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

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

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Editorial information provided by DB-Engines
NameLovefield  Xexclude from comparisonMicrosoft Azure Table Storage  Xexclude from comparisonSolr  Xexclude from comparisonTrafodion  Xexclude from comparison
Apache Trafodion has been retired in 2021. Therefore it is excluded from the DB-Engines Ranking.
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 LuceneTransactional SQL-on-Hadoop DBMS
Primary database modelRelational DBMSWide column storeSearch engineRelational DBMS
Secondary database modelsSpatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.32
Rank#290  Overall
#132  Relational DBMS
Score4.92
Rank#73  Overall
#6  Wide column stores
Score44.28
Rank#24  Overall
#3  Search engines
Websitegoogle.github.io/­lovefieldazure.microsoft.com/­en-us/­services/­storage/­tablessolr.apache.orgtrafodion.apache.org
Technical documentationgithub.com/­google/­lovefield/­blob/­master/­docs/­spec_index.mdsolr.apache.org/­resources.htmltrafodion.apache.org/­documentation.html
DeveloperGoogleMicrosoftApache Software FoundationApache Software Foundation, originally developed by HP
Initial release2014201220062014
Current release2.1.12, February 20179.5.0, February 20242.3.0, February 2019
License infoCommercial or Open SourceOpen Source infoApache 2.0commercialOpen Source infoApache Version 2Open Source infoApache 2.0
Cloud-based only infoOnly available as a cloud servicenoyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJavaScriptJavaC++, Java
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)Linux
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 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.nonoyesno
Secondary indexesyesnoyes infoAll search fields are automatically indexedyes
SQL infoSupport of SQLSQL-like query language infovia JavaScript builder patternnoSolr Parallel SQL Interfaceyes
APIs and other access methodsRESTful HTTP APIJava API
RESTful HTTP/JSON API
ADO.NET
JDBC
ODBC
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
All languages supporting JDBC/ODBC/ADO.Net
Server-side scripts infoStored proceduresnonoJava pluginsJava Stored Procedures
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
Replication methods infoMethods for redundantly storing data on multiple nodesnoneyes infoimplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.yesyes, via HBase
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonospark-solr: github.com/­lucidworks/­spark-solr and streaming expressions to reduceyes infovia user defined functions and HBase
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyEventual ConsistencyImmediate Consistency
Foreign keys infoReferential integrityyesnonoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDoptimistic lockingoptimistic lockingACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyes, by using IndexedDB or the cloud service Firebase Realtime Databaseyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yes infousing MemoryDBnoyesno
User concepts infoAccess controlnoAccess rights based on private key authentication or shared access signaturesyesfine grained access rights according to SQL-standard

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More resources
LovefieldMicrosoft Azure Table StorageSolrTrafodion
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