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DBMS > Microsoft Azure Table Storage vs. OpenEdge vs. Solr vs. Sqrrl

System Properties Comparison Microsoft Azure Table Storage vs. OpenEdge vs. Solr vs. Sqrrl

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Editorial information provided by DB-Engines
NameMicrosoft Azure Table Storage  Xexclude from comparisonOpenEdge  Xexclude from comparisonSolr  Xexclude from comparisonSqrrl  Xexclude from comparison
Sqrrl has been acquired by Amazon and became a part of Amazon Web Services. It has been removed from the DB-Engines ranking.
DescriptionA Wide Column Store for rapid development using massive semi-structured datasetsApplication development environment with integrated database management systemA widely used distributed, scalable search engine based on Apache LuceneAdaptable, secure NoSQL built on Apache Accumulo
Primary database modelWide column storeRelational DBMSSearch engineDocument store
Graph DBMS
Key-value store
Wide column store
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score5.77
Rank#66  Overall
#5  Wide column stores
Score5.06
Rank#74  Overall
#41  Relational DBMS
Score51.62
Rank#20  Overall
#3  Search engines
Websiteazure.microsoft.com/­en-us/­services/­storage/­tableswww.progress.com/­openedgelucene.apache.org/­solrsqrrl.com
Technical documentationdocumentation.progress.com/­output/­ua/­OpenEdge_latestlucene.apache.org/­solr/­resources.html
DeveloperMicrosoftProgress Software CorporationApache Software FoundationAmazon infooriginally Sqrrl Data, Inc.
Initial release2012198420062012
Current releaseOpenEdge 12.2, March 20208.6.2, September 2020
License infoCommercial or Open SourcecommercialcommercialOpen Source infoApache Version 2commercial
Cloud-based only infoOnly available as a cloud serviceyesnonono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJavaJava
Server operating systemshostedAIX
HP-UX
Linux
Solaris
Windows
All OS with a Java VM inforuns as a servlet in servlet container (e.g. Tomcat, Jetty is included)Linux
Data schemeschema-freeyesyes infoDynamic Fields enables on-the-fly addition of new fieldsschema-free
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.noyesyes
Secondary indexesnoyesyes infoAll search fields are automatically indexedyes
SQL infoSupport of SQLnoyes infoclose to SQL 92Solr Parallel SQL Interfaceno
APIs and other access methodsRESTful HTTP APIJDBC
ODBC
Java API
RESTful HTTP/JSON API
Accumulo Shell
Java API
JDBC
ODBC
RESTful HTTP API
Thrift
Supported programming languages.Net
C#
C++
Java
JavaScript (Node.js)
PHP
Python
Ruby
Progress proprietary ABL (Advanced Business Language).Net
Erlang
Java
JavaScript
any language that supports sockets and either XML or JSON
Perl
PHP
Python
Ruby
Scala
Actionscript
C infousing GLib
C#
C++
Cocoa
Delphi
Erlang
Go
Haskell
Java
JavaScript
OCaml
Perl
PHP
Python
Ruby
Smalltalk
Server-side scripts infoStored proceduresnoyesJava pluginsno
Triggersnoyesyes 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 11.4ShardingSharding infomaking use of Hadoop
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 replicationyesselectable replication factor infomaking use of Hadoop
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonospark-solr: github.com/­lucidworks/­spark-solr and streaming expressions to reduceyes
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyEventual ConsistencyImmediate Consistency infoDocument store kept consistent with combination of global timestamping, row-level transactions, and server-side consistency resolution.
Foreign keys infoReferential integritynoyesnono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataoptimistic lockingACIDoptimistic lockingAtomic updates per row, document, or graph entity
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.nonoyes
User concepts infoAccess controlAccess rights based on private key authentication or shared access signaturesUsers and groupsyesCell-level Security, Data-Centric Security, Role-Based Access Control (RBAC), Attribute-Based Access Control (ABAC)

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Microsoft Azure Table StorageOpenEdgeSolrSqrrl
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