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DBMS > Amazon Neptune vs. Apache Phoenix vs. Lovefield vs. SiriDB vs. Solr

System Properties Comparison Amazon Neptune vs. Apache Phoenix vs. Lovefield vs. SiriDB vs. Solr

Editorial information provided by DB-Engines
NameAmazon Neptune  Xexclude from comparisonApache Phoenix  Xexclude from comparisonLovefield  Xexclude from comparisonSiriDB  Xexclude from comparisonSolr  Xexclude from comparison
DescriptionFast, reliable graph database built for the cloudA scale-out RDBMS with evolutionary schema built on Apache HBaseEmbeddable relational database for web apps written in pure JavaScriptOpen Source Time Series DBMSA widely used distributed, scalable search engine based on Apache Lucene
Primary database modelGraph DBMS
RDF store
Relational DBMSRelational DBMSTime Series DBMSSearch engine
Secondary database modelsSpatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score2.29
Rank#113  Overall
#9  Graph DBMS
#5  RDF stores
Score2.06
Rank#123  Overall
#58  Relational DBMS
Score0.33
Rank#286  Overall
#131  Relational DBMS
Score0.07
Rank#378  Overall
#42  Time Series DBMS
Score41.02
Rank#24  Overall
#3  Search engines
Websiteaws.amazon.com/­neptunephoenix.apache.orggoogle.github.io/­lovefieldsiridb.comsolr.apache.org
Technical documentationaws.amazon.com/­neptune/­developer-resourcesphoenix.apache.orggithub.com/­google/­lovefield/­blob/­master/­docs/­spec_index.mddocs.siridb.comsolr.apache.org/­resources.html
DeveloperAmazonApache Software FoundationGoogleCesbitApache Software Foundation
Initial release20172014201420172006
Current release5.0-HBase2, July 2018 and 4.15-HBase1, December 20192.1.12, February 20179.6.1, May 2024
License infoCommercial or Open SourcecommercialOpen Source infoApache Version 2.0Open Source infoApache 2.0Open Source infoMIT LicenseOpen Source infoApache Version 2
Cloud-based only infoOnly available as a cloud serviceyesnononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaJavaScriptCJava
Server operating systemshostedLinux
Unix
Windows
server-less, requires a JavaScript environment (browser, Node.js) infotested with Chrome, Firefox, IE, SafariLinuxAll OS with a Java VM inforuns as a servlet in servlet container (e.g. Tomcat, Jetty is included)
Data schemeschema-freeyes infolate-bound, schema-on-read capabilitiesyesyesyes infoDynamic Fields enables on-the-fly addition of new fields
Typing infopredefined data types such as float or dateyesyesyesyes infoNumeric datayes 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.nonononoyes
Secondary indexesnoyesyesyesyes infoAll search fields are automatically indexed
SQL infoSupport of SQLnoyesSQL-like query language infovia JavaScript builder patternnoSolr Parallel SQL Interface
APIs and other access methodsOpenCypher
RDF 1.1 / SPARQL 1.1
TinkerPop Gremlin
JDBCHTTP APIJava API
RESTful HTTP/JSON API
Supported programming languagesC#
Go
Java
JavaScript
PHP
Python
Ruby
Scala
C
C#
C++
Go
Groovy
Java
PHP
Python
Scala
JavaScriptC
C++
Go
Java
JavaScript (Node.js)
PHP
Python
R
.Net
Erlang
Java
JavaScript
any language that supports sockets and either XML or JSON
Perl
PHP
Python
Ruby
Scala
Server-side scripts infoStored proceduresnouser defined functionsnonoJava plugins
TriggersnonoUsing read-only observersnoyes infoUser configurable commands triggered on index changes
Partitioning methods infoMethods for storing different data on different nodesnoneShardingnoneShardingSharding
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.Multi-source replication
Source-replica replication
noneyesyes
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoHadoop integrationnonospark-solr: github.com/­lucidworks/­spark-solr and streaming expressions to reduce
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate Consistency or Eventual ConsistencyEventual Consistency
Foreign keys infoReferential integrityyes infoRelationships in graphsnoyesnono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACIDACIDnooptimistic locking
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentyes infowith encyption-at-restyesyes, by using IndexedDB or the cloud service Firebase Realtime Databaseyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesyes infousing MemoryDByesyes
User concepts infoAccess controlAccess rights for users and roles can be defined via the AWS Identity and Access Management (IAM)Access Control Lists (using HBase ACL) for RBAC, integration with Apache Ranger for RBAC & ABAC, multi-tenancynosimple rights management via user accountsyes

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Amazon NeptuneApache PhoenixLovefieldSiriDBSolr
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