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DBMS > Apache Doris vs. Apache Impala vs. Drizzle vs. Microsoft Azure Data Explorer

System Properties Comparison Apache Doris vs. Apache Impala vs. Drizzle vs. Microsoft Azure Data Explorer

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Editorial information provided by DB-Engines
NameApache Doris  Xexclude from comparisonApache Impala  Xexclude from comparisonDrizzle  Xexclude from comparisonMicrosoft Azure Data Explorer  Xexclude from comparison
Drizzle has published its last release in September 2012. The open-source project is discontinued and Drizzle is excluded from the DB-Engines ranking.
DescriptionAn MPP-based analytics DBMS embracing the MySQL protocolAnalytic DBMS for HadoopMySQL fork with a pluggable micro-kernel and with an emphasis of performance over compatibility.Fully managed big data interactive analytics platform
Primary database modelRelational 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
Score0.57
Rank#244  Overall
#113  Relational DBMS
Score13.77
Rank#40  Overall
#24  Relational DBMS
Score4.38
Rank#77  Overall
#41  Relational DBMS
Websitedoris.apache.org
github.com/­apache/­doris
impala.apache.orgazure.microsoft.com/­services/­data-explorer
Technical documentationgithub.com/­apache/­doris/­wikiimpala.apache.org/­impala-docs.htmldocs.microsoft.com/­en-us/­azure/­data-explorer
DeveloperApache Software Foundation, originally contributed from BaiduApache Software Foundation infoApache top-level project, originally developed by ClouderaDrizzle project, originally started by Brian AkerMicrosoft
Initial release2017201320082019
Current release1.2.2, February 20234.1.0, June 20227.2.4, September 2012cloud service with continuous releases
License infoCommercial or Open SourceOpen Source infoApache Version 2.0Open Source infoApache Version 2Open Source infoGNU GPLcommercial
Cloud-based only infoOnly available as a cloud servicenononoyes
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaC++C++
Server operating systemsLinuxLinuxFreeBSD
Linux
OS X
hosted
Data schemeyesyesyesFixed schema with schema-less datatypes (dynamic)
Typing infopredefined data types such as float or dateyesyesyesyes 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 indexesyesyesyesall fields are automatically indexed
SQL infoSupport of SQLyesSQL-like DML and DDL statementsyes infowith proprietary extensionsKusto Query Language (KQL), SQL subset
APIs and other access methodsJDBC
MySQL client
JDBC
ODBC
JDBCMicrosoft SQL Server communication protocol (MS-TDS)
RESTful HTTP API
Supported programming languagesJavaAll languages supporting JDBC/ODBCC
C++
Java
PHP
.Net
Go
Java
JavaScript (Node.js)
PowerShell
Python
R
Server-side scripts infoStored proceduresuser defined functionsyes infouser defined functions and integration of map-reducenoYes, possible languages: KQL, Python, R
Triggersnonono infohooks for callbacks inside the server can be used.yes infosee docs.microsoft.com/­en-us/­azure/­kusto/­management/­updatepolicy
Partitioning methods infoMethods for storing different data on different nodeshorizontal partitioningShardingShardingSharding infoImplicit feature of the cloud service
Replication methods infoMethods for redundantly storing data on multiple nodesnoneselectable replication factorMulti-source replication
Source-replica replication
yes 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 MapReducenoSpark connector (open source): github.com/­Azure/­azure-kusto-spark
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyEventual ConsistencyEventual Consistency
Immediate Consistency
Foreign keys infoReferential integritynonoyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDno
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.nonono
User concepts infoAccess controlfine grained access rights according to SQL-standardAccess rights for users, groups and roles infobased on Apache Sentry and KerberosPluggable authentication mechanisms infoe.g. LDAP, HTTPAzure Active Directory Authentication

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More resources
Apache DorisApache ImpalaDrizzleMicrosoft Azure Data Explorer
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