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DBMS > Apache Impala vs. Citus vs. Microsoft Azure Table Storage vs. XTDB vs. Yanza

System Properties Comparison Apache Impala vs. Citus vs. Microsoft Azure Table Storage vs. XTDB vs. Yanza

Editorial information provided by DB-Engines
NameApache Impala  Xexclude from comparisonCitus  Xexclude from comparisonMicrosoft Azure Table Storage  Xexclude from comparisonXTDB infoformerly named Crux  Xexclude from comparisonYanza  Xexclude from comparison
Yanza seems to be discontinued. Therefore it is excluded from the DB-Engines Ranking.
DescriptionAnalytic DBMS for HadoopScalable hybrid operational and analytics RDBMS for big data use cases based on PostgreSQLA Wide Column Store for rapid development using massive semi-structured datasetsA general purpose database with bitemporal SQL and Datalog and graph queriesTime Series DBMS for IoT Applications
Primary database modelRelational DBMSRelational DBMSWide column storeDocument storeTime Series DBMS
Secondary database modelsDocument storeDocument store
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score12.45
Rank#40  Overall
#24  Relational DBMS
Score2.15
Rank#117  Overall
#56  Relational DBMS
Score4.04
Rank#77  Overall
#6  Wide column stores
Score0.18
Rank#332  Overall
#46  Document stores
Websiteimpala.apache.orgwww.citusdata.comazure.microsoft.com/­en-us/­services/­storage/­tablesgithub.com/­xtdb/­xtdb
www.xtdb.com
yanza.com
Technical documentationimpala.apache.org/­impala-docs.htmldocs.citusdata.comwww.xtdb.com/­docs
DeveloperApache Software Foundation infoApache top-level project, originally developed by ClouderaMicrosoftJuxt Ltd.Yanza
Initial release20132010201220192015
Current release4.1.0, June 20228.1, December 20181.19, September 2021
License infoCommercial or Open SourceOpen Source infoApache Version 2Open Source infoAGPL, commercial license also availablecommercialOpen Source infoMIT Licensecommercial infofree version available
Cloud-based only infoOnly available as a cloud servicenonoyesnono infobut mainly used as a service provided by Yanza
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageC++CClojure
Server operating systemsLinuxLinuxhostedAll OS with a Java 8 (and higher) VM
Linux
Windows
Data schemeyesyesschema-freeschema-freeschema-free
Typing infopredefined data types such as float or dateyesyesyesyes, extensible-data-notation formatno
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.noyes infospecific XML type available, but no XML query functionalitynonono
Secondary indexesyesyesnoyesno
SQL infoSupport of SQLSQL-like DML and DDL statementsyes infostandard, with numerous extensionsnolimited SQL, making use of Apache Calciteno
APIs and other access methodsJDBC
ODBC
ADO.NET
JDBC
native C library
ODBC
streaming API for large objects
RESTful HTTP APIHTTP REST
JDBC
HTTP API
Supported programming languagesAll languages supporting JDBC/ODBC.Net
C
C++
Delphi
Java
JavaScript (Node.js)
Perl
PHP
Python
Tcl
.Net
C#
C++
Java
JavaScript (Node.js)
PHP
Python
Ruby
Clojure
Java
any language that supports HTTP calls
Server-side scripts infoStored proceduresyes infouser defined functions and integration of map-reduceuser defined functions inforealized in proprietary language PL/pgSQL or with common languages like Perl, Python, Tcl etc.nonono
Triggersnoyesnonoyes infoTimer and event based
Partitioning methods infoMethods for storing different data on different nodesShardingShardingSharding infoImplicit feature of the cloud servicenonenone
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factorSource-replica replication infoother methods possible by using 3rd party extensionsyes infoimplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.yes, each node contains all datanone
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infoquery execution via MapReducenononono
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual ConsistencyImmediate ConsistencyImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynoyesnonono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDoptimistic lockingACIDno
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentyesyesyesyes, flexibel persistency by using storage technologies like Apache Kafka, RocksDB or LMDByes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.nonono
User concepts infoAccess controlAccess rights for users, groups and roles infobased on Apache Sentry and Kerberosfine grained access rights according to SQL-standardAccess rights based on private key authentication or shared access signaturesno

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More resources
Apache ImpalaCitusMicrosoft Azure Table StorageXTDB infoformerly named CruxYanza
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