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DBMS > Amazon Redshift vs. Apache Impala vs. Hive vs. Microsoft Access vs. Microsoft Azure Data Explorer

System Properties Comparison Amazon Redshift vs. Apache Impala vs. Hive vs. Microsoft Access vs. Microsoft Azure Data Explorer

Editorial information provided by DB-Engines
NameAmazon Redshift  Xexclude from comparisonApache Impala  Xexclude from comparisonHive  Xexclude from comparisonMicrosoft Access  Xexclude from comparisonMicrosoft Azure Data Explorer  Xexclude from comparison
DescriptionLarge scale data warehouse service for use with business intelligence toolsAnalytic DBMS for Hadoopdata warehouse software for querying and managing large distributed datasets, built on HadoopMicrosoft Access combines a backend RDBMS (JET / ACE Engine) with a GUI frontend for data manipulation and queries. infoThe Access frontend is often used for accessing other datasources (DBMS, Excel, etc.)Fully managed big data interactive analytics platform
Primary database modelRelational DBMSRelational DBMSRelational DBMSRelational DBMSRelational DBMS infocolumn oriented
Secondary database modelsDocument storeDocument 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
Score17.94
Rank#34  Overall
#21  Relational DBMS
Score13.77
Rank#40  Overall
#24  Relational DBMS
Score61.17
Rank#18  Overall
#12  Relational DBMS
Score104.92
Rank#11  Overall
#8  Relational DBMS
Score4.38
Rank#77  Overall
#41  Relational DBMS
Websiteaws.amazon.com/­redshiftimpala.apache.orghive.apache.orgwww.microsoft.com/­en-us/­microsoft-365/­accessazure.microsoft.com/­services/­data-explorer
Technical documentationdocs.aws.amazon.com/­redshiftimpala.apache.org/­impala-docs.htmlcwiki.apache.org/­confluence/­display/­Hive/­Homedeveloper.microsoft.com/­en-us/­accessdocs.microsoft.com/­en-us/­azure/­data-explorer
DeveloperAmazon (based on PostgreSQL)Apache Software Foundation infoApache top-level project, originally developed by ClouderaApache Software Foundation infoinitially developed by FacebookMicrosoftMicrosoft
Initial release20122013201219922019
Current release4.1.0, June 20223.1.3, April 20221902 (16.0.11328.20222), March 2019cloud service with continuous releases
License infoCommercial or Open SourcecommercialOpen Source infoApache Version 2Open Source infoApache Version 2commercial infoBundled with Microsoft Officecommercial
Cloud-based only infoOnly available as a cloud serviceyesnononoyes
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageCC++JavaC++
Server operating systemshostedLinuxAll OS with a Java VMWindows infoNot a real database server, but making use of DLLshosted
Data schemeyesyesyesyesFixed schema with schema-less datatypes (dynamic)
Typing infopredefined data types such as float or dateyesyesyesyesyes infobool, datetime, dynamic, guid, int, long, real, string, timespan, double: docs.microsoft.com/­en-us/­azure/­kusto/­query/­scalar-data-types
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 indexesrestrictedyesyesyesall fields are automatically indexed
SQL infoSupport of SQLyes infodoes not fully support an SQL-standardSQL-like DML and DDL statementsSQL-like DML and DDL statementsyes infobut not compliant to any SQL standardKusto Query Language (KQL), SQL subset
APIs and other access methodsJDBC
ODBC
JDBC
ODBC
JDBC
ODBC
Thrift
ADO.NET
DAO
ODBC
OLE DB
Microsoft SQL Server communication protocol (MS-TDS)
RESTful HTTP API
Supported programming languagesAll languages supporting JDBC/ODBCAll languages supporting JDBC/ODBCC++
Java
PHP
Python
C
C#
C++
Delphi
Java (JDBC-ODBC)
VBA
Visual Basic.NET
.Net
Go
Java
JavaScript (Node.js)
PowerShell
Python
R
Server-side scripts infoStored proceduresuser defined functions infoin Pythonyes infouser defined functions and integration of map-reduceyes infouser defined functions and integration of map-reduceyes infosince Access 2010 using the ACE-engineYes, possible languages: KQL, Python, R
Triggersnononoyes infosince Access 2010 using the ACE-engineyes infosee docs.microsoft.com/­en-us/­azure/­kusto/­management/­updatepolicy
Partitioning methods infoMethods for storing different data on different nodesShardingShardingShardingnoneSharding infoImplicit feature of the cloud service
Replication methods infoMethods for redundantly storing data on multiple nodesyesselectable replication factorselectable replication factornoneyes infoImplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyes infoquery execution via MapReduceyes infoquery execution via MapReducenoSpark connector (open source): github.com/­Azure/­azure-kusto-spark
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyEventual ConsistencyEventual ConsistencyEventual Consistency
Immediate Consistency
Foreign keys infoReferential integrityyes infoinformational only, not enforced by the systemnonoyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDnonoACID infobut no files for transaction loggingno
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentyesyesyesyes infobut no files for transaction loggingyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesnono
User concepts infoAccess controlfine grained access rights according to SQL-standardAccess rights for users, groups and roles infobased on Apache Sentry and KerberosAccess rights for users, groups and rolesno infoa simple user-level security was built in till version Access 2003Azure Active Directory Authentication

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Amazon RedshiftApache ImpalaHiveMicrosoft AccessMicrosoft Azure Data Explorer
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