary database modelsSpatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score2.58
Rank#112  Overall
#9  Graph DBMS
#5  RDF stores
Score1.67
Rank#151  Overall
#70  Relational DBMS
Score44.28
Rank#24  Overall
#3  Search engines
Score19.15
Rank#33  Overall
#20  Relational DBMS
Score6.03
Rank#60  Overall
#6  Search engines
Websiteaws.amazon.com/­neptunehughestech.com.au/­products/­msqlsolr.apache.orgspark.apache.org/­sqlsphinxsearch.com
Technical documentationaws.amazon.com/­neptune/­developer-resourcessolr.apache.org/­resources.htmlspark.apache.org/­docs/­latest/­sql-programming-guide.htmlsphinxsearch.com/­docs
DeveloperAmazonHughes TechnologiesApache Software FoundationApache Software FoundationSphinx Technologies Inc.
Initial release20171994200620142001
Current release4.4, October 20219.5.0, February 20243.5.0 ( 2.13), September 20233.5.1, February 2023
License infoCommercial or Open Sourcecommercialcommercial infofree licenses can be providedOpen Source infoApache Version 2Open Source infoApache 2.0Open Source infoGPL version 2, commercial licence available
Cloud-based only infoOnly available as a cloud serviceyesnononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageCJavaScalaC++
Server operating systemshostedAIX
HP-UX
Linux
OS X
Solaris SPARC/x86
Windows
All OS with a Java VM inforuns as a servlet in servlet container (e.g. Tomcat, Jetty is included)Linux
OS X
Windows
FreeBSD
Linux
NetBSD
OS X
Solaris
Windows
Data schemeschema-freeyesyes infoDynamic Fields enables on-the-fly addition of new fieldsyesyes
Typing infopredefined data types such as float or dateyesyesyes infosupports customizable data types and automatic typingyesno
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.nonoyesno
Secondary indexesnoyesyes infoAll search fields are automatically indexednoyes infofull-text index on all search fields
SQL infoSupport of SQLnoA subset of ANSI SQL is implemented infono subqueries, aggregate functions, views, foreign keys, triggersSolr Parallel SQL InterfaceSQL-like DML and DDL statementsSQL-like query language (SphinxQL)
APIs and other access methodsOpenCypher
RDF 1.1 / SPARQL 1.1
TinkerPop Gremlin
JDBC
ODBC
Java API
RESTful HTTP/JSON API
JDBC
ODBC
Proprietary protocol
Supported programming languagesC#
Go
Java
JavaScript
PHP
Python
Ruby
Scala
C
C++
Delphi
Java
Perl
PHP
Tcl
.Net
Erlang
Java
JavaScript
any language that supports sockets and either XML or JSON
Perl
PHP
Python
Ruby
Scala
Java
Python
R
Scala
C++ infounofficial client library
Java
Perl infounofficial client library
PHP
Python
Ruby infounofficial client library
Server-side scripts infoStored proceduresnonoJava pluginsnono
Triggersnonoyes infoUser configurable commands triggered on index changesnono
Partitioning methods infoMethods for storing different data on different nodesnonenoneShardingyes, 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 replicas within a single region. Global database clusters consists of a primary write DB cluster in one region, and up to five secondary read DB clusters in different regions. Each secondary region can have up to 16 reader instances.noneyesnonenone
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonospark-solr: github.com/­lucidworks/­spark-solr and streaming expressions to reduceno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencynoneEventual Consistency
Foreign keys infoReferential integrityyes infoRelationships in graphsnononono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDnooptimistic lockingnono
Concurrency infoSupport for concurrent manipulation of datayesnoyesyesyes
Durability infoSupport for making data persistentyes infowith encyption-at-restyesyesyesyes 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.noyesno
User concepts infoAccess controlAccess rights for users and roles can be defined via the AWS Identity and Access Management (IAM)noyesnono

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More resources
Amazon NeptunemSQL infoMini SQLSolrSpark SQLSphinx
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