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DBMS > Bangdb vs. HBase vs. Heroic vs. Microsoft Azure Data Explorer

System Properties Comparison Bangdb vs. HBase vs. Heroic vs. Microsoft Azure Data Explorer

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Editorial information provided by DB-Engines
NameBangdb  Xexclude from comparisonHBase  Xexclude from comparisonHeroic  Xexclude from comparisonMicrosoft Azure Data Explorer  Xexclude from comparison
DescriptionConverged and high performance database for device data, events, time series, document and graphWide-column store based on Apache Hadoop and on concepts of BigTableTime Series DBMS built at Spotify based on Cassandra or Google Cloud Bigtable, and ElasticSearchFully managed big data interactive analytics platform
Primary database modelDocument store
Graph DBMS
Time Series DBMS
Wide column storeTime Series DBMSRelational DBMS infocolumn oriented
Secondary database modelsSpatial DBMSDocument 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
Score0.08
Rank#347  Overall
#47  Document stores
#34  Graph DBMS
#31  Time Series DBMS
Score30.50
Rank#26  Overall
#2  Wide column stores
Score0.51
Rank#255  Overall
#21  Time Series DBMS
Score4.38
Rank#77  Overall
#41  Relational DBMS
Websitebangdb.comhbase.apache.orggithub.com/­spotify/­heroicazure.microsoft.com/­services/­data-explorer
Technical documentationdocs.bangdb.comhbase.apache.org/­book.htmlspotify.github.io/­heroicdocs.microsoft.com/­en-us/­azure/­data-explorer
DeveloperSachin Sinha, BangDBApache Software Foundation infoApache top-level project, originally developed by PowersetSpotifyMicrosoft
Initial release2012200820142019
Current releaseBangDB 2.0, October 20212.3.4, January 2021cloud service with continuous releases
License infoCommercial or Open SourceOpen Source infoBSD 3Open Source infoApache version 2Open Source infoApache 2.0commercial
Cloud-based only infoOnly available as a cloud servicenononoyes
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC, C++JavaJava
Server operating systemsLinuxLinux
Unix
Windows infousing Cygwin
hosted
Data schemeschema-freeschema-free, schema definition possibleschema-freeFixed schema with schema-less datatypes (dynamic)
Typing infopredefined data types such as float or dateyes: string, long, double, int, geospatial, stream, eventsoptions to bring your own types, AVROyesyes 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 indexesyes infosecondary, composite, nested, reverse, geospatialnoyes infovia Elasticsearchall fields are automatically indexed
SQL infoSupport of SQLSQL like support with command line toolnonoKusto Query Language (KQL), SQL subset
APIs and other access methodsProprietary protocol
RESTful HTTP API
Java API
RESTful HTTP API
Thrift
HQL (Heroic Query Language, a JSON-based language)
HTTP API
Microsoft SQL Server communication protocol (MS-TDS)
RESTful HTTP API
Supported programming languagesC
C#
C++
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 JavanoYes, possible languages: KQL, Python, R
Triggersyes, Notifications (with Streaming only)yesnoyes infosee docs.microsoft.com/­en-us/­azure/­kusto/­management/­updatepolicy
Partitioning methods infoMethods for storing different data on different nodesSharding (enterprise version only). P2P based virtual network overlay with consistent hashing and chord algorithmShardingShardingSharding infoImplicit feature of the cloud service
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factor, Knob for CAP (enterprise version only)Multi-source replication
Source-replica replication
yesyes infoImplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyesnoSpark connector (open source): github.com/­Azure/­azure-kusto-spark
Consistency concepts infoMethods to ensure consistency in a distributed systemTunable consistency, set CAP knob accordinglyImmediate Consistency or Eventual ConsistencyEventual Consistency
Immediate Consistency
Eventual Consistency
Immediate Consistency
Foreign keys infoReferential integritynononono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDSingle row ACID (across millions of columns)nono
Concurrency infoSupport for concurrent manipulation of datayes, optimistic concurrency controlyesyesyes
Durability infoSupport for making data persistentyes, implements WAL (Write ahead log) as wellyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yes, run db with in-memory only modeyesnono
User concepts infoAccess controlyes (enterprise version only)Access Control Lists (ACL) for RBAC, integration with Apache Ranger for RBAC & ABACAzure Active Directory Authentication

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More resources
BangdbHBaseHeroicMicrosoft Azure Data Explorer
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