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

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

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NameApache Druid  Xexclude from comparisonBadger  Xexclude from comparisonFeatureBase  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 dataAn embeddable, persistent, simple and fast Key-Value Store, written purely in Go.Real-time database platform that powers real-time analytics and machine learning applications by simultaneously executing low-latency, high-throughput, and highly concurrent workloads.Fully managed big data interactive analytics platform
Primary database modelRelational DBMS
Time Series DBMS
Key-value storeRelational DBMSRelational 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
Score2.85
Rank#96  Overall
#50  Relational DBMS
#6  Time Series DBMS
Score0.14
Rank#328  Overall
#48  Key-value stores
Score0.23
Rank#296  Overall
#134  Relational DBMS
Score3.28
Rank#83  Overall
#45  Relational DBMS
Websitedruid.apache.orggithub.com/­dgraph-io/­badgerwww.featurebase.comazure.microsoft.com/­services/­data-explorer
Technical documentationdruid.apache.org/­docs/­latest/­designgodoc.org/­github.com/­dgraph-io/­badgerdocs.featurebase.comdocs.microsoft.com/­en-us/­azure/­data-explorer
DeveloperApache Software Foundation and contributorsDGraph LabsMolecula and Pilosa Open Source ContributorsMicrosoft
Initial release2012201720172019
Current release30.0.0, June 20242022, May 2022cloud service with continuous releases
License infoCommercial or Open SourceOpen Source infoApache license v2Open Source infoApache 2.0commercialcommercial
Cloud-based only infoOnly available as a cloud servicenononoyes
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJavaGoGo
Server operating systemsLinux
OS X
Unix
BSD
Linux
OS X
Solaris
Windows
Linux
macOS
hosted
Data schemeyes infoschema-less columns are supportedschema-freeyesFixed schema with schema-less datatypes (dynamic)
Typing infopredefined data types such as float or dateyesnoyesyes 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 queryingnoSQL queriesKusto Query Language (KQL), SQL subset
APIs and other access methodsJDBC
RESTful HTTP/JSON API
gRPC
JDBC
Kafka Connector
ODBC
Microsoft SQL Server communication protocol (MS-TDS)
RESTful HTTP API
Supported programming languagesClojure
JavaScript
PHP
Python
R
Ruby
Scala
GoJava
Python
.Net
Go
Java
JavaScript (Node.js)
PowerShell
Python
R
Server-side scripts infoStored proceduresnonoYes, possible languages: KQL, Python, R
Triggersnononoyes infosee docs.microsoft.com/­en-us/­azure/­kusto/­management/­updatepolicy
Partitioning methods infoMethods for storing different data on different nodesSharding infomanual/auto, time-basednoneShardingSharding infoImplicit feature of the cloud service
Replication methods infoMethods for redundantly storing data on multiple nodesyes, via HDFS, S3 or other storage enginesnoneyesyes infoImplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonoSpark connector (open source): github.com/­Azure/­azure-kusto-spark
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencynoneEventual Consistency
Immediate Consistency
Foreign keys infoReferential integritynonoyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanonoyesno
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyesyes, using Linux fsyncyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.nonoyesno
User concepts infoAccess controlRBAC using LDAP or Druid internals for users and groups for read/write by datasource and systemnoAzure Active Directory Authentication

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More resources
Apache DruidBadgerFeatureBaseMicrosoft Azure Data Explorer
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