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DBMS > Google Cloud Bigtable vs. Solr vs. SpatiaLite vs. Sphinx

System Properties Comparison Google Cloud Bigtable vs. Solr vs. SpatiaLite vs. Sphinx

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Editorial information provided by DB-Engines
NameGoogle Cloud Bigtable  Xexclude from comparisonSolr  Xexclude from comparisonSpatiaLite  Xexclude from comparisonSphinx  Xexclude from comparison
DescriptionGoogle's NoSQL Big Data database service. It's the same database that powers many core Google services, including Search, Analytics, Maps, and Gmail.A widely used distributed, scalable search engine based on Apache LuceneSpatial extension of SQLiteOpen source search engine for searching in data from different sources, e.g. relational databases
Primary database modelKey-value store
Wide column store
Search engineSpatial DBMSSearch engine
Secondary database modelsSpatial DBMSRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score3.15
Rank#95  Overall
#14  Key-value stores
#8  Wide column stores
Score41.02
Rank#24  Overall
#3  Search engines
Score1.63
Rank#146  Overall
#3  Spatial DBMS
Score5.95
Rank#55  Overall
#5  Search engines
Websitecloud.google.com/­bigtablesolr.apache.orgwww.gaia-gis.it/­fossil/­libspatialite/­indexsphinxsearch.com
Technical documentationcloud.google.com/­bigtable/­docssolr.apache.org/­resources.htmlwww.gaia-gis.it/­gaia-sins/­spatialite_topics.htmlsphinxsearch.com/­docs
DeveloperGoogleApache Software FoundationAlessandro FurieriSphinx Technologies Inc.
Initial release2015200620082001
Current release9.6.1, May 20245.0.0, August 20203.5.1, February 2023
License infoCommercial or Open SourcecommercialOpen Source infoApache Version 2Open Source infoMPL 1.1, GPL v2.0 or LGPL v2.1Open Source infoGPL version 2, commercial licence available
Cloud-based only infoOnly available as a cloud serviceyesnonono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaC++C++
Server operating systemshostedAll OS with a Java VM inforuns as a servlet in servlet container (e.g. Tomcat, Jetty is included)server-lessFreeBSD
Linux
NetBSD
OS X
Solaris
Windows
Data schemeschema-freeyes infoDynamic Fields enables on-the-fly addition of new fieldsyesyes
Typing infopredefined data types such as float or datenoyes infosupports customizable data types and automatic typingyesno
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 indexedyesyes infofull-text index on all search fields
SQL infoSupport of SQLnoSolr Parallel SQL InterfaceyesSQL-like query language (SphinxQL)
APIs and other access methodsgRPC (using protocol buffers) API
HappyBase (Python library)
HBase compatible API (Java)
Java API
RESTful HTTP/JSON API
Proprietary protocol
Supported programming languagesC#
C++
Go
Java
JavaScript (Node.js)
Python
.Net
Erlang
Java
JavaScript
any language that supports sockets and either XML or JSON
Perl
PHP
Python
Ruby
Scala
C++ infounofficial client library
Java
Perl infounofficial client library
PHP
Python
Ruby infounofficial client library
Server-side scripts infoStored proceduresnoJava pluginsnono
Triggersnoyes infoUser configurable commands triggered on index changesyesno
Partitioning methods infoMethods for storing different data on different nodesShardingShardingnoneSharding infoPartitioning is done manually, search queries against distributed index is supported
Replication methods infoMethods for redundantly storing data on multiple nodesInternal replication in Colossus, and regional replication between two clusters in different zonesyesnonenone
MapReduce infoOffers an API for user-defined Map/Reduce methodsyesspark-solr: github.com/­lucidworks/­spark-solr and streaming expressions to reducenono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate consistency (for a single cluster), Eventual consistency (for two or more replicated clusters)Eventual Consistency
Foreign keys infoReferential integritynonoyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataAtomic single-row operationsoptimistic lockingACIDno
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyesyesyes infoThe original contents of fields are not stored in the Sphinx index.
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)yesnono

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More resources
Google Cloud BigtableSolrSpatiaLiteSphinx
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