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

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

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Editorial information provided by DB-Engines
NameGoogle Cloud Datastore  Xexclude from comparisonSolr  Xexclude from comparisonValentina Server  Xexclude from comparisonYTsaurus  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 LuceneObject-relational database and reports serverYTsaurus is an open source platform for distributed storage and processing.
Primary database modelDocument storeSearch engineRelational DBMSDocument store
Key-value store
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
Score0.17
Rank#327  Overall
#145  Relational DBMS
Score0.11
Rank#340  Overall
#45  Document stores
#50  Key-value stores
Websitecloud.google.com/­datastoresolr.apache.orgwww.valentina-db.netytsaurus.tech
Technical documentationcloud.google.com/­datastore/­docssolr.apache.org/­resources.htmlvalentina-db.com/­docs/­dokuwiki/­v5/­doku.phpytsaurus.tech/­docs/­en
DeveloperGoogleApache Software FoundationParadigma SoftwareYandex
Initial release2008200619992023
Current release9.6.0, April 20245.7.5
License infoCommercial or Open SourcecommercialOpen Source infoApache Version 2commercialOpen Source infoApache License, Version 2.0
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)Linux
OS X
Windows
Ubuntu
Data schemeschema-freeyes infoDynamic Fields enables on-the-fly addition of new fieldsyes
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 InterfaceyesYQL, an SQL-based language, is supported
APIs and other access methodsgRPC (using protocol buffers) API
RESTful HTTP/JSON API
Java API
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
.Net
C
C#
C++
Objective-C
PHP
Ruby
Visual Basic
Visual Basic.NET
C++
Go
Java
JavaScript
Python
Server-side scripts infoStored proceduresusing Google App EngineJava pluginsyes
TriggersCallbacks using the Google Apps Engineyes infoUser configurable commands triggered on index changesyes
Partitioning methods infoMethods for storing different data on different nodesShardingShardingSharding
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication using Paxosyesyes
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infousing Google Cloud Dataflowspark-solr: github.com/­lucidworks/­spark-solr and streaming expressions to reducenoyes
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
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.noyesyes
User concepts infoAccess controlAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)yesfine grained access rights according to SQL-standardAccess Control Lists

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More resources
Google Cloud DatastoreSolrValentina ServerYTsaurus
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