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DBMS > Blueflood vs. Drizzle vs. Kinetica vs. Microsoft Azure Data Explorer

System Properties Comparison Blueflood vs. Drizzle vs. Kinetica vs. Microsoft Azure Data Explorer

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Editorial information provided by DB-Engines
NameBlueflood  Xexclude from comparisonDrizzle  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.
DescriptionScalable TimeSeries DBMS based on CassandraMySQL fork with a pluggable micro-kernel and with an emphasis of performance over compatibility.Fully vectorized database across both GPUs and CPUsFully managed big data interactive analytics platform
Primary database modelTime Series DBMSRelational 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
Score0.13
Rank#346  Overall
#33  Time Series DBMS
Score0.66
Rank#234  Overall
#107  Relational DBMS
Score3.80
Rank#81  Overall
#43  Relational DBMS
Websiteblueflood.iowww.kinetica.comazure.microsoft.com/­services/­data-explorer
Technical documentationgithub.com/­rax-maas/­blueflood/­wikidocs.kinetica.comdocs.microsoft.com/­en-us/­azure/­data-explorer
DeveloperRackspaceDrizzle project, originally started by Brian AkerKineticaMicrosoft
Initial release2013200820122019
Current release7.2.4, September 20127.1, August 2021cloud service with continuous releases
License infoCommercial or Open SourceOpen Source infoApache 2.0Open Source infoGNU GPLcommercialcommercial
Cloud-based only infoOnly available as a cloud servicenononoyes
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaC++C, C++
Server operating systemsLinux
OS X
FreeBSD
Linux
OS X
Linuxhosted
Data schemepredefined schemeyesyesFixed schema with schema-less datatypes (dynamic)
Typing infopredefined data types such as float or dateyesyesyesyes 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.nonoyes
Secondary indexesnoyesyesall fields are automatically indexed
SQL infoSupport of SQLnoyes infowith proprietary extensionsSQL-like DML and DDL statementsKusto Query Language (KQL), SQL subset
APIs and other access methodsHTTP RESTJDBCJDBC
ODBC
RESTful HTTP API
Microsoft SQL Server communication protocol (MS-TDS)
RESTful HTTP API
Supported programming languagesC
C++
Java
PHP
C++
Java
JavaScript (Node.js)
Python
.Net
Go
Java
JavaScript (Node.js)
PowerShell
Python
R
Server-side scripts infoStored proceduresnonouser defined functionsYes, possible languages: KQL, Python, R
Triggersnono infohooks for callbacks inside the server can be used.yes 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 nodesSharding infobased on CassandraShardingShardingSharding infoImplicit feature of the cloud service
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factor infobased on CassandraMulti-source replication
Source-replica replication
Source-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 methodsnononoSpark connector (open source): github.com/­Azure/­azure-kusto-spark
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual Consistency infobased on Cassandra
Immediate Consistency infobased on Cassandra
Immediate Consistency or Eventual Consistency depending on configurationEventual Consistency
Immediate Consistency
Foreign keys infoReferential integritynoyesyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDnono
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyes 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
BluefloodDrizzleKineticaMicrosoft Azure Data Explorer
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