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DBMS > Amazon Neptune vs. HugeGraph vs. mSQL vs. Solr vs. Sphinx

System Properties Comparison Amazon Neptune vs. HugeGraph vs. mSQL vs. Solr vs. Sphinx

Editorial information provided by DB-Engines
NameAmazon Neptune  Xexclude from comparisonHugeGraph  Xexclude from comparisonmSQL infoMini SQL  Xexclude from comparisonSolr  Xexclude from comparisonSphinx  Xexclude from comparison
DescriptionFast, reliable graph database built for the cloudA fast-speed and highly-scalable Graph DBMSmSQL (Mini SQL) is a simple and lightweight RDBMSA widely used distributed, scalable search engine based on Apache LuceneOpen source search engine for searching in data from different sources, e.g. relational databases
Primary database modelGraph DBMS
RDF store
Graph DBMSRelational DBMSSearch engineSearch engine
Secondary database modelsSpatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score2.20
Rank#119  Overall
#9  Graph DBMS
#5  RDF stores
Score0.13
Rank#336  Overall
#32  Graph DBMS
Score1.27
Rank#167  Overall
#77  Relational DBMS
Score42.91
Rank#24  Overall
#3  Search engines
Score5.98
Rank#56  Overall
#5  Search engines
Websiteaws.amazon.com/­neptunegithub.com/­hugegraph
hugegraph.apache.org
hughestech.com.au/­products/­msqlsolr.apache.orgsphinxsearch.com
Technical documentationaws.amazon.com/­neptune/­developer-resourceshugegraph.apache.org/­docssolr.apache.org/­resources.htmlsphinxsearch.com/­docs
DeveloperAmazonBaiduHughes TechnologiesApache Software FoundationSphinx Technologies Inc.
Initial release20172018199420062001
Current release0.94.4, October 20219.6.0, April 20243.5.1, February 2023
License infoCommercial or Open SourcecommercialOpen Source infoApache Version 2.0commercial infofree licenses can be providedOpen Source infoApache Version 2Open 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 languageJavaCJavaC++
Server operating systemshostedLinux
macOS
Unix
AIX
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)FreeBSD
Linux
NetBSD
OS X
Solaris
Windows
Data schemeschema-freeyesyesyes infoDynamic Fields enables on-the-fly addition of new fieldsyes
Typing infopredefined data types such as float or dateyesyesyesyes infosupports customizable data types and automatic typingno
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.nononoyes
Secondary indexesnoyes infoalso supports composite index and range indexyesyes infoAll search fields are automatically indexedyes infofull-text index on all search fields
SQL infoSupport of SQLnonoA subset of ANSI SQL is implemented infono subqueries, aggregate functions, views, foreign keys, triggersSolr Parallel SQL InterfaceSQL-like query language (SphinxQL)
APIs and other access methodsOpenCypher
RDF 1.1 / SPARQL 1.1
TinkerPop Gremlin
Java API
RESTful HTTP API
TinkerPop Gremlin
JDBC
ODBC
Java API
RESTful HTTP/JSON API
Proprietary protocol
Supported programming languagesC#
Go
Java
JavaScript
PHP
Python
Ruby
Scala
Groovy
Java
Python
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
C++ infounofficial client library
Java
Perl infounofficial client library
PHP
Python
Ruby infounofficial client library
Server-side scripts infoStored proceduresnoasynchronous Gremlin script jobsnoJava pluginsno
Triggersnononoyes infoUser configurable commands triggered on index changesno
Partitioning methods infoMethods for storing different data on different nodesnoneyes infodepending on used storage backend, e.g. Cassandra and HBasenoneShardingSharding 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.yes infodepending on used storage backend, e.g. Cassandra and HBasenoneyesnone
MapReduce infoOffers an API for user-defined Map/Reduce methodsnovia hugegraph-sparknospark-solr: github.com/­lucidworks/­spark-solr and streaming expressions to reduceno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyEventual ConsistencynoneEventual Consistency
Foreign keys infoReferential integrityyes infoRelationships in graphsyes infoedges in graphnonono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACIDnooptimistic lockingno
Concurrency infoSupport for concurrent manipulation of datayesyesnoyesyes
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.yesnoyes
User concepts infoAccess controlAccess rights for users and roles can be defined via the AWS Identity and Access Management (IAM)Users, roles and permissionsnoyesno

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More resources
Amazon NeptuneHugeGraphmSQL infoMini SQLSolrSphinx
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