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DBMS > Drizzle vs. Microsoft Azure Data Explorer vs. Oracle Rdb

System Properties Comparison Drizzle vs. Microsoft Azure Data Explorer vs. Oracle Rdb

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Editorial information provided by DB-Engines
NameDrizzle  Xexclude from comparisonMicrosoft Azure Data Explorer  Xexclude from comparisonOracle Rdb  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.
DescriptionMySQL 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 DBMS infocolumn orientedRelational DBMS
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
Score4.38
Rank#77  Overall
#41  Relational DBMS
Score1.08
Rank#184  Overall
#85  Relational DBMS
Websiteazure.microsoft.com/­services/­data-explorerwww.oracle.com/­database/­technologies/­related/­rdb.html
Technical documentationdocs.microsoft.com/­en-us/­azure/­data-explorerwww.oracle.com/­database/­technologies/­related/­rdb-doc.html
DeveloperDrizzle project, originally started by Brian AkerMicrosoftOracle, originally developed by Digital Equipment Corporation (DEC)
Initial release200820191984
Current release7.2.4, September 2012cloud service with continuous releases7.4.1.1, 2021
License infoCommercial or Open SourceOpen Source infoGNU GPLcommercialcommercial
Cloud-based only infoOnly available as a cloud servicenoyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC++
Server operating systemsFreeBSD
Linux
OS X
hostedHP Open VMS
Data schemeyesFixed schema with schema-less datatypes (dynamic)Flexible Schema (defined schema, partial schema, 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.yesno
Secondary indexesyesall fields are automatically indexedyes
SQL infoSupport of SQLyes infowith proprietary extensionsKusto Query Language (KQL), SQL subsetyes
APIs and other access methodsJDBCMicrosoft SQL Server communication protocol (MS-TDS)
RESTful HTTP API
Supported programming languagesC
C++
Java
PHP
.Net
Go
Java
JavaScript (Node.js)
PowerShell
Python
R
Server-side scripts infoStored proceduresnoYes, possible languages: KQL, Python, R
Triggersno 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 nodesShardingSharding infoImplicit feature of the cloud service
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-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 methodsnoSpark connector (open source): github.com/­Azure/­azure-kusto-sparkno
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual Consistency
Immediate Consistency
Immediate Consistency
Foreign keys infoReferential integrityyesnoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDnoyes, on a single node
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 controlPluggable authentication mechanisms infoe.g. LDAP, HTTPAzure Active Directory Authentication

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More resources
DrizzleMicrosoft Azure Data ExplorerOracle Rdb
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