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DBMS > AgensGraph vs. Amazon Neptune vs. Apache Solr vs. Elasticsearch

System Properties Comparison AgensGraph vs. Amazon Neptune vs. Apache Solr vs. Elasticsearch

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Editorial information provided by DB-Engines
NameAgensGraph  Xexclude from comparisonAmazon Neptune  Xexclude from comparisonApache Solr  Xexclude from comparisonElasticsearch  Xexclude from comparison
DescriptionMulti-model database supporting relational and graph data models and built upon PostgreSQLFast, reliable graph database built for the cloudA widely used distributed, scalable search engine based on Apache LuceneA distributed, RESTful modern search and analytics engine based on Apache Lucene infoElasticsearch lets you perform and combine many types of searches such as structured, unstructured, geo, and metric
Primary database modelGraph DBMS
Relational DBMS
Graph DBMS
RDF store
Search engineSearch engine
Vector DBMS
Secondary database modelsSpatial DBMSDocument store
Spatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.14
Rank#335  Overall
#31  Graph DBMS
#147  Relational DBMS
Score2.13
Rank#111  Overall
#9  Graph DBMS
#5  RDF stores
Score32.79
Rank#23  Overall
#3  Search engines
Score123.81
Rank#9  Overall
#1  Search engines
#1  Vector DBMS
Websitebitnine.net/­agensgraphaws.amazon.com/­neptunesolr.apache.orgwww.elastic.co/­elasticsearch
Technical documentationbitnine.net/­documentationaws.amazon.com/­neptune/­developer-resourcessolr.apache.org/­resources.htmlwww.elastic.co/­guide/­en/­elasticsearch/­reference/­current/­index.html
DeveloperBitnine Global Inc.AmazonApache Software FoundationElastic
Initial release2016201720062010
Current release2.1, December 20189.6.1, May 20248.6, January 2023
License infoCommercial or Open SourceOpen Source infoApache License 2.0commercialOpen Source infoApache Version 2Open Source infoElastic License
Cloud-based only infoOnly available as a cloud servicenoyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageCJavaJava
Server operating systemsLinux
OS X
Windows
hostedAll OS with a Java VM inforuns as a servlet in servlet container (e.g. Tomcat, Jetty is included)All OS with a Java VM
Data schemedepending on used data modelschema-freeyes infoDynamic Fields enables on-the-fly addition of new fieldsschema-free infoFlexible type definitions. Once a type is defined, it is persistent
Typing infopredefined data types such as float or dateyesyesyes infosupports customizable data types and automatic typingyes
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 indexesyesnoyes infoAll search fields are automatically indexedyes infoAll search fields are automatically indexed
SQL infoSupport of SQLyesnoSolr Parallel SQL InterfaceSQL-like query language
APIs and other access methodsCypher Query Language
JDBC
OpenCypher
RDF 1.1 / SPARQL 1.1
TinkerPop Gremlin
Java API
RESTful HTTP/JSON API
Java API
RESTful HTTP/JSON API
Supported programming languagesC
Java
JavaScript
Python
C#
Go
Java
JavaScript
PHP
Python
Ruby
Scala
.Net
Erlang
Java
JavaScript
any language that supports sockets and either XML or JSON
Perl
PHP
Python
Ruby
Scala
.Net
Groovy
Community Contributed Clients
Java
JavaScript
Perl
PHP
Python
Ruby
Server-side scripts infoStored proceduresyesnoJava pluginsyes
Triggersnonoyes infoUser configurable commands triggered on index changesyes infoby using the 'percolation' feature
Partitioning methods infoMethods for storing different data on different nodesno, but can be realized using table inheritancenoneShardingSharding
Replication methods infoMethods for redundantly storing data on multiple nodesSource-replica replicationMulti-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.yesyes
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonospark-solr: github.com/­lucidworks/­spark-solr and streaming expressions to reduceES-Hadoop Connector
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyEventual ConsistencyEventual Consistency infoSynchronous doc based replication. Get by ID may show delays up to 1 sec. Configurable write consistency: one, quorum, all
Foreign keys infoReferential integrityyesyes infoRelationships in graphsnono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACIDoptimistic lockingno
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyes infowith encyption-at-restyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyesMemcached and Redis integration
User concepts infoAccess controlfine grained access rights according to SQL-standardAccess rights for users and roles can be defined via the AWS Identity and Access Management (IAM)yes

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More resources
AgensGraphAmazon NeptuneApache SolrElasticsearch
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