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DBMS > Google BigQuery vs. Solr vs. WakandaDB

System Properties Comparison Google BigQuery vs. Solr vs. WakandaDB

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Editorial information provided by DB-Engines
NameGoogle BigQuery  Xexclude from comparisonSolr  Xexclude from comparisonWakandaDB  Xexclude from comparison
DescriptionLarge scale data warehouse service with append-only tablesA widely used distributed, scalable search engine based on Apache LuceneWakandaDB is embedded in a server that provides a REST API and a server-side javascript engine to access data
Primary database modelRelational DBMSSearch engineObject oriented DBMS
Secondary database modelsSpatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score62.67
Rank#19  Overall
#13  Relational DBMS
Score43.91
Rank#24  Overall
#3  Search engines
Score0.06
Rank#374  Overall
#17  Object oriented DBMS
Websitecloud.google.com/­bigquerysolr.apache.orgwakanda.github.io
Technical documentationcloud.google.com/­bigquery/­docssolr.apache.org/­resources.htmlwakanda.github.io/­doc
DeveloperGoogleApache Software FoundationWakanda SAS
Initial release201020062012
Current release9.5.0, February 20242.7.0 (April 29, 2019), April 2019
License infoCommercial or Open SourcecommercialOpen Source infoApache Version 2Open Source infoAGPLv3, extended commercial license available
Cloud-based only infoOnly available as a cloud serviceyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaC++, JavaScript
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
Data schemeyesyes infoDynamic Fields enables on-the-fly addition of new fieldsyes
Typing infopredefined data types such as float or dateyesyes 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.noyesno
Secondary indexesnoyes infoAll search fields are automatically indexed
SQL infoSupport of SQLyesSolr Parallel SQL Interfaceno
APIs and other access methodsRESTful HTTP/JSON APIJava API
RESTful HTTP/JSON API
RESTful HTTP API
Supported programming languages.Net
Java
JavaScript
Objective-C
PHP
Python
Ruby
.Net
Erlang
Java
JavaScript
any language that supports sockets and either XML or JSON
Perl
PHP
Python
Ruby
Scala
JavaScript
Server-side scripts infoStored proceduresuser defined functions infoin JavaScriptJava pluginsyes
Triggersnoyes infoUser configurable commands triggered on index changesyes
Partitioning methods infoMethods for storing different data on different nodesnoneShardingnone
Replication methods infoMethods for redundantly storing data on multiple nodesyesnone
MapReduce infoOffers an API for user-defined Map/Reduce methodsnospark-solr: github.com/­lucidworks/­spark-solr and streaming expressions to reduceno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyEventual ConsistencyImmediate Consistency
Foreign keys infoReferential integritynono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datano infoSince BigQuery is designed for querying dataoptimistic lockingACID
Concurrency infoSupport for concurrent manipulation of datayesyesyes
Durability infoSupport for making data persistentyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyesno
User concepts infoAccess controlAccess privileges (owner, writer, reader) on dataset, table or view level infoGoogle Cloud Identity & Access Management (IAM)yesyes

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More resources
Google BigQuerySolrWakandaDB
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