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DBMS > Lovefield vs. Microsoft Azure Table Storage vs. Solr vs. Sphinx

System Properties Comparison Lovefield vs. Microsoft Azure Table Storage vs. Solr vs. Sphinx

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Editorial information provided by DB-Engines
NameLovefield  Xexclude from comparisonMicrosoft Azure Table Storage  Xexclude from comparisonSolr  Xexclude from comparisonSphinx  Xexclude from comparison
DescriptionEmbeddable relational database for web apps written in pure JavaScriptA Wide Column Store for rapid development using massive semi-structured datasetsA widely used distributed, scalable search engine based on Apache LuceneOpen source search engine for searching in data from different sources, e.g. relational databases
Primary database modelRelational DBMSWide column storeSearch engineSearch engine
Secondary database modelsSpatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.29
Rank#293  Overall
#133  Relational DBMS
Score4.48
Rank#75  Overall
#6  Wide column stores
Score42.91
Rank#24  Overall
#3  Search engines
Score5.98
Rank#56  Overall
#5  Search engines
Websitegoogle.github.io/­lovefieldazure.microsoft.com/­en-us/­services/­storage/­tablessolr.apache.orgsphinxsearch.com
Technical documentationgithub.com/­google/­lovefield/­blob/­master/­docs/­spec_index.mdsolr.apache.org/­resources.htmlsphinxsearch.com/­docs
DeveloperGoogleMicrosoftApache Software FoundationSphinx Technologies Inc.
Initial release2014201220062001
Current release2.1.12, February 20179.5.0, February 20243.5.1, February 2023
License infoCommercial or Open SourceOpen Source infoApache 2.0commercialOpen Source infoApache Version 2Open Source infoGPL version 2, commercial licence available
Cloud-based only infoOnly available as a cloud servicenoyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaScriptJavaC++
Server operating systemsserver-less, requires a JavaScript environment (browser, Node.js) infotested with Chrome, Firefox, IE, SafarihostedAll OS with a Java VM inforuns as a servlet in servlet container (e.g. Tomcat, Jetty is included)FreeBSD
Linux
NetBSD
OS X
Solaris
Windows
Data schemeyesschema-freeyes infoDynamic Fields enables on-the-fly addition of new fieldsyes
Typing infopredefined data types such as float or dateyesyesyes infosupports customizable data types and automatic typingno
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 indexesyesnoyes infoAll search fields are automatically indexedyes infofull-text index on all search fields
SQL infoSupport of SQLSQL-like query language infovia JavaScript builder patternnoSolr Parallel SQL InterfaceSQL-like query language (SphinxQL)
APIs and other access methodsRESTful HTTP APIJava API
RESTful HTTP/JSON API
Proprietary protocol
Supported programming languagesJavaScript.Net
C#
C++
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
C++ infounofficial client library
Java
Perl infounofficial client library
PHP
Python
Ruby infounofficial client library
Server-side scripts infoStored proceduresnonoJava pluginsno
TriggersUsing read-only observersnoyes infoUser configurable commands triggered on index changesno
Partitioning methods infoMethods for storing different data on different nodesnoneSharding infoImplicit feature of the cloud serviceShardingSharding infoPartitioning is done manually, search queries against distributed index is supported
Replication methods infoMethods for redundantly storing data on multiple nodesnoneyes infoimplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.yesnone
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonospark-solr: github.com/­lucidworks/­spark-solr and streaming expressions to reduceno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyEventual Consistency
Foreign keys infoReferential integrityyesnonono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDoptimistic lockingoptimistic lockingno
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyes, by using IndexedDB or the cloud service Firebase Realtime Databaseyesyesyes 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.yes infousing MemoryDBnoyes
User concepts infoAccess controlnoAccess rights based on private key authentication or shared access signaturesyesno

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More resources
LovefieldMicrosoft Azure Table StorageSolrSphinx
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