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DBMS > Apache Impala vs. CouchDB vs. InterSystems IRIS vs. Microsoft Azure Data Explorer vs. XTDB

System Properties Comparison Apache Impala vs. CouchDB vs. InterSystems IRIS vs. Microsoft Azure Data Explorer vs. XTDB

Editorial information provided by DB-Engines
NameApache Impala  Xexclude from comparisonCouchDB infostands for "Cluster Of Unreliable Commodity Hardware"  Xexclude from comparisonInterSystems IRIS  Xexclude from comparisonMicrosoft Azure Data Explorer  Xexclude from comparisonXTDB infoformerly named Crux  Xexclude from comparison
DescriptionAnalytic DBMS for HadoopA native JSON - document store inspired by Lotus Notes, scalable from globally distributed server-clusters down to mobile phones.A containerised multi-model DBMS, interoperability and analytics data platform with wide capabilities for vertical and horizontal scalabilityFully managed big data interactive analytics platformA general purpose database with bitemporal SQL and Datalog and graph queries
Primary database modelRelational DBMSDocument storeDocument store
Key-value store
Object oriented DBMS
Relational DBMS
Relational DBMS infocolumn orientedDocument store
Secondary database modelsDocument storeSpatial DBMS infousing the Geocouch extensionDocument 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
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score13.77
Rank#40  Overall
#24  Relational DBMS
Score9.30
Rank#45  Overall
#7  Document stores
Score4.05
Rank#83  Overall
#14  Document stores
#10  Key-value stores
#1  Object oriented DBMS
#45  Relational DBMS
Score4.38
Rank#77  Overall
#41  Relational DBMS
Score0.11
Rank#343  Overall
#46  Document stores
Websiteimpala.apache.orgcouchdb.apache.orgwww.intersystems.com/­products/­intersystems-irisazure.microsoft.com/­services/­data-explorergithub.com/­xtdb/­xtdb
www.xtdb.com
Technical documentationimpala.apache.org/­impala-docs.htmldocs.couchdb.org/­en/­stabledocs.intersystems.com/­irislatest/­csp/­docbook/­DocBook.UI.Page.clsdocs.microsoft.com/­en-us/­azure/­data-explorerwww.xtdb.com/­docs
DeveloperApache Software Foundation infoApache top-level project, originally developed by ClouderaApache Software Foundation infoApache top-level project, originally developed by Damien Katz, a former Lotus Notes developerInterSystemsMicrosoftJuxt Ltd.
Initial release20132005201820192019
Current release4.1.0, June 20223.3.3, December 20232023.3, June 2023cloud service with continuous releases1.19, September 2021
License infoCommercial or Open SourceOpen Source infoApache Version 2Open Source infoApache version 2commercialcommercialOpen Source infoMIT License
Cloud-based only infoOnly available as a cloud servicenononoyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageC++ErlangClojure
Server operating systemsLinuxAndroid
BSD
Linux
OS X
Solaris
Windows
AIX
Linux
macOS
Ubuntu
Windows
hostedAll OS with a Java 8 (and higher) VM
Linux
Data schemeyesschema-freedepending on used data modelFixed schema with schema-less datatypes (dynamic)schema-free
Typing infopredefined data types such as float or dateyesnoyesyes infobool, datetime, dynamic, guid, int, long, real, string, timespan, double: docs.microsoft.com/­en-us/­azure/­kusto/­query/­scalar-data-typesyes, extensible-data-notation format
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.nonoyesyesno
Secondary indexesyesyes infovia viewsyesall fields are automatically indexedyes
SQL infoSupport of SQLSQL-like DML and DDL statementsnoyesKusto Query Language (KQL), SQL subsetlimited SQL, making use of Apache Calcite
APIs and other access methodsJDBC
ODBC
RESTful HTTP/JSON APIJDBC
ODBC
RESTful HTTP API
Microsoft SQL Server communication protocol (MS-TDS)
RESTful HTTP API
HTTP REST
JDBC
Supported programming languagesAll languages supporting JDBC/ODBCC
C#
ColdFusion
Erlang
Haskell
Java
JavaScript
Lisp
Lua
Objective-C
OCaml
Perl
PHP
PL/SQL
Python
Ruby
Smalltalk
.Net
C++
Java
JavaScript (Node.js)
Python
.Net
Go
Java
JavaScript (Node.js)
PowerShell
Python
R
Clojure
Java
Server-side scripts infoStored proceduresyes infouser defined functions and integration of map-reduceView functions in JavaScriptyesYes, possible languages: KQL, Python, Rno
Triggersnoyesyesyes infosee docs.microsoft.com/­en-us/­azure/­kusto/­management/­updatepolicyno
Partitioning methods infoMethods for storing different data on different nodesShardingSharding infoimproved architecture with release 2.0ShardingSharding infoImplicit feature of the cloud servicenone
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factorMulti-source replication
Source-replica replication
Source-replica replicationyes infoImplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.yes, each node contains all data
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infoquery execution via MapReduceyesnoSpark connector (open source): github.com/­Azure/­azure-kusto-sparkno
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual ConsistencyEventual ConsistencyImmediate ConsistencyEventual Consistency
Immediate Consistency
Foreign keys infoReferential integritynonoyesnono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanono infoatomic operations within a single document possibleACIDnoACID
Concurrency infoSupport for concurrent manipulation of datayesyes infostrategy: optimistic lockingyesyesyes
Durability infoSupport for making data persistentyesyesyesyesyes, flexibel persistency by using storage technologies like Apache Kafka, RocksDB or LMDB
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.nonoyesno
User concepts infoAccess controlAccess rights for users, groups and roles infobased on Apache Sentry and KerberosAccess rights for users can be defined per databaseyesAzure Active Directory Authentication
More information provided by the system vendor
Apache ImpalaCouchDB infostands for "Cluster Of Unreliable Commodity Hardware"InterSystems IRISMicrosoft Azure Data ExplorerXTDB infoformerly named Crux
Specific characteristicsInterSystems IRIS is a complete cloud-first data platform which includes a multi-model...
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More resources
Apache ImpalaCouchDB infostands for "Cluster Of Unreliable Commodity Hardware"InterSystems IRISMicrosoft Azure Data ExplorerXTDB infoformerly named Crux
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