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DBMS > Badger vs. Drizzle vs. Heroic vs. Kinetica vs. Microsoft Azure Data Explorer

System Properties Comparison Badger vs. Drizzle vs. Heroic vs. Kinetica vs. Microsoft Azure Data Explorer

Editorial information provided by DB-Engines
NameBadger  Xexclude from comparisonDrizzle  Xexclude from comparisonHeroic  Xexclude from comparisonKinetica  Xexclude from comparisonMicrosoft Azure Data Explorer  Xexclude from comparison
Drizzle has published its last release in September 2012. The open-source project is discontinued and Drizzle is excluded from the DB-Engines ranking.
DescriptionAn embeddable, persistent, simple and fast Key-Value Store, written purely in Go.MySQL fork with a pluggable micro-kernel and with an emphasis of performance over compatibility.Time Series DBMS built at Spotify based on Cassandra or Google Cloud Bigtable, and ElasticSearchFully vectorized database across both GPUs and CPUsFully managed big data interactive analytics platform
Primary database modelKey-value storeRelational DBMSTime Series DBMSRelational DBMSRelational DBMS infocolumn oriented
Secondary database modelsSpatial DBMS
Time Series DBMS
Document 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
Score0.22
Rank#320  Overall
#47  Key-value stores
Score0.46
Rank#265  Overall
#22  Time Series DBMS
Score0.66
Rank#234  Overall
#107  Relational DBMS
Score3.80
Rank#81  Overall
#43  Relational DBMS
Websitegithub.com/­dgraph-io/­badgergithub.com/­spotify/­heroicwww.kinetica.comazure.microsoft.com/­services/­data-explorer
Technical documentationgodoc.org/­github.com/­dgraph-io/­badgerspotify.github.io/­heroicdocs.kinetica.comdocs.microsoft.com/­en-us/­azure/­data-explorer
DeveloperDGraph LabsDrizzle project, originally started by Brian AkerSpotifyKineticaMicrosoft
Initial release20172008201420122019
Current release7.2.4, September 20127.1, August 2021cloud service with continuous releases
License infoCommercial or Open SourceOpen Source infoApache 2.0Open Source infoGNU GPLOpen Source infoApache 2.0commercialcommercial
Cloud-based only infoOnly available as a cloud servicenonononoyes
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageGoC++JavaC, C++
Server operating systemsBSD
Linux
OS X
Solaris
Windows
FreeBSD
Linux
OS X
Linuxhosted
Data schemeschema-freeyesschema-freeyesFixed schema with schema-less datatypes (dynamic)
Typing infopredefined data types such as float or datenoyesyesyesyes 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 indexesnoyesyes infovia Elasticsearchyesall fields are automatically indexed
SQL infoSupport of SQLnoyes infowith proprietary extensionsnoSQL-like DML and DDL statementsKusto Query Language (KQL), SQL subset
APIs and other access methodsJDBCHQL (Heroic Query Language, a JSON-based language)
HTTP API
JDBC
ODBC
RESTful HTTP API
Microsoft SQL Server communication protocol (MS-TDS)
RESTful HTTP API
Supported programming languagesGoC
C++
Java
PHP
C++
Java
JavaScript (Node.js)
Python
.Net
Go
Java
JavaScript (Node.js)
PowerShell
Python
R
Server-side scripts infoStored proceduresnononouser defined functionsYes, possible languages: KQL, Python, R
Triggersnono infohooks for callbacks inside the server can be used.noyes infotriggers when inserted values for one or more columns fall within a specified rangeyes infosee docs.microsoft.com/­en-us/­azure/­kusto/­management/­updatepolicy
Partitioning methods infoMethods for storing different data on different nodesnoneShardingShardingShardingSharding infoImplicit feature of the cloud service
Replication methods infoMethods for redundantly storing data on multiple nodesnoneMulti-source replication
Source-replica replication
yesSource-replica replicationyes infoImplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonononoSpark connector (open source): github.com/­Azure/­azure-kusto-spark
Consistency concepts infoMethods to ensure consistency in a distributed systemnoneEventual Consistency
Immediate Consistency
Immediate Consistency or Eventual Consistency depending on configurationEventual Consistency
Immediate Consistency
Foreign keys infoReferential integritynoyesnoyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDnonono
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentyesyesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.nonoyes infoGPU vRAM or System RAMno
User concepts infoAccess controlnoPluggable authentication mechanisms infoe.g. LDAP, HTTPAccess rights for users and roles on table levelAzure Active Directory Authentication

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More resources
BadgerDrizzleHeroicKineticaMicrosoft Azure Data Explorer
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