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DBMS > Apache Impala vs. Cubrid vs. Microsoft Azure SQL Database

System Properties Comparison Apache Impala vs. Cubrid vs. Microsoft Azure SQL Database

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Editorial information provided by DB-Engines
NameApache Impala  Xexclude from comparisonCubrid  Xexclude from comparisonMicrosoft Azure SQL Database infoformerly SQL Azure  Xexclude from comparison
DescriptionAnalytic DBMS for HadoopCUBRID is an open-source SQL-based relational database management system with object extensions for OLTPDatabase as a Service offering with high compatibility to Microsoft SQL Server
Primary database modelRelational DBMSRelational DBMSRelational DBMS
Secondary database modelsDocument storeDocument store
Graph DBMS
Spatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score14.03
Rank#40  Overall
#24  Relational DBMS
Score1.31
Rank#169  Overall
#78  Relational DBMS
Score78.40
Rank#15  Overall
#10  Relational DBMS
Websiteimpala.apache.orgcubrid.com (korean)
cubrid.org (english)
azure.microsoft.com/­en-us/­products/­azure-sql/­database
Technical documentationimpala.apache.org/­impala-docs.htmlcubrid.org/­manualsdocs.microsoft.com/­en-us/­azure/­azure-sql
DeveloperApache Software Foundation infoApache top-level project, originally developed by ClouderaCUBRID Corporation, CUBRID FoundationMicrosoft
Initial release201320082010
Current release4.1.0, June 202211.0, January 2021V12
License infoCommercial or Open SourceOpen Source infoApache Version 2Open Source infoApache Version 2.0commercial
Cloud-based only infoOnly available as a cloud servicenonoyes
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageC++C, C++, JavaC++
Server operating systemsLinuxLinux
Windows
hosted
Data schemeyesyesyes
Typing infopredefined data types such as float or dateyesyesyes
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.nonoyes
Secondary indexesyesyesyes
SQL infoSupport of SQLSQL-like DML and DDL statementsyesyes
APIs and other access methodsJDBC
ODBC
ADO.NET
JDBC
ODBC
OLE DB
ADO.NET
JDBC
ODBC
Supported programming languagesAll languages supporting JDBC/ODBCC
C#
C++
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
Ruby
.Net
C#
Java
JavaScript (Node.js)
PHP
Python
Ruby
Server-side scripts infoStored proceduresyes infouser defined functions and integration of map-reduceJava Stored ProceduresTransact SQL
Triggersnoyesyes
Partitioning methods infoMethods for storing different data on different nodesShardingnone
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factorSource-replica replicationyes, with always 3 replicas available
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infoquery execution via MapReducenono
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual ConsistencyImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynoyesyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDACID
Concurrency infoSupport for concurrent manipulation of datayesyesyes
Durability infoSupport for making data persistentyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.nono
User concepts infoAccess controlAccess rights for users, groups and roles infobased on Apache Sentry and Kerberosfine grained access rights according to SQL-standardfine grained access rights according to SQL-standard

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More resources
Apache ImpalaCubridMicrosoft Azure SQL Database infoformerly SQL Azure
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Recent citations in the news

Apache Impala 4 Supports Operator Multi-Threading
29 July 2021, iProgrammer

Apache Impala becomes Top-Level Project
28 November 2017, SDTimes.com

Cloudera Bringing Impala to AWS Cloud
28 November 2017, Datanami

Apache Doris just 'graduated': Why care about this SQL data warehouse
24 June 2022, InfoWorld

Hudi: Uber Engineering’s Incremental Processing Framework on Apache Hadoop
12 March 2017, Uber

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22 April 2024, PR Urgent

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