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DBMS > Google Cloud Datastore vs. Oracle Rdb vs. Solr vs. Vitess

System Properties Comparison Google Cloud Datastore vs. Oracle Rdb vs. Solr vs. Vitess

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Editorial information provided by DB-Engines
NameGoogle Cloud Datastore  Xexclude from comparisonOracle Rdb  Xexclude from comparisonSolr  Xexclude from comparisonVitess  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 LuceneScalable, distributed, cloud-native DBMS, extending MySQL
Primary database modelDocument storeRelational DBMSSearch engineRelational DBMS
Secondary database modelsSpatial DBMSDocument store
Spatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score4.47
Rank#76  Overall
#12  Document stores
Score1.08
Rank#184  Overall
#85  Relational DBMS
Score42.91
Rank#24  Overall
#3  Search engines
Score0.82
Rank#209  Overall
#97  Relational DBMS
Websitecloud.google.com/­datastorewww.oracle.com/­database/­technologies/­related/­rdb.htmlsolr.apache.orgvitess.io
Technical documentationcloud.google.com/­datastore/­docswww.oracle.com/­database/­technologies/­related/­rdb-doc.htmlsolr.apache.org/­resources.htmlvitess.io/­docs
DeveloperGoogleOracle, originally developed by Digital Equipment Corporation (DEC)Apache Software FoundationThe Linux Foundation, PlanetScale
Initial release2008198420062013
Current release7.4.1.1, 20219.6.0, April 202415.0.2, December 2022
License infoCommercial or Open SourcecommercialcommercialOpen Source infoApache Version 2Open Source infoApache Version 2.0, commercial licenses available
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 languageJavaGo
Server operating systemshostedHP Open VMSAll OS with a Java VM inforuns as a servlet in servlet container (e.g. Tomcat, Jetty is included)Docker
Linux
macOS
Data schemeschema-freeFlexible Schema (defined schema, partial schema, schema free)yes infoDynamic Fields enables on-the-fly addition of new fieldsyes
Typing infopredefined data types such as float or dateyes, details hereyesyes 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.nonoyes
Secondary indexesyesyesyes infoAll search fields are automatically indexedyes
SQL infoSupport of SQLSQL-like query language (GQL)yesSolr Parallel SQL Interfaceyes infowith proprietary extensions
APIs and other access methodsgRPC (using protocol buffers) API
RESTful HTTP/JSON API
Java API
RESTful HTTP/JSON API
ADO.NET
JDBC
MySQL protocol
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
Ada
C
C#
C++
D
Delphi
Eiffel
Erlang
Haskell
Java
JavaScript (Node.js)
Objective-C
OCaml
Perl
PHP
Python
Ruby
Scheme
Tcl
Server-side scripts infoStored proceduresusing Google App EngineJava pluginsyes infoproprietary syntax
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 PaxosyesMulti-source replication
Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infousing Google Cloud Dataflownospark-solr: github.com/­lucidworks/­spark-solr and streaming expressions to reduceno
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.Immediate ConsistencyEventual ConsistencyEventual Consistency across shards
Immediate Consistency within a shard
Foreign keys infoReferential integrityyes infovia ReferenceProperties or Ancestor pathsyesnoyes infonot for MyISAM storage engine
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACID infoSerializable Isolation within Transactions, Read Committed outside of Transactionsyes, on a single nodeoptimistic lockingACID at shard level
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes infotable locks or row locks depending on storage engine
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.nonoyesyes
User concepts infoAccess controlAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)yesUsers with fine-grained authorization concept infono user groups or roles

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More resources
Google Cloud DatastoreOracle RdbSolrVitess
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