DB-EnginesInfluxDB download bannerEnglish
Deutsch
Knowledge Base of Relational and NoSQL Database Management Systemsprovided by solid IT

DBMS > Heroic vs. Linter vs. Microsoft Azure Data Explorer

System Properties Comparison Heroic vs. Linter vs. Microsoft Azure Data Explorer

Please select another system to include it in the comparison.

Editorial information provided by DB-Engines
NameHeroic  Xexclude from comparisonLinter  Xexclude from comparisonMicrosoft Azure Data Explorer  Xexclude from comparison
DescriptionTime Series DBMS built at Spotify based on Cassandra or Google Cloud Bigtable, and ElasticSearchRDBMS for high security requirementsFully managed big data interactive analytics platform
Primary database modelTime Series DBMSRelational DBMSRelational DBMS infocolumn oriented
Secondary database modelsDocument 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)
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
Score0.39
Rank#248  Overall
#18  Time Series DBMS
Score0.12
Rank#298  Overall
#134  Relational DBMS
Score4.74
Rank#74  Overall
#40  Relational DBMS
Websitespotify.github.io/­heroic/­#!/­indexlinter.ru/­enazure.microsoft.com/­services/­data-explorer
Technical documentationspotify.github.io/­heroic/­#!/­docs/­overviewdocs.microsoft.com/­en-us/­azure/­data-explorer
DeveloperSpotifyrelex.ru/­enMicrosoft
Initial release201419902019
Current releasecloud service with continuous releases
License infoCommercial or Open SourceOpen Source infoApache 2.0commercialcommercial
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 languageJavaC and C++
Server operating systemsAIX
Android
BSD
HP Open VMS
iOS
Linux
OS X
VxWorks
Windows
hosted
Data schemeschema-freeyesFixed schema with schema-less datatypes (dynamic)
Typing infopredefined data types such as float or dateyesyesyes 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 indexesyes infovia Elasticsearchyesall fields are automatically indexed
SQL infoSupport of SQLnoyesKusto Query Language (KQL), SQL subset
APIs and other access methodsHQL (Heroic Query Language, a JSON-based language)
HTTP API
ADO.NET
JDBC
LINQ
ODBC
OLE DB
Oracle Call Interface (OCI)
Microsoft SQL Server communication protocol (MS-TDS)
RESTful HTTP API
Supported programming languagesC
C#
C++
Java
Perl
PHP
Python
Qt
Ruby
Tcl
.Net
Go
Java
JavaScript (Node.js)
PowerShell
Python
R
Server-side scripts infoStored proceduresnoyes infoproprietary syntax with the possibility to convert from PL/SQLYes, possible languages: KQL, Python, R
Triggersnoyesyes infosee docs.microsoft.com/­en-us/­azure/­kusto/­management/­updatepolicy
Partitioning methods infoMethods for storing different data on different nodesShardingnoneSharding infoImplicit feature of the cloud service
Replication methods infoMethods for redundantly storing data on multiple nodesyesSource-replica replicationyes infoImplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonono
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual Consistency
Immediate Consistency
Immediate ConsistencyEventual Consistency
Immediate Consistency
Foreign keys infoReferential integritynoyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDno
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 controlfine grained access rights according to SQL-standardAzure Active Directory Authentication
More information provided by the system vendor
HeroicLinterMicrosoft Azure Data Explorer
Specific characteristicsAzure Data Explorer is a fast and highly scalable data exploration service for log...
» more
Competitive advantagesKusto Query Language (innovative query language, optimized for high performance data...
» more
Typical application scenariosIoT applications IoT devices generate billions of sensor readings. Normalizing and...
» more
Key customersMicrosoft, DocuSign, Taboola, Bosch, Siemens Healthineers, B├╝hler, Ecolab, Zoomd
» more
Market metricsAzure Data Explorer is the data service for Azure Monitor, Azure Time Series Insights,...
» more

We invite representatives of system vendors to contact us for updating and extending the system information,
and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.

Related products and services

We invite representatives of vendors of related products to contact us for presenting information about their offerings here.

More resources
HeroicLinterMicrosoft Azure Data Explorer
Recent citations in the news

Review: Google Bigtable scales with ease
7 September 2016, InfoWorld

provided by Google News

Azure Data Explorer gets new engine, numerous enhancements and Synapse integration
14 October 2020, ZDNet

AMD Boosts Microsoft Azure Data Explorer Performance
16 October 2020, SDxCentral

AMD EPYC Processors Power Microsoft Azure Data Explorer, Offers Users 30 Percent Better Performance
15 October 2020, HPCwire

AMD releases Azure Data Explorer PaaS solution
19 October 2020, IT Brief Australia

Azure Data Explorer gets Synapse integration and other enhancements
15 October 2020, EnterpriseTalk

provided by Google News

Job opportunities

Azure Data Engineer / Architect ( SQL and Power BI)
VTeam Labs, Seattle, WA

Data Engineer
C2S Technologies, Remote

Risk & Compliance Program Manger
Microsoft, Redmond, WA

Content Writer and Developer
Lenora Systems Inc, Redmond, WA

Machine Learning Engineer
ThinkInTree Inc, Redmond, WA

jobs by Indeed




Share this page

Featured Products

Neo4j logo

Get your free copy of the new O'Reilly book Graph Algorithms with 20+ examples for
machine learning, graph analytics and more.

MariaDB logo

SkySQL, the ultimate
MariaDB cloud, is here.

Get started with SkySQL today!

Datastax Astra logo

Build cloud-native apps fast with Astra, the open-source, multi-cloud stack for
modern data apps.
Get started with 5 GB free..

Couchbase logo

SQL + JSON + NoSQL.
Power, flexibility & scale.
All open source.
Get started now.

AllegroGraph logo

Graph Database Leader for AI Knowledge Graph Applications - The Most Secure Graph Database Available.
Free Download

Present your product here