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DBMS > Elasticsearch vs. IBM Db2 vs. Microsoft Azure Data Explorer vs. Solr vs. Trafodion

System Properties Comparison Elasticsearch vs. IBM Db2 vs. Microsoft Azure Data Explorer vs. Solr vs. Trafodion

Editorial information provided by DB-Engines
NameElasticsearch  Xexclude from comparisonIBM Db2 infoformerly named DB2 or IBM Database 2  Xexclude from comparisonMicrosoft Azure Data Explorer  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.
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 metricCommon in IBM host environments, 2 different versions for host and Windows/LinuxFully managed big data interactive analytics platformA widely used distributed, scalable search engine based on Apache LuceneTransactional SQL-on-Hadoop DBMS
Primary database modelSearch engineRelational DBMS infoSince Version 10.5 support for JSON/BSON documents compatible with MongoDBRelational DBMS infocolumn orientedSearch engineRelational DBMS
Secondary database modelsDocument store
Spatial DBMS
Vector DBMS
Document store
RDF store infoin Db2 LUW (Linux, Unix, Windows)
Spatial DBMS infowith Db2 Spatial Extender
Document store infoIf a column is of type dynamic docs.microsoft.com/­en-us/­azure/­kusto/­query/­scalar-data-types/­dynamic then it's possible to add arbitrary JSON documents in this cell
Event Store infothis is the general usage pattern at Microsoft. Billing, Logs, Telemetry events are stored in ADX and the state of an individual entity is defined by the arg_max(timestamps)
Spatial DBMS
Search engine infosupport for complex search expressions docs.microsoft.com/­en-us/­azure/­kusto/­query/­parseoperator FTS, Geospatial docs.microsoft.com/­en-us/­azure/­kusto/­query/­geo-point-to-geohash-function distributed search -> ADX acts as a distributed search engine
Time Series DBMS infosee docs.microsoft.com/­en-us/­azure/­data-explorer/­time-series-analysis
Spatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score134.78
Rank#7  Overall
#1  Search engines
Score127.49
Rank#8  Overall
#5  Relational DBMS
Score5.16
Rank#69  Overall
#37  Relational DBMS
Score44.28
Rank#24  Overall
#3  Search engines
Websitewww.elastic.co/­elasticsearchwww.ibm.com/­products/­db2azure.microsoft.com/­services/­data-explorersolr.apache.orgtrafodion.apache.org
Technical documentationwww.elastic.co/­guide/­en/­elasticsearch/­reference/­current/­index.htmlwww.ibm.com/­docs/­en/­db2docs.microsoft.com/­en-us/­azure/­data-explorersolr.apache.org/­resources.htmltrafodion.apache.org/­documentation.html
DeveloperElasticIBMMicrosoftApache Software FoundationApache Software Foundation, originally developed by HP
Initial release20101983 infohost version201920062014
Current release8.6, January 202312.1, October 2016cloud service with continuous releases9.5.0, February 20242.3.0, February 2019
License infoCommercial or Open SourceOpen Source infoElastic Licensecommercial infofree version is availablecommercialOpen Source infoApache Version 2Open Source infoApache 2.0
Cloud-based only infoOnly available as a cloud servicenonoyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJavaC and C++JavaC++, Java
Server operating systemsAll OS with a Java VMAIX
HP-UX
Linux
Solaris
Windows
z/OS
hostedAll OS with a Java VM inforuns as a servlet in servlet container (e.g. Tomcat, Jetty is included)Linux
Data schemeschema-free infoFlexible type definitions. Once a type is defined, it is persistentyesFixed schema with schema-less datatypes (dynamic)yes infoDynamic Fields enables on-the-fly addition of new fieldsyes
Typing infopredefined data types such as float or dateyesyesyes infobool, datetime, dynamic, guid, int, long, real, string, timespan, double: docs.microsoft.com/­en-us/­azure/­kusto/­query/­scalar-data-typesyes 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.noyesyesno
Secondary indexesyes infoAll search fields are automatically indexedyesall fields are automatically indexedyes infoAll search fields are automatically indexedyes
SQL infoSupport of SQLSQL-like query languageyesKusto Query Language (KQL), SQL subsetSolr Parallel SQL Interfaceyes
APIs and other access methodsJava API
RESTful HTTP/JSON API
ADO.NET
JDBC
JSON style queries infoMongoDB compatible
ODBC
XQuery
Microsoft SQL Server communication protocol (MS-TDS)
RESTful HTTP API
Java API
RESTful HTTP/JSON API
ADO.NET
JDBC
ODBC
Supported programming languages.Net
Groovy
Community Contributed Clients
Java
JavaScript
Perl
PHP
Python
Ruby
C
C#
C++
Cobol
Delphi
Fortran
Java
Perl
PHP
Python
Ruby
Visual Basic
.Net
Go
Java
JavaScript (Node.js)
PowerShell
Python
R
.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 proceduresyesyesYes, possible languages: KQL, Python, RJava pluginsJava Stored Procedures
Triggersyes infoby using the 'percolation' featureyesyes infosee docs.microsoft.com/­en-us/­azure/­kusto/­management/­updatepolicyyes infoUser configurable commands triggered on index changesno
Partitioning methods infoMethods for storing different data on different nodesShardingSharding infoonly with Windows/Unix/Linux VersionSharding infoImplicit feature of the cloud serviceShardingSharding
Replication methods infoMethods for redundantly storing data on multiple nodesyesyes infowith separate tools (MQ, InfoSphere)yes 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 methodsES-Hadoop ConnectornoSpark connector (open source): github.com/­Azure/­azure-kusto-sparkspark-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 systemEventual Consistency infoSynchronous doc based replication. Get by ID may show delays up to 1 sec. Configurable write consistency: one, quorum, allEventual Consistency
Immediate Consistency
Eventual ConsistencyImmediate Consistency
Foreign keys infoReferential integritynoyesnonoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDnooptimistic lockingACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
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.Memcached and Redis integrationnoyesno
User concepts infoAccess controlfine grained access rights according to SQL-standardAzure Active Directory Authenticationyesfine grained access rights according to SQL-standard

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More resources
ElasticsearchIBM Db2 infoformerly named DB2 or IBM Database 2Microsoft Azure Data ExplorerSolrTrafodion
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