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

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

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Editorial information provided by DB-Engines
NameApache Impala  Xexclude from comparisonMicrosoft Azure Data Explorer  Xexclude from comparisonTempoIQ infoformerly TempoDB  Xexclude from comparison
TempoIQ seems to be decommissioned. It will be removed from the DB-Engines ranking.
DescriptionAnalytic DBMS for HadoopFully managed big data interactive analytics platformScalable analytics DBMS for sensor data, provided as a service (SaaS)
Primary database modelRelational DBMSRelational DBMS infocolumn orientedTime Series 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
Score13.77
Rank#40  Overall
#24  Relational DBMS
Score4.38
Rank#77  Overall
#41  Relational DBMS
Websiteimpala.apache.orgazure.microsoft.com/­services/­data-explorertempoiq.com (offline)
Technical documentationimpala.apache.org/­impala-docs.htmldocs.microsoft.com/­en-us/­azure/­data-explorer
DeveloperApache Software Foundation infoApache top-level project, originally developed by ClouderaMicrosoftTempoIQ
Initial release201320192012
Current release4.1.0, June 2022cloud service with continuous releases
License infoCommercial or Open SourceOpen Source infoApache Version 2commercialcommercial
Cloud-based only infoOnly available as a cloud servicenoyesyes
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageC++
Server operating systemsLinuxhosted
Data schemeyesFixed schema with schema-less datatypes (dynamic)schema-free
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-typesyes
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
Secondary indexesyesall fields are automatically indexed
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
HTTP API
Supported programming languagesAll languages supporting JDBC/ODBC.Net
Go
Java
JavaScript (Node.js)
PowerShell
Python
R
C#
Java
JavaScript infoNode.js
Python
Ruby
Server-side scripts infoStored proceduresyes infouser defined functions and integration of map-reduceYes, possible languages: KQL, Python, Rno
Triggersnoyes infosee docs.microsoft.com/­en-us/­azure/­kusto/­management/­updatepolicyyes infoRealtime Alerts
Partitioning methods infoMethods for storing different data on different nodesShardingSharding infoImplicit feature of the cloud service
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.
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 integritynonono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanonono
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.nonono
User concepts infoAccess controlAccess rights for users, groups and roles infobased on Apache Sentry and KerberosAzure Active Directory Authenticationsimple authentication-based access control

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More resources
Apache ImpalaMicrosoft Azure Data ExplorerTempoIQ infoformerly TempoDB
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