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DBMS > Amazon CloudSearch vs. EsgynDB vs. Google Cloud Datastore vs. Solr vs. TinkerGraph

System Properties Comparison Amazon CloudSearch vs. EsgynDB vs. Google Cloud Datastore vs. Solr vs. TinkerGraph

Editorial information provided by DB-Engines
NameAmazon CloudSearch  Xexclude from comparisonEsgynDB  Xexclude from comparisonGoogle Cloud Datastore  Xexclude from comparisonSolr  Xexclude from comparisonTinkerGraph  Xexclude from comparison
DescriptionA hosted search engine service by Amazon with the data stored in Amazons cloudEnterprise-class SQL-on-Hadoop solution, powered by Apache TrafodionAutomatically scaling NoSQL Database as a Service (DBaaS) on the Google Cloud PlatformA widely used distributed, scalable search engine based on Apache LuceneA lightweight, in-memory graph engine that serves as a reference implementation of the TinkerPop3 API
Primary database modelSearch engineRelational DBMSDocument storeSearch engineGraph DBMS
Secondary database modelsSpatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.81
Rank#137  Overall
#12  Search engines
Score0.25
Rank#312  Overall
#138  Relational DBMS
Score4.36
Rank#72  Overall
#12  Document stores
Score41.02
Rank#24  Overall
#3  Search engines
Score0.13
Rank#345  Overall
#35  Graph DBMS
Websiteaws.amazon.com/­cloudsearchwww.esgyn.cncloud.google.com/­datastoresolr.apache.orgtinkerpop.apache.org/­docs/­current/­reference/­#tinkergraph-gremlin
Technical documentationdocs.aws.amazon.com/­cloudsearchcloud.google.com/­datastore/­docssolr.apache.org/­resources.html
DeveloperAmazonEsgynGoogleApache Software Foundation
Initial release20122015200820062009
Current release9.6.1, May 2024
License infoCommercial or Open SourcecommercialcommercialcommercialOpen Source infoApache Version 2Open Source infoApache 2.0
Cloud-based only infoOnly available as a cloud serviceyesnoyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageC++, JavaJavaJava
Server operating systemshostedLinuxhostedAll OS with a Java VM inforuns as a servlet in servlet container (e.g. Tomcat, Jetty is included)
Data schemeyesyesschema-freeyes infoDynamic Fields enables on-the-fly addition of new fieldsschema-free
Typing infopredefined data types such as float or dateyesyesyes, details hereyes 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 indexesyes infoall search fields are automatically indexedyesyesyes infoAll search fields are automatically indexedno
SQL infoSupport of SQLnoyesSQL-like query language (GQL)Solr Parallel SQL Interfaceno
APIs and other access methodsHTTP APIADO.NET
JDBC
ODBC
gRPC (using protocol buffers) API
RESTful HTTP/JSON API
Java API
RESTful HTTP/JSON API
TinkerPop 3
Supported programming languagesAll languages supporting JDBC/ODBC/ADO.Net.Net
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
.Net
Erlang
Java
JavaScript
any language that supports sockets and either XML or JSON
Perl
PHP
Python
Ruby
Scala
Groovy
Java
Server-side scripts infoStored proceduresnoJava Stored Proceduresusing Google App EngineJava pluginsno
TriggersnonoCallbacks using the Google Apps Engineyes infoUser configurable commands triggered on index changesno
Partitioning methods infoMethods for storing different data on different nodesyes infoautomatic partitioning across Amazon Search Instance as requiredShardingShardingShardingnone
Replication methods infoMethods for redundantly storing data on multiple nodesyes infomanaged transparently by AWSMulti-source replication between multi datacentersMulti-source replication using Paxosyesnone
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyesyes infousing Google Cloud Dataflowspark-solr: github.com/­lucidworks/­spark-solr and streaming expressions to reduceno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate Consistency or Eventual Consistency depending on type of query and configuration infoStrong Consistency is default for entity lookups and queries within an Entity Group (but can instead be made eventually consistent). Other queries are always eventual consistent.Eventual Consistencynone
Foreign keys infoReferential integritynoyesyes infovia ReferenceProperties or Ancestor pathsnoyes infoRelationships in graphs
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDACID infoSerializable Isolation within Transactions, Read Committed outside of Transactionsoptimistic lockingno
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesno
Durability infoSupport for making data persistentyesyesyesyesoptional
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.nonoyesyes
User concepts infoAccess controlauthentication via encrypted signaturesfine grained access rights according to SQL-standardAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)yesno

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More resources
Amazon CloudSearchEsgynDBGoogle Cloud DatastoreSolrTinkerGraph
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