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DBMS > Apache Drill vs. Drizzle vs. Heroic vs. Microsoft Azure Data Explorer

System Properties Comparison Apache Drill vs. Drizzle vs. Heroic vs. Microsoft Azure Data Explorer

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Editorial information provided by DB-Engines
NameApache Drill  Xexclude from comparisonDrizzle  Xexclude from comparisonHeroic  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.
DescriptionSchema-free SQL Query Engine for Hadoop, NoSQL and Cloud StorageMySQL fork with a pluggable micro-kernel and with an emphasis of performance over compatibility.Time Series DBMS built at Spotify based on Cassandra or Google Cloud Bigtable, and ElasticSearchFully managed big data interactive analytics platform
Primary database modelDocument store
Relational DBMS
Relational DBMSTime Series 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)
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
Score2.28
Rank#119  Overall
#23  Document stores
#56  Relational DBMS
Score0.57
Rank#250  Overall
#21  Time Series DBMS
Score5.16
Rank#69  Overall
#37  Relational DBMS
Websitedrill.apache.orggithub.com/­spotify/­heroicazure.microsoft.com/­services/­data-explorer
Technical documentationdrill.apache.org/­docsspotify.github.io/­heroicdocs.microsoft.com/­en-us/­azure/­data-explorer
DeveloperApache Software FoundationDrizzle project, originally started by Brian AkerSpotifyMicrosoft
Initial release2012200820142019
Current release1.20.3, January 20237.2.4, September 2012cloud service with continuous releases
License infoCommercial or Open SourceOpen Source infoApache Version 2Open Source infoGNU GPLOpen Source infoApache 2.0commercial
Cloud-based only infoOnly available as a cloud servicenononoyes
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC++Java
Server operating systemsLinux
OS X
Windows
FreeBSD
Linux
OS X
hosted
Data schemeschema-freeyesschema-freeFixed 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 indexesnoyesyes infovia Elasticsearchall fields are automatically indexed
SQL infoSupport of SQLSQL SELECT statement is SQL:2003 compliantyes infowith proprietary extensionsnoKusto Query Language (KQL), SQL subset
APIs and other access methodsJDBC
ODBC
RESTful HTTP API
JDBCHQL (Heroic Query Language, a JSON-based language)
HTTP API
Microsoft SQL Server communication protocol (MS-TDS)
RESTful HTTP API
Supported programming languagesC++C
C++
Java
PHP
.Net
Go
Java
JavaScript (Node.js)
PowerShell
Python
R
Server-side scripts infoStored proceduresuser defined functionsnonoYes, possible languages: KQL, Python, R
Triggersnono infohooks for callbacks inside the server can be used.noyes infosee docs.microsoft.com/­en-us/­azure/­kusto/­management/­updatepolicy
Partitioning methods infoMethods for storing different data on different nodesShardingShardingShardingSharding infoImplicit feature of the cloud service
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication
Source-replica replication
yesyes infoImplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.
MapReduce infoOffers an API for user-defined Map/Reduce methodsyesnonoSpark connector (open source): github.com/­Azure/­azure-kusto-spark
Consistency concepts infoMethods to ensure consistency in a distributed systemnoneEventual Consistency
Immediate Consistency
Eventual Consistency
Immediate Consistency
Foreign keys infoReferential integritynoyesnono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDnono
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentDepending on the underlying data sourceyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.Depending on the underlying data sourcenono
User concepts infoAccess controlDepending on the underlying data sourcePluggable authentication mechanisms infoe.g. LDAP, HTTPAzure Active Directory Authentication

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More resources
Apache DrillDrizzleHeroicMicrosoft Azure Data Explorer
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