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DBMS > Drizzle vs. Hawkular Metrics vs. Microsoft Azure Data Explorer vs. SiteWhere

System Properties Comparison Drizzle vs. Hawkular Metrics vs. Microsoft Azure Data Explorer vs. SiteWhere

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Editorial information provided by DB-Engines
NameDrizzle  Xexclude from comparisonHawkular Metrics  Xexclude from comparisonMicrosoft Azure Data Explorer  Xexclude from comparisonSiteWhere  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.
DescriptionMySQL fork with a pluggable micro-kernel and with an emphasis of performance over compatibility.Hawkular metrics is the metric storage of the Red Hat sponsored Hawkular monitoring system. It is based on Cassandra.Fully managed big data interactive analytics platformM2M integration platform for persisting/querying time series data
Primary database modelRelational DBMSTime Series 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
Score0.08
Rank#366  Overall
#39  Time Series DBMS
Score3.80
Rank#81  Overall
#43  Relational DBMS
Score0.06
Rank#383  Overall
#43  Time Series DBMS
Websitewww.hawkular.orgazure.microsoft.com/­services/­data-explorergithub.com/­sitewhere/­sitewhere
Technical documentationwww.hawkular.org/­hawkular-metrics/­docs/­user-guidedocs.microsoft.com/­en-us/­azure/­data-explorersitewhere1.sitewhere.io/­index.html
DeveloperDrizzle project, originally started by Brian AkerCommunity supported by Red HatMicrosoftSiteWhere
Initial release2008201420192010
Current release7.2.4, September 2012cloud service with continuous releases
License infoCommercial or Open SourceOpen Source infoGNU GPLOpen Source infoApache 2.0commercialOpen Source infoCommon Public Attribution License Version 1.0
Cloud-based only infoOnly available as a cloud servicenonoyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC++JavaJava
Server operating systemsFreeBSD
Linux
OS X
Linux
OS X
Windows
hostedLinux
OS X
Windows
Data schemeyesschema-freeFixed schema with schema-less datatypes (dynamic)predefined scheme
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-typesyes
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 indexesyesnoall fields are automatically indexedno
SQL infoSupport of SQLyes infowith proprietary extensionsnoKusto Query Language (KQL), SQL subsetno
APIs and other access methodsJDBCHTTP RESTMicrosoft SQL Server communication protocol (MS-TDS)
RESTful HTTP API
HTTP REST
Supported programming languagesC
C++
Java
PHP
Go
Java
Python
Ruby
.Net
Go
Java
JavaScript (Node.js)
PowerShell
Python
R
Server-side scripts infoStored proceduresnonoYes, possible languages: KQL, Python, R
Triggersno infohooks for callbacks inside the server can be used.yes infovia Hawkular Alertingyes infosee docs.microsoft.com/­en-us/­azure/­kusto/­management/­updatepolicy
Partitioning methods infoMethods for storing different data on different nodesShardingSharding infobased on CassandraSharding infoImplicit feature of the cloud serviceSharding infobased on HBase
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication
Source-replica replication
selectable replication factor infobased on Cassandrayes infoImplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.selectable replication factor infobased on HBase
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
Immediate Consistency
Foreign keys infoReferential integrityyesnonono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDnonono
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 controlPluggable authentication mechanisms infoe.g. LDAP, HTTPnoAzure Active Directory AuthenticationUsers with fine-grained authorization concept

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More resources
DrizzleHawkular MetricsMicrosoft Azure Data ExplorerSiteWhere
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