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DBMS > Databricks vs. Hawkular Metrics vs. Microsoft Azure SQL Database

System Properties Comparison Databricks vs. Hawkular Metrics vs. Microsoft Azure SQL Database

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Editorial information provided by DB-Engines
NameDatabricks  Xexclude from comparisonHawkular Metrics  Xexclude from comparisonMicrosoft Azure SQL Database infoformerly SQL Azure  Xexclude from comparison
DescriptionThe Databricks Lakehouse Platform combines elements of data lakes and data warehouses to provide a unified view onto structured and unstructured data. It is based on Apache Spark.Hawkular metrics is the metric storage of the Red Hat sponsored Hawkular monitoring system. It is based on Cassandra.Database as a Service offering with high compatibility to Microsoft SQL Server
Primary database modelDocument store
Relational DBMS
Time Series DBMSRelational DBMS
Secondary database modelsDocument store
Graph DBMS
Spatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score78.61
Rank#15  Overall
#2  Document stores
#10  Relational DBMS
Score0.00
Rank#379  Overall
#40  Time Series DBMS
Score77.99
Rank#16  Overall
#11  Relational DBMS
Websitewww.databricks.comwww.hawkular.orgazure.microsoft.com/­en-us/­products/­azure-sql/­database
Technical documentationdocs.databricks.comwww.hawkular.org/­hawkular-metrics/­docs/­user-guidedocs.microsoft.com/­en-us/­azure/­azure-sql
DeveloperDatabricksCommunity supported by Red HatMicrosoft
Initial release201320142010
Current releaseV12
License infoCommercial or Open SourcecommercialOpen Source infoApache 2.0commercial
Cloud-based only infoOnly available as a cloud serviceyesnoyes
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJavaC++
Server operating systemshostedLinux
OS X
Windows
hosted
Data schemeFlexible Schema (defined schema, partial schema, schema free)schema-freeyes
Typing infopredefined data types such as float or dateyesyes
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.yesnoyes
Secondary indexesyesnoyes
SQL infoSupport of SQLwith Databricks SQLnoyes
APIs and other access methodsJDBC
ODBC
RESTful HTTP API
HTTP RESTADO.NET
JDBC
ODBC
Supported programming languagesPython
R
Scala
Go
Java
Python
Ruby
.Net
C#
Java
JavaScript (Node.js)
PHP
Python
Ruby
Server-side scripts infoStored proceduresuser defined functions and aggregatesnoTransact SQL
Triggersyes infovia Hawkular Alertingyes
Partitioning methods infoMethods for storing different data on different nodesSharding infobased on Cassandra
Replication methods infoMethods for redundantly storing data on multiple nodesyesselectable replication factor infobased on Cassandrayes, with always 3 replicas available
MapReduce infoOffers an API for user-defined Map/Reduce methodsnono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyEventual Consistency infobased on Cassandra
Immediate Consistency infobased on Cassandra
Immediate Consistency
Foreign keys infoReferential integritynoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDnoACID
Concurrency infoSupport for concurrent manipulation of datayesyesyes
Durability infoSupport for making data persistentyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.nono
User concepts infoAccess controlnofine grained access rights according to SQL-standard
More information provided by the system vendor
DatabricksHawkular MetricsMicrosoft Azure SQL Database infoformerly SQL Azure
Specific characteristicsSupported database models : In addition to the Document store and Relational DBMS...
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DatabricksHawkular MetricsMicrosoft Azure SQL Database infoformerly SQL Azure
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