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DBMS > Apache Druid vs. FeatureBase vs. HBase vs. Microsoft Azure Data Explorer

System Properties Comparison Apache Druid vs. FeatureBase vs. HBase vs. Microsoft Azure Data Explorer

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Editorial information provided by DB-Engines
NameApache Druid  Xexclude from comparisonFeatureBase  Xexclude from comparisonHBase  Xexclude from comparisonMicrosoft Azure Data Explorer  Xexclude from comparison
DescriptionOpen-source analytics data store designed for sub-second OLAP queries on high dimensionality and high cardinality dataReal-time database platform that powers real-time analytics and machine learning applications by simultaneously executing low-latency, high-throughput, and highly concurrent workloads.Wide-column store based on Apache Hadoop and on concepts of BigTableFully managed big data interactive analytics platform
Primary database modelRelational DBMS
Time Series DBMS
Relational DBMSWide column storeRelational 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
Score0.31
Rank#292  Overall
#135  Relational DBMS
Score27.97
Rank#26  Overall
#2  Wide column stores
Score3.80
Rank#81  Overall
#43  Relational DBMS
Websitedruid.apache.orgwww.featurebase.comhbase.apache.orgazure.microsoft.com/­services/­data-explorer
Technical documentationdruid.apache.org/­docs/­latest/­designdocs.featurebase.comhbase.apache.org/­book.htmldocs.microsoft.com/­en-us/­azure/­data-explorer
DeveloperApache Software Foundation and contributorsMolecula and Pilosa Open Source ContributorsApache Software Foundation infoApache top-level project, originally developed by PowersetMicrosoft
Initial release2012201720082019
Current release29.0.1, April 20242022, May 20222.3.4, January 2021cloud service with continuous releases
License infoCommercial or Open SourceOpen Source infoApache license v2commercialOpen Source infoApache version 2commercial
Cloud-based only infoOnly available as a cloud servicenononoyes
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaGoJava
Server operating systemsLinux
OS X
Unix
Linux
macOS
Linux
Unix
Windows infousing Cygwin
hosted
Data schemeyes infoschema-less columns are supportedyesschema-free, schema definition possibleFixed schema with schema-less datatypes (dynamic)
Typing infopredefined data types such as float or dateyesyesoptions to bring your own types, AVROyes 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.nononoyes
Secondary indexesyesnonoall fields are automatically indexed
SQL infoSupport of SQLSQL for queryingSQL queriesnoKusto Query Language (KQL), SQL subset
APIs and other access methodsJDBC
RESTful HTTP/JSON API
gRPC
JDBC
Kafka Connector
ODBC
Java API
RESTful HTTP API
Thrift
Microsoft SQL Server communication protocol (MS-TDS)
RESTful HTTP API
Supported programming languagesClojure
JavaScript
PHP
Python
R
Ruby
Scala
Java
Python
C
C#
C++
Groovy
Java
PHP
Python
Scala
.Net
Go
Java
JavaScript (Node.js)
PowerShell
Python
R
Server-side scripts infoStored proceduresnoyes infoCoprocessors in JavaYes, possible languages: KQL, Python, R
Triggersnonoyesyes infosee docs.microsoft.com/­en-us/­azure/­kusto/­management/­updatepolicy
Partitioning methods infoMethods for storing different data on different nodesSharding infomanual/auto, time-basedShardingShardingSharding infoImplicit feature of the cloud service
Replication methods infoMethods for redundantly storing data on multiple nodesyes, via HDFS, S3 or other storage enginesyesMulti-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 methodsnoyesSpark connector (open source): github.com/­Azure/­azure-kusto-spark
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate Consistency or Eventual ConsistencyEventual Consistency
Immediate Consistency
Foreign keys infoReferential integritynoyesnono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoyesSingle row ACID (across millions of columns)no
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyes, using Linux fsyncyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyesyesno
User concepts infoAccess controlRBAC using LDAP or Druid internals for users and groups for read/write by datasource and systemAccess Control Lists (ACL) for RBAC, integration with Apache Ranger for RBAC & ABACAzure Active Directory Authentication

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More resources
Apache DruidFeatureBaseHBaseMicrosoft Azure Data Explorer
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