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

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

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Editorial information provided by DB-Engines
NameBlueflood  Xexclude from comparisonDrizzle  Xexclude from comparisonMicrosoft Azure Data Explorer  Xexclude from comparisonVictoriaMetrics  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 managed big data interactive analytics platformA fast, cost-effective and scalable Time Series DBMS and monitoring solution
Primary database modelTime Series DBMSRelational DBMSRelational DBMS infocolumn orientedTime Series DBMS
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
Score0.13
Rank#346  Overall
#33  Time Series DBMS
Score3.80
Rank#81  Overall
#43  Relational DBMS
Score1.23
Rank#172  Overall
#15  Time Series DBMS
Websiteblueflood.ioazure.microsoft.com/­services/­data-explorervictoriametrics.com
Technical documentationgithub.com/­rax-maas/­blueflood/­wikidocs.microsoft.com/­en-us/­azure/­data-explorerdocs.victoriametrics.com
github.com/­VictoriaMetrics/­VictoriaMetrics/­wiki
DeveloperRackspaceDrizzle project, originally started by Brian AkerMicrosoftVictoriaMetrics
Initial release2013200820192018
Current release7.2.4, September 2012cloud service with continuous releasesv1.91, May 2023
License infoCommercial or Open SourceOpen Source infoApache 2.0Open Source infoGNU GPLcommercialOpen Source infoApache Version 2.0
Cloud-based only infoOnly available as a cloud servicenonoyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJavaC++Go
Server operating systemsLinux
OS X
FreeBSD
Linux
OS X
hostedFreeBSD
Linux
macOS
OpenBSD
Data schemepredefined schemeyesFixed schema with schema-less datatypes (dynamic)
Typing infopredefined data types such as float or dateyesyesyes 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.noyesno
Secondary indexesnoyesall fields are automatically indexed
SQL infoSupport of SQLnoyes infowith proprietary extensionsKusto Query Language (KQL), SQL subsetno
APIs and other access methodsHTTP RESTJDBCMicrosoft SQL Server communication protocol (MS-TDS)
RESTful HTTP API
Graphite protocol
InfluxDB Line Protocol
OpenTSDB
Prometheus Query API
Prometheus Remote Read/Write
Supported programming languagesC
C++
Java
PHP
.Net
Go
Java
JavaScript (Node.js)
PowerShell
Python
R
Server-side scripts infoStored proceduresnonoYes, possible languages: KQL, Python, Rno
Triggersnono infohooks for callbacks inside the server can be used.yes infosee docs.microsoft.com/­en-us/­azure/­kusto/­management/­updatepolicyno
Partitioning methods infoMethods for storing different data on different nodesSharding infobased on CassandraShardingSharding 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
yes infoImplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.Synchronous replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonoSpark connector (open source): github.com/­Azure/­azure-kusto-sparkno
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual Consistency infobased on Cassandra
Immediate Consistency infobased on Cassandra
Eventual Consistency
Immediate Consistency
Eventual Consistency
Foreign keys infoReferential integritynoyesnono
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.nonono
User concepts infoAccess controlnoPluggable authentication mechanisms infoe.g. LDAP, HTTPAzure Active Directory Authentication

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More resources
BluefloodDrizzleMicrosoft Azure Data ExplorerVictoriaMetrics
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