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DBMS > Google Cloud Datastore vs. LokiJS vs. Netezza vs. Solr

System Properties Comparison Google Cloud Datastore vs. LokiJS vs. Netezza vs. Solr

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Editorial information provided by DB-Engines
NameGoogle Cloud Datastore  Xexclude from comparisonLokiJS  Xexclude from comparisonNetezza infoAlso called PureData System for Analytics by IBM  Xexclude from comparisonSolr  Xexclude from comparison
DescriptionAutomatically scaling NoSQL Database as a Service (DBaaS) on the Google Cloud PlatformIn-memory JavaScript DBMSData warehouse and analytics appliance part of IBM PureSystemsA widely used distributed, scalable search engine based on Apache Lucene
Primary database modelDocument storeDocument storeRelational DBMSSearch engine
Secondary database modelsSpatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score4.36
Rank#72  Overall
#12  Document stores
Score0.49
Rank#260  Overall
#42  Document stores
Score8.59
Rank#45  Overall
#29  Relational DBMS
Score41.02
Rank#24  Overall
#3  Search engines
Websitecloud.google.com/­datastoregithub.com/­techfort/­LokiJSwww.ibm.com/­products/­netezzasolr.apache.org
Technical documentationcloud.google.com/­datastore/­docstechfort.github.io/­LokiJSsolr.apache.org/­resources.html
DeveloperGoogleIBMApache Software Foundation
Initial release2008201420002006
Current release9.6.1, May 2024
License infoCommercial or Open SourcecommercialOpen SourcecommercialOpen Source infoApache Version 2
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 languageJavaScriptJava
Server operating systemshostedserver-less, requires a JavaScript environment (browser, Node.js)Linux infoincluded in applianceAll OS with a Java VM inforuns as a servlet in servlet container (e.g. Tomcat, Jetty is included)
Data schemeschema-freeschema-freeyesyes infoDynamic Fields enables on-the-fly addition of new fields
Typing infopredefined data types such as float or dateyes, details herenoyesyes infosupports customizable data types and automatic typing
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 indexesyesyes infovia viewsyesyes infoAll search fields are automatically indexed
SQL infoSupport of SQLSQL-like query language (GQL)noyesSolr Parallel SQL Interface
APIs and other access methodsgRPC (using protocol buffers) API
RESTful HTTP/JSON API
JavaScript APIJDBC
ODBC
OLE DB
Java API
RESTful HTTP/JSON API
Supported programming languages.Net
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
JavaScriptC
C++
Fortran
Java
Lua
Perl
Python
R
.Net
Erlang
Java
JavaScript
any language that supports sockets and either XML or JSON
Perl
PHP
Python
Ruby
Scala
Server-side scripts infoStored proceduresusing Google App EngineView functions in JavaScriptyesJava plugins
TriggersCallbacks using the Google Apps Engineyesnoyes infoUser configurable commands triggered on index changes
Partitioning methods infoMethods for storing different data on different nodesShardingnoneShardingSharding
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication using PaxosnoneSource-replica replicationyes
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infousing Google Cloud Dataflowyesyesspark-solr: github.com/­lucidworks/­spark-solr and streaming expressions to reduce
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.noneEventual Consistency
Foreign keys infoReferential integrityyes infovia ReferenceProperties or Ancestor pathsnonono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACID infoSerializable Isolation within Transactions, Read Committed outside of Transactionsno infoatomic operations within a single collection possibleACIDoptimistic locking
Concurrency infoSupport for concurrent manipulation of datayesyesyes
Durability infoSupport for making data persistentyesyes infoSerialization of a DB in a Node.JS/Cordova/PhoneGap environment. Usage of the IndexedDB-API in a browser.yesyes
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)noUsers with fine-grained authorization conceptyes

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More resources
Google Cloud DatastoreLokiJSNetezza infoAlso called PureData System for Analytics by IBMSolr
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