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DBMS > Microsoft Azure Table Storage vs. OpenEdge vs. Realm vs. Solr vs. Spark SQL

System Properties Comparison Microsoft Azure Table Storage vs. OpenEdge vs. Realm vs. Solr vs. Spark SQL

Editorial information provided by DB-Engines
NameMicrosoft Azure Table Storage  Xexclude from comparisonOpenEdge  Xexclude from comparisonRealm  Xexclude from comparisonSolr  Xexclude from comparisonSpark SQL  Xexclude from comparison
DescriptionA Wide Column Store for rapid development using massive semi-structured datasetsApplication development environment with integrated database management systemA DBMS built for use on mobile devices that’s a fast, easy to use alternative to SQLite and Core DataA widely used distributed, scalable search engine based on Apache LuceneSpark SQL is a component on top of 'Spark Core' for structured data processing
Primary database modelWide column storeRelational DBMSDocument storeSearch engineRelational DBMS
Secondary database modelsSpatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score4.48
Rank#75  Overall
#6  Wide column stores
Score3.51
Rank#86  Overall
#46  Relational DBMS
Score7.60
Rank#52  Overall
#9  Document stores
Score42.91
Rank#24  Overall
#3  Search engines
Score18.96
Rank#33  Overall
#20  Relational DBMS
Websiteazure.microsoft.com/­en-us/­services/­storage/­tableswww.progress.com/­openedgerealm.iosolr.apache.orgspark.apache.org/­sql
Technical documentationdocumentation.progress.com/­output/­ua/­OpenEdge_latestrealm.io/­docssolr.apache.org/­resources.htmlspark.apache.org/­docs/­latest/­sql-programming-guide.html
DeveloperMicrosoftProgress Software CorporationRealm, acquired by MongoDB in May 2019Apache Software FoundationApache Software Foundation
Initial release20121984201420062014
Current releaseOpenEdge 12.2, March 20209.6.0, April 20243.5.0 ( 2.13), September 2023
License infoCommercial or Open SourcecommercialcommercialOpen SourceOpen Source infoApache Version 2Open Source infoApache 2.0
Cloud-based only infoOnly available as a cloud serviceyesnononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaScala
Server operating systemshostedAIX
HP-UX
Linux
Solaris
Windows
Android
Backend: server-less
iOS
Windows
All OS with a Java VM inforuns as a servlet in servlet container (e.g. Tomcat, Jetty is included)Linux
OS X
Windows
Data schemeschema-freeyesyesyes infoDynamic Fields enables on-the-fly addition of new fieldsyes
Typing infopredefined data types such as float or dateyesyesyesyes 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.noyesnoyesno
Secondary indexesnoyesyesyes infoAll search fields are automatically indexedno
SQL infoSupport of SQLnoyes infoclose to SQL 92noSolr Parallel SQL InterfaceSQL-like DML and DDL statements
APIs and other access methodsRESTful HTTP APIJDBC
ODBC
Java API
RESTful HTTP/JSON API
JDBC
ODBC
Supported programming languages.Net
C#
C++
Java
JavaScript (Node.js)
PHP
Python
Ruby
Progress proprietary ABL (Advanced Business Language).Net
Java infowith Android only
Objective-C
React Native
Swift
.Net
Erlang
Java
JavaScript
any language that supports sockets and either XML or JSON
Perl
PHP
Python
Ruby
Scala
Java
Python
R
Scala
Server-side scripts infoStored proceduresnoyesno inforuns within the applications so server-side scripts are unnecessaryJava pluginsno
Triggersnoyesyes infoChange Listenersyes infoUser configurable commands triggered on index changesno
Partitioning methods infoMethods for storing different data on different nodesSharding infoImplicit feature of the cloud servicehorizontal partitioning infosince Version 11.4noneShardingyes, utilizing Spark Core
Replication methods infoMethods for redundantly storing data on multiple nodesyes infoimplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.Source-replica replicationnoneyesnone
MapReduce infoOffers an API for user-defined Map/Reduce methodsnononospark-solr: github.com/­lucidworks/­spark-solr and streaming expressions to reduce
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyImmediate ConsistencyEventual Consistency
Foreign keys infoReferential integritynoyesnonono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataoptimistic lockingACIDACIDoptimistic lockingno
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.nonoyes infoIn-Memory realmyesno
User concepts infoAccess controlAccess rights based on private key authentication or shared access signaturesUsers and groupsyesyesno

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More resources
Microsoft Azure Table StorageOpenEdgeRealmSolrSpark SQL
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