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

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

Editorial information provided by DB-Engines
NameApache Impala  Xexclude from comparisonCitus  Xexclude from comparisonGBase  Xexclude from comparisonMicrosoft Azure Table Storage  Xexclude from comparisonXTDB infoformerly named Crux  Xexclude from comparison
DescriptionAnalytic DBMS for HadoopScalable hybrid operational and analytics RDBMS for big data use cases based on PostgreSQLWidely used RDBMS in China, including analytical, transactional, distributed transactional, and cloud-native data warehousing.A Wide Column Store for rapid development using massive semi-structured datasetsA general purpose database with bitemporal SQL and Datalog and graph queries
Primary database modelRelational DBMSRelational DBMSRelational DBMSWide column storeDocument store
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
Score1.05
Rank#186  Overall
#86  Relational DBMS
Score4.04
Rank#77  Overall
#6  Wide column stores
Score0.18
Rank#332  Overall
#46  Document stores
Websiteimpala.apache.orgwww.citusdata.comwww.gbase.cnazure.microsoft.com/­en-us/­services/­storage/­tablesgithub.com/­xtdb/­xtdb
www.xtdb.com
Technical documentationimpala.apache.org/­impala-docs.htmldocs.citusdata.comwww.xtdb.com/­docs
DeveloperApache Software Foundation infoApache top-level project, originally developed by ClouderaGeneral Data Technology Co., Ltd.MicrosoftJuxt Ltd.
Initial release20132010200420122019
Current release4.1.0, June 20228.1, December 2018GBase 8a, GBase 8s, GBase 8c1.19, September 2021
License infoCommercial or Open SourceOpen Source infoApache Version 2Open Source infoAGPL, commercial license also availablecommercialcommercialOpen Source infoMIT License
Cloud-based only infoOnly available as a cloud servicenononoyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC++CC, Java, PythonClojure
Server operating systemsLinuxLinuxLinuxhostedAll OS with a Java 8 (and higher) VM
Linux
Data schemeyesyesyesschema-freeschema-free
Typing infopredefined data types such as float or dateyesyesyesyesyes, 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.noyes infospecific XML type available, but no XML query functionalityyesnono
Secondary indexesyesyesyesnoyes
SQL infoSupport of SQLSQL-like DML and DDL statementsyes infostandard, with numerous extensionsStandard with numerous extensionsnolimited SQL, making use of Apache Calcite
APIs and other access methodsJDBC
ODBC
ADO.NET
JDBC
native C library
ODBC
streaming API for large objects
ADO.NET
C API
JDBC
ODBC
RESTful HTTP APIHTTP REST
JDBC
Supported programming languagesAll languages supporting JDBC/ODBC.Net
C
C++
Delphi
Java
JavaScript (Node.js)
Perl
PHP
Python
Tcl
C#.Net
C#
C++
Java
JavaScript (Node.js)
PHP
Python
Ruby
Clojure
Java
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.user defined functionsnono
Triggersnoyesyesnono
Partitioning methods infoMethods for storing different data on different nodesShardingShardinghorizontal partitioning (by range, list and hash) and vertical partitioningSharding infoImplicit feature of the cloud servicenone
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factorSource-replica replication infoother methods possible by using 3rd party extensionsyesyes 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 MapReducenonono
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual ConsistencyImmediate ConsistencyImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynoyesyesnono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDACIDoptimistic lockingACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
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.nonono
User concepts infoAccess controlAccess rights for users, groups and roles infobased on Apache Sentry and Kerberosfine grained access rights according to SQL-standardyesAccess rights based on private key authentication or shared access signatures

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More resources
Apache ImpalaCitusGBaseMicrosoft Azure Table StorageXTDB infoformerly named Crux
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