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DBMS > Apache Druid vs. eXtremeDB vs. FatDB vs. Microsoft Azure Data Explorer

System Properties Comparison Apache Druid vs. eXtremeDB vs. FatDB vs. Microsoft Azure Data Explorer

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Editorial information provided by DB-Engines
NameApache Druid  Xexclude from comparisoneXtremeDB  Xexclude from comparisonFatDB  Xexclude from comparisonMicrosoft Azure Data Explorer  Xexclude from comparison
FatDB/FatCloud has ceased operations as a company with February 2014. FatDB is discontinued and excluded from the ranking.
DescriptionOpen-source analytics data store designed for sub-second OLAP queries on high dimensionality and high cardinality dataNatively in-memory DBMS with options for persistency, high-availability and clusteringA .NET NoSQL DBMS that can integrate with and extend SQL Server.Fully managed big data interactive analytics platform
Primary database modelRelational DBMS
Time Series DBMS
Relational DBMS
Time Series DBMS
Document store
Key-value store
Relational 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
Score3.25
Rank#90  Overall
#47  Relational DBMS
#7  Time Series DBMS
Score0.80
Rank#214  Overall
#99  Relational DBMS
#18  Time Series DBMS
Score3.80
Rank#81  Overall
#43  Relational DBMS
Websitedruid.apache.orgwww.mcobject.comazure.microsoft.com/­services/­data-explorer
Technical documentationdruid.apache.org/­docs/­latest/­designwww.mcobject.com/­docs/­extremedb.htmdocs.microsoft.com/­en-us/­azure/­data-explorer
DeveloperApache Software Foundation and contributorsMcObjectFatCloudMicrosoft
Initial release2012200120122019
Current release29.0.1, April 20248.2, 2021cloud service with continuous releases
License infoCommercial or Open SourceOpen Source infoApache license v2commercialcommercialcommercial
Cloud-based only infoOnly available as a cloud servicenononoyes
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaC and C++C#
Server operating systemsLinux
OS X
Unix
AIX
HP-UX
Linux
macOS
Solaris
Windows
Windowshosted
Data schemeyes infoschema-less columns are supportedyesschema-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.nono infosupport of XML interfaces availableyes
Secondary indexesyesyesyesall fields are automatically indexed
SQL infoSupport of SQLSQL for queryingyes infowith the option: eXtremeSQLno infoVia inetgration in SQL ServerKusto Query Language (KQL), SQL subset
APIs and other access methodsJDBC
RESTful HTTP/JSON API
.NET Client API
JDBC
JNI
ODBC
Proprietary protocol
RESTful HTTP API
.NET Client API
LINQ
RESTful HTTP API
RPC
Windows WCF Bindings
Microsoft SQL Server communication protocol (MS-TDS)
RESTful HTTP API
Supported programming languagesClojure
JavaScript
PHP
Python
R
Ruby
Scala
.Net
C
C#
C++
Java
Lua
Python
Scala
C#.Net
Go
Java
JavaScript (Node.js)
PowerShell
Python
R
Server-side scripts infoStored proceduresnoyesyes infovia applicationsYes, possible languages: KQL, Python, R
Triggersnoyes infoby defining eventsyes infovia applicationsyes infosee docs.microsoft.com/­en-us/­azure/­kusto/­management/­updatepolicy
Partitioning methods infoMethods for storing different data on different nodesSharding infomanual/auto, time-basedhorizontal partitioning / shardingShardingSharding infoImplicit feature of the cloud service
Replication methods infoMethods for redundantly storing data on multiple nodesyes, via HDFS, S3 or other storage enginesActive Replication Fabric™ for IoT
Multi-source replication infoby means of eXtremeDB Cluster option
Source-replica replication infoby means of eXtremeDB High Availability option
selectable 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 methodsnonoyesSpark connector (open source): github.com/­Azure/­azure-kusto-spark
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyEventual 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 datayesyes infoOptimistic (MVCC) and pessimistic (locking) strategies availableyesyes
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.noyesno
User concepts infoAccess controlRBAC using LDAP or Druid internals for users and groups for read/write by datasource and systemno infoCan implement custom security layer via applicationsAzure Active Directory Authentication
More information provided by the system vendor
Apache DruideXtremeDBFatDBMicrosoft Azure Data Explorer
Specific characteristicseXtremeDB is an in-memory and/or persistent database system that offers an ultra-small...
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Competitive advantageseXtremeDB databases can be modeled relationally or as objects and can utilize SQL...
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Typical application scenariosIoT application across all markets: Industrial Control, Netcom, Telecom, Defense,...
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Key customersSchneider Electronics, F5 Networks, TNS, Boeing, Northrop Grumman, GoPro, ViaSat,...
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Market metricsWith hundreds of customers and over 30 million devices/applications using the product...
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Licensing and pricing modelsFor server use cases, there is a simple per-server license irrespective of the number...
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Apache DruideXtremeDBFatDBMicrosoft Azure Data Explorer
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