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DBMS > Databricks vs. Drizzle vs. Hawkular Metrics vs. HBase vs. Microsoft Azure Data Explorer

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

Editorial information provided by DB-Engines
NameDatabricks  Xexclude from comparisonDrizzle  Xexclude from comparisonHawkular Metrics  Xexclude from comparisonHBase  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.
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.MySQL 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.Wide-column store based on Apache Hadoop and on concepts of BigTableFully managed big data interactive analytics platform
Primary database modelDocument store
Relational DBMS
Relational DBMSTime Series DBMSWide column storeRelational DBMS infocolumn oriented
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
Score78.61
Rank#15  Overall
#2  Document stores
#10  Relational DBMS
Score0.00
Rank#379  Overall
#40  Time Series DBMS
Score30.50
Rank#26  Overall
#2  Wide column stores
Score4.38
Rank#77  Overall
#41  Relational DBMS
Websitewww.databricks.comwww.hawkular.orghbase.apache.orgazure.microsoft.com/­services/­data-explorer
Technical documentationdocs.databricks.comwww.hawkular.org/­hawkular-metrics/­docs/­user-guidehbase.apache.org/­book.htmldocs.microsoft.com/­en-us/­azure/­data-explorer
DeveloperDatabricksDrizzle project, originally started by Brian AkerCommunity supported by Red HatApache Software Foundation infoApache top-level project, originally developed by PowersetMicrosoft
Initial release20132008201420082019
Current release7.2.4, September 20122.3.4, January 2021cloud service with continuous releases
License infoCommercial or Open SourcecommercialOpen Source infoGNU GPLOpen Source infoApache 2.0Open Source infoApache version 2commercial
Cloud-based only infoOnly available as a cloud serviceyesnononoyes
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageC++JavaJava
Server operating systemshostedFreeBSD
Linux
OS X
Linux
OS X
Windows
Linux
Unix
Windows infousing Cygwin
hosted
Data schemeFlexible Schema (defined schema, partial schema, schema free)yesschema-freeschema-free, schema definition possibleFixed schema with schema-less datatypes (dynamic)
Typing infopredefined data types such as float or dateyesyesoptions to bring your own types, AVROyes 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.yesnonoyes
Secondary indexesyesyesnonoall fields are automatically indexed
SQL infoSupport of SQLwith Databricks SQLyes infowith proprietary extensionsnonoKusto Query Language (KQL), SQL subset
APIs and other access methodsJDBC
ODBC
RESTful HTTP API
JDBCHTTP RESTJava API
RESTful HTTP API
Thrift
Microsoft SQL Server communication protocol (MS-TDS)
RESTful HTTP API
Supported programming languagesPython
R
Scala
C
C++
Java
PHP
Go
Java
Python
Ruby
C
C#
C++
Groovy
Java
PHP
Python
Scala
.Net
Go
Java
JavaScript (Node.js)
PowerShell
Python
R
Server-side scripts infoStored proceduresuser defined functions and aggregatesnonoyes infoCoprocessors in JavaYes, possible languages: KQL, Python, R
Triggersno infohooks for callbacks inside the server can be used.yes infovia Hawkular Alertingyesyes infosee docs.microsoft.com/­en-us/­azure/­kusto/­management/­updatepolicy
Partitioning methods infoMethods for storing different data on different nodesShardingSharding infobased on CassandraShardingSharding infoImplicit feature of the cloud service
Replication methods infoMethods for redundantly storing data on multiple nodesyesMulti-source replication
Source-replica replication
selectable 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.
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonoyesSpark connector (open source): github.com/­Azure/­azure-kusto-spark
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyEventual Consistency infobased on Cassandra
Immediate Consistency infobased on Cassandra
Immediate Consistency or Eventual ConsistencyEventual Consistency
Immediate Consistency
Foreign keys infoReferential integrityyesnonono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACIDnoSingle row ACID (across millions of columns)no
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.nonoyesno
User concepts infoAccess controlPluggable authentication mechanisms infoe.g. LDAP, HTTPnoAccess Control Lists (ACL) for RBAC, integration with Apache Ranger for RBAC & ABACAzure Active Directory Authentication
More information provided by the system vendor
DatabricksDrizzleHawkular MetricsHBaseMicrosoft Azure Data Explorer
Specific characteristicsSupported database models : In addition to the Document store and Relational DBMS...
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DatabricksDrizzleHawkular MetricsHBaseMicrosoft Azure Data Explorer
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