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DBMS > Drizzle vs. LeanXcale vs. Microsoft Azure Data Explorer vs. Realm

System Properties Comparison Drizzle vs. LeanXcale vs. Microsoft Azure Data Explorer vs. Realm

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Editorial information provided by DB-Engines
NameDrizzle  Xexclude from comparisonLeanXcale  Xexclude from comparisonMicrosoft Azure Data Explorer  Xexclude from comparisonRealm  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.A highly scalable full ACID SQL database with fast NoSQL data ingestion and GIS capabilitiesFully managed big data interactive analytics platformA DBMS built for use on mobile devices that’s a fast, easy to use alternative to SQLite and Core Data
Primary database modelRelational DBMSKey-value store
Relational DBMS
Relational DBMS infocolumn orientedDocument store
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
Score0.36
Rank#280  Overall
#40  Key-value stores
#129  Relational DBMS
Score3.80
Rank#81  Overall
#43  Relational DBMS
Score7.41
Rank#52  Overall
#8  Document stores
Websitewww.leanxcale.comazure.microsoft.com/­services/­data-explorerrealm.io
Technical documentationdocs.microsoft.com/­en-us/­azure/­data-explorerrealm.io/­docs
DeveloperDrizzle project, originally started by Brian AkerLeanXcaleMicrosoftRealm, acquired by MongoDB in May 2019
Initial release2008201520192014
Current release7.2.4, September 2012cloud service with continuous releases
License infoCommercial or Open SourceOpen Source infoGNU GPLcommercialcommercialOpen Source
Cloud-based only infoOnly available as a cloud servicenonoyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC++
Server operating systemsFreeBSD
Linux
OS X
hostedAndroid
Backend: server-less
iOS
Windows
Data schemeyesyesFixed 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-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 extensionsyes infothrough Apache DerbyKusto Query Language (KQL), SQL subsetno
APIs and other access methodsJDBCJDBC
Kafka Connector
ODBC
proprietary key/value interface
Spark Connector
Microsoft SQL Server communication protocol (MS-TDS)
RESTful HTTP API
Supported programming languagesC
C++
Java
PHP
C
Java
Scala
.Net
Go
Java
JavaScript (Node.js)
PowerShell
Python
R
.Net
Java infowith Android only
Objective-C
React Native
Swift
Server-side scripts infoStored proceduresnoYes, possible languages: KQL, Python, Rno inforuns within the applications so server-side scripts are unnecessary
Triggersno infohooks for callbacks inside the server can be used.yes infosee docs.microsoft.com/­en-us/­azure/­kusto/­management/­updatepolicyyes infoChange Listeners
Partitioning methods infoMethods for storing different data on different nodesShardingSharding infoImplicit feature of the cloud servicenone
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.none
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonoSpark connector (open source): github.com/­Azure/­azure-kusto-sparkno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyEventual Consistency
Immediate Consistency
Immediate Consistency
Foreign keys infoReferential integrityyesyesnono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACIDnoACID
Concurrency infoSupport for concurrent manipulation of datayesyesyes
Durability infoSupport for making data persistentyesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesnoyes infoIn-Memory realm
User concepts infoAccess controlPluggable authentication mechanisms infoe.g. LDAP, HTTPAzure Active Directory Authenticationyes

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More resources
DrizzleLeanXcaleMicrosoft Azure Data ExplorerRealm
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