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DBMS > Google Cloud Datastore vs. Solr vs. TigerGraph vs. Valentina Server

System Properties Comparison Google Cloud Datastore vs. Solr vs. TigerGraph vs. Valentina Server

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Editorial information provided by DB-Engines
NameGoogle Cloud Datastore  Xexclude from comparisonSolr  Xexclude from comparisonTigerGraph  Xexclude from comparisonValentina Server  Xexclude from comparison
DescriptionAutomatically scaling NoSQL Database as a Service (DBaaS) on the Google Cloud PlatformA widely used distributed, scalable search engine based on Apache LuceneA complete, distributed, parallel graph computing platform supporting web-scale data analytics in real-timeObject-relational database and reports server
Primary database modelDocument storeSearch engineGraph DBMSRelational DBMS
Secondary database modelsSpatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score4.47
Rank#76  Overall
#12  Document stores
Score42.91
Rank#24  Overall
#3  Search engines
Score1.83
Rank#139  Overall
#13  Graph DBMS
Score0.17
Rank#327  Overall
#145  Relational DBMS
Websitecloud.google.com/­datastoresolr.apache.orgwww.tigergraph.comwww.valentina-db.net
Technical documentationcloud.google.com/­datastore/­docssolr.apache.org/­resources.htmldocs.tigergraph.comvalentina-db.com/­docs/­dokuwiki/­v5/­doku.php
DeveloperGoogleApache Software FoundationParadigma Software
Initial release2008200620171999
Current release9.6.0, April 20245.7.5
License infoCommercial or Open SourcecommercialOpen Source infoApache Version 2commercialcommercial
Cloud-based only infoOnly available as a cloud serviceyesnonono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJavaC++
Server operating systemshostedAll OS with a Java VM inforuns as a servlet in servlet container (e.g. Tomcat, Jetty is included)LinuxLinux
OS X
Windows
Data schemeschema-freeyes infoDynamic Fields enables on-the-fly addition of new fieldsyesyes
Typing infopredefined data types such as float or dateyes, details hereyes infosupports customizable data types and automatic typingyesyes
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.noyesno
Secondary indexesyesyes infoAll search fields are automatically indexedyes
SQL infoSupport of SQLSQL-like query language (GQL)Solr Parallel SQL InterfaceSQL-like query language (GSQL)yes
APIs and other access methodsgRPC (using protocol buffers) API
RESTful HTTP/JSON API
Java API
RESTful HTTP/JSON API
GSQL (TigerGraph Query Language)
Kafka
RESTful HTTP/JSON API
ODBC
Supported programming languages.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
C++
Java
.Net
C
C#
C++
Objective-C
PHP
Ruby
Visual Basic
Visual Basic.NET
Server-side scripts infoStored proceduresusing Google App EngineJava pluginsyesyes
TriggersCallbacks using the Google Apps Engineyes infoUser configurable commands triggered on index changesnoyes
Partitioning methods infoMethods for storing different data on different nodesShardingSharding
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication using Paxosyes
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infousing Google Cloud Dataflowspark-solr: github.com/­lucidworks/­spark-solr and streaming expressions to reduceyesno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate 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 Consistency
Foreign keys infoReferential integrityyes infovia ReferenceProperties or Ancestor pathsnoyes infoRelationships in graphsyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACID infoSerializable Isolation within Transactions, Read Committed outside of Transactionsoptimistic lockingACID
Concurrency infoSupport for concurrent manipulation of datayesyesyes
Durability infoSupport for making data persistentyesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyesnoyes
User concepts infoAccess controlAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)yesRole-based access controlfine grained access rights according to SQL-standard

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More resources
Google Cloud DatastoreSolrTigerGraphValentina Server
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