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DBMS > Elasticsearch vs. Interbase vs. Microsoft Azure Table Storage vs. Solr

System Properties Comparison Elasticsearch vs. Interbase vs. Microsoft Azure Table Storage vs. Solr

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Editorial information provided by DB-Engines
NameElasticsearch  Xexclude from comparisonInterbase  Xexclude from comparisonMicrosoft Azure Table Storage  Xexclude from comparisonSolr  Xexclude from comparison
DescriptionA distributed, RESTful modern search and analytics engine based on Apache Lucene infoElasticsearch lets you perform and combine many types of searches such as structured, unstructured, geo, and metricLight-weight proven RDBMS infooriginally from BorlandA Wide Column Store for rapid development using massive semi-structured datasetsA widely used distributed, scalable search engine based on Apache Lucene
Primary database modelSearch engineRelational DBMSWide column storeSearch engine
Secondary database modelsDocument store
Spatial DBMS
Vector DBMS
Spatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score135.35
Rank#7  Overall
#1  Search engines
Score4.61
Rank#72  Overall
#39  Relational DBMS
Score4.48
Rank#75  Overall
#6  Wide column stores
Score42.91
Rank#24  Overall
#3  Search engines
Websitewww.elastic.co/­elasticsearchwww.embarcadero.com/­products/­interbaseazure.microsoft.com/­en-us/­services/­storage/­tablessolr.apache.org
Technical documentationwww.elastic.co/­guide/­en/­elasticsearch/­reference/­current/­index.htmldocs.embarcadero.com/­products/­interbasesolr.apache.org/­resources.html
DeveloperElasticEmbarcaderoMicrosoftApache Software Foundation
Initial release2010198420122006
Current release8.6, January 2023InterBase 2020, December 20199.6.0, April 2024
License infoCommercial or Open SourceOpen Source infoElastic LicensecommercialcommercialOpen Source infoApache Version 2
Cloud-based only infoOnly available as a cloud servicenonoyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJavaCJava
Server operating systemsAll OS with a Java VMAndroid
iOS
Linux
OS X
Windows
hostedAll OS with a Java VM inforuns as a servlet in servlet container (e.g. Tomcat, Jetty is included)
Data schemeschema-free infoFlexible type definitions. Once a type is defined, it is persistentyesschema-freeyes infoDynamic Fields enables on-the-fly addition of new fields
Typing infopredefined data types such as float or dateyesyesyesyes infosupports customizable data types and automatic typing
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.nono infoexport as XML data possiblenoyes
Secondary indexesyes infoAll search fields are automatically indexedyesnoyes infoAll search fields are automatically indexed
SQL infoSupport of SQLSQL-like query languageyesnoSolr Parallel SQL Interface
APIs and other access methodsJava API
RESTful HTTP/JSON API
ADO.NET
JDBC
ODBC
RESTful HTTP APIJava API
RESTful HTTP/JSON API
Supported programming languages.Net
Groovy
Community Contributed Clients
Java
JavaScript
Perl
PHP
Python
Ruby
.Net
C
C++
Delphi
Java
Object Pascal
PHP
Ruby
.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
Server-side scripts infoStored proceduresyesyes infoInterbase procedure and trigger languagenoJava plugins
Triggersyes infoby using the 'percolation' featureyesnoyes infoUser configurable commands triggered on index changes
Partitioning methods infoMethods for storing different data on different nodesShardingnoneSharding infoImplicit feature of the cloud serviceSharding
Replication methods infoMethods for redundantly storing data on multiple nodesyesInterbase Change Viewsyes infoimplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.yes
MapReduce infoOffers an API for user-defined Map/Reduce methodsES-Hadoop Connectornonospark-solr: github.com/­lucidworks/­spark-solr and streaming expressions to reduce
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual Consistency infoSynchronous doc based replication. Get by ID may show delays up to 1 sec. Configurable write consistency: one, quorum, allImmediate ConsistencyImmediate ConsistencyEventual Consistency
Foreign keys infoReferential integritynoyesnono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDoptimistic lockingoptimistic locking
Concurrency infoSupport for concurrent manipulation of datayesyes infoMultiversion concurreny controlyesyes
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.Memcached and Redis integrationyesnoyes
User concepts infoAccess controlfine grained access rights according to SQL-standardAccess rights based on private key authentication or shared access signaturesyes

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More resources
ElasticsearchInterbaseMicrosoft Azure Table StorageSolr
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