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DBMS > Amazon Neptune vs. Lovefield vs. Microsoft Azure Table Storage vs. OrigoDB vs. Solr

System Properties Comparison Amazon Neptune vs. Lovefield vs. Microsoft Azure Table Storage vs. OrigoDB vs. Solr

Editorial information provided by DB-Engines
NameAmazon Neptune  Xexclude from comparisonLovefield  Xexclude from comparisonMicrosoft Azure Table Storage  Xexclude from comparisonOrigoDB  Xexclude from comparisonSolr  Xexclude from comparison
DescriptionFast, reliable graph database built for the cloudEmbeddable relational database for web apps written in pure JavaScriptA Wide Column Store for rapid development using massive semi-structured datasetsA fully ACID in-memory object graph databaseA widely used distributed, scalable search engine based on Apache Lucene
Primary database modelGraph DBMS
RDF store
Relational DBMSWide column storeDocument store
Object oriented DBMS
Search 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
Score0.32
Rank#290  Overall
#132  Relational DBMS
Score4.92
Rank#73  Overall
#6  Wide column stores
Score0.03
Rank#378  Overall
#51  Document stores
#18  Object oriented DBMS
Score44.28
Rank#24  Overall
#3  Search engines
Websiteaws.amazon.com/­neptunegoogle.github.io/­lovefieldazure.microsoft.com/­en-us/­services/­storage/­tablesorigodb.comsolr.apache.org
Technical documentationaws.amazon.com/­neptune/­developer-resourcesgithub.com/­google/­lovefield/­blob/­master/­docs/­spec_index.mdorigodb.com/­docssolr.apache.org/­resources.html
DeveloperAmazonGoogleMicrosoftRobert Friberg et alApache Software Foundation
Initial release2017201420122009 infounder the name LiveDB2006
Current release2.1.12, February 20179.5.0, February 2024
License infoCommercial or Open SourcecommercialOpen Source infoApache 2.0commercialOpen SourceOpen Source infoApache Version 2
Cloud-based only infoOnly available as a cloud serviceyesnoyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaScriptC#Java
Server operating systemshostedserver-less, requires a JavaScript environment (browser, Node.js) infotested with Chrome, Firefox, IE, SafarihostedLinux
Windows
All OS with a Java VM inforuns as a servlet in servlet container (e.g. Tomcat, Jetty is included)
Data schemeschema-freeyesschema-freeyesyes infoDynamic Fields enables on-the-fly addition of new fields
Typing infopredefined data types such as float or dateyesyesyesUser defined using .NET types and collectionsyes infosupports customizable data types and automatic typing
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 infocan be achieved using .NETyes
Secondary indexesnoyesnoyesyes infoAll search fields are automatically indexed
SQL infoSupport of SQLnoSQL-like query language infovia JavaScript builder patternnonoSolr Parallel SQL Interface
APIs and other access methodsOpenCypher
RDF 1.1 / SPARQL 1.1
TinkerPop Gremlin
RESTful HTTP API.NET Client API
HTTP API
LINQ
Java API
RESTful HTTP/JSON API
Supported programming languagesC#
Go
Java
JavaScript
PHP
Python
Ruby
Scala
JavaScript.Net
C#
C++
Java
JavaScript (Node.js)
PHP
Python
Ruby
.Net.Net
Erlang
Java
JavaScript
any language that supports sockets and either XML or JSON
Perl
PHP
Python
Ruby
Scala
Server-side scripts infoStored proceduresnononoyesJava plugins
TriggersnoUsing read-only observersnoyes infoDomain Eventsyes infoUser configurable commands triggered on index changes
Partitioning methods infoMethods for storing different data on different nodesnonenoneSharding infoImplicit feature of the cloud servicehorizontal partitioning infoclient side managed; servers are not synchronizedSharding
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.noneyes infoimplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.Source-replica replicationyes
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonononospark-solr: github.com/­lucidworks/­spark-solr and streaming expressions to reduce
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyEventual Consistency
Foreign keys infoReferential integrityyes infoRelationships in graphsyesnodepending on modelno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACIDoptimistic lockingACIDoptimistic locking
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentyes infowith encyption-at-restyes, by using IndexedDB or the cloud service Firebase Realtime Databaseyesyes infoWrite ahead logyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yes infousing MemoryDBnoyesyes
User concepts infoAccess controlAccess rights for users and roles can be defined via the AWS Identity and Access Management (IAM)noAccess rights based on private key authentication or shared access signaturesRole based authorizationyes

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More resources
Amazon NeptuneLovefieldMicrosoft Azure Table StorageOrigoDBSolr
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