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DBMS > Apache Impala vs. Microsoft Azure Data Explorer vs. OrigoDB

System Properties Comparison Apache Impala vs. Microsoft Azure Data Explorer vs. OrigoDB

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Editorial information provided by DB-Engines
NameApache Impala  Xexclude from comparisonMicrosoft Azure Data Explorer  Xexclude from comparisonOrigoDB  Xexclude from comparison
DescriptionAnalytic DBMS for HadoopFully managed big data interactive analytics platformA fully ACID in-memory object graph database
Primary database modelRelational DBMSRelational DBMS infocolumn orientedDocument store
Object oriented DBMS
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
Score14.03
Rank#40  Overall
#24  Relational DBMS
Score5.16
Rank#69  Overall
#37  Relational DBMS
Score0.03
Rank#378  Overall
#51  Document stores
#18  Object oriented DBMS
Websiteimpala.apache.orgazure.microsoft.com/­services/­data-explorerorigodb.com
Technical documentationimpala.apache.org/­impala-docs.htmldocs.microsoft.com/­en-us/­azure/­data-explorerorigodb.com/­docs
DeveloperApache Software Foundation infoApache top-level project, originally developed by ClouderaMicrosoftRobert Friberg et al
Initial release201320192009 infounder the name LiveDB
Current release4.1.0, June 2022cloud service with continuous releases
License infoCommercial or Open SourceOpen Source infoApache Version 2commercialOpen Source
Cloud-based only infoOnly available as a cloud servicenoyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC++C#
Server operating systemsLinuxhostedLinux
Windows
Data schemeyesFixed schema with schema-less datatypes (dynamic)yes
Typing infopredefined data types such as float or dateyesyes infobool, datetime, dynamic, guid, int, long, real, string, timespan, double: docs.microsoft.com/­en-us/­azure/­kusto/­query/­scalar-data-typesUser defined using .NET types and collections
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.noyesno infocan be achieved using .NET
Secondary indexesyesall fields are automatically indexedyes
SQL infoSupport of SQLSQL-like DML and DDL statementsKusto Query Language (KQL), SQL subsetno
APIs and other access methodsJDBC
ODBC
Microsoft SQL Server communication protocol (MS-TDS)
RESTful HTTP API
.NET Client API
HTTP API
LINQ
Supported programming languagesAll languages supporting JDBC/ODBC.Net
Go
Java
JavaScript (Node.js)
PowerShell
Python
R
.Net
Server-side scripts infoStored proceduresyes infouser defined functions and integration of map-reduceYes, possible languages: KQL, Python, Ryes
Triggersnoyes infosee docs.microsoft.com/­en-us/­azure/­kusto/­management/­updatepolicyyes infoDomain Events
Partitioning methods infoMethods for storing different data on different nodesShardingSharding infoImplicit feature of the cloud servicehorizontal partitioning infoclient side managed; servers are not synchronized
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factoryes infoImplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infoquery execution via MapReduceSpark connector (open source): github.com/­Azure/­azure-kusto-sparkno
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual ConsistencyEventual Consistency
Immediate Consistency
Foreign keys infoReferential integritynonodepending on model
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanonoACID
Concurrency infoSupport for concurrent manipulation of datayesyesyes
Durability infoSupport for making data persistentyesyesyes infoWrite ahead log
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.nonoyes
User concepts infoAccess controlAccess rights for users, groups and roles infobased on Apache Sentry and KerberosAzure Active Directory AuthenticationRole based authorization

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More resources
Apache ImpalaMicrosoft Azure Data ExplorerOrigoDB
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