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DBMS > Apache Druid vs. Atos Standard Common Repository vs. Microsoft Azure Data Explorer

System Properties Comparison Apache Druid vs. Atos Standard Common Repository vs. Microsoft Azure Data Explorer

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Editorial information provided by DB-Engines
NameApache Druid  Xexclude from comparisonAtos Standard Common Repository  Xexclude from comparisonMicrosoft Azure Data Explorer  Xexclude from comparison
This system has been discontinued and will be removed from the DB-Engines ranking.
DescriptionOpen-source analytics data store designed for sub-second OLAP queries on high dimensionality and high cardinality dataHighly scalable database system, designed for managing session and subscriber data in modern mobile communication networksFully managed big data interactive analytics platform
Primary database modelRelational 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
Score3.34
Rank#88  Overall
#48  Relational DBMS
#7  Time Series DBMS
Score4.38
Rank#77  Overall
#41  Relational DBMS
Websitedruid.apache.orgatos.net/en/convergence-creators/portfolio/standard-common-repositoryazure.microsoft.com/­services/­data-explorer
Technical documentationdruid.apache.org/­docs/­latest/­designdocs.microsoft.com/­en-us/­azure/­data-explorer
DeveloperApache Software Foundation and contributorsAtos Convergence CreatorsMicrosoft
Initial release201220162019
Current release29.0.1, April 20241703cloud service with continuous releases
License infoCommercial or Open SourceOpen Source infoApache license v2commercialcommercial
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 languageJavaJava
Server operating systemsLinux
OS X
Unix
Linuxhosted
Data schemeyes infoschema-less columns are supportedSchema and schema-less with LDAP viewsFixed schema with schema-less datatypes (dynamic)
Typing infopredefined data types such as float or dateyesoptionalyes 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.noyesyes
Secondary indexesyesyesall fields are automatically indexed
SQL infoSupport of SQLSQL for queryingnoKusto Query Language (KQL), SQL subset
APIs and other access methodsJDBC
RESTful HTTP/JSON API
LDAPMicrosoft SQL Server communication protocol (MS-TDS)
RESTful HTTP API
Supported programming languagesClojure
JavaScript
PHP
Python
R
Ruby
Scala
All languages with LDAP bindings.Net
Go
Java
JavaScript (Node.js)
PowerShell
Python
R
Server-side scripts infoStored proceduresnonoYes, 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 nodesSharding infomanual/auto, time-basedSharding infocell divisionSharding infoImplicit feature of the cloud service
Replication methods infoMethods for redundantly storing data on multiple nodesyes, via HDFS, S3 or other storage enginesyesyes 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-spark
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate Consistency or Eventual Consistency depending on configurationEventual Consistency
Immediate Consistency
Foreign keys infoReferential integritynonono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoAtomic execution of specific operationsno
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.noyesno
User concepts infoAccess controlRBAC using LDAP or Druid internals for users and groups for read/write by datasource and systemLDAP bind authenticationAzure Active Directory Authentication

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More resources
Apache DruidAtos Standard Common RepositoryMicrosoft Azure Data Explorer
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