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DBMS > Databricks vs. Drizzle vs. Hawkular Metrics

System Properties Comparison Databricks vs. Drizzle vs. Hawkular Metrics

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Editorial information provided by DB-Engines
NameDatabricks  Xexclude from comparisonDrizzle  Xexclude from comparisonHawkular Metrics  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.
Primary database modelDocument store
Relational DBMS
Relational DBMSTime Series 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
Websitewww.databricks.comwww.hawkular.org
Technical documentationdocs.databricks.comwww.hawkular.org/­hawkular-metrics/­docs/­user-guide
DeveloperDatabricksDrizzle project, originally started by Brian AkerCommunity supported by Red Hat
Initial release201320082014
Current release7.2.4, September 2012
License infoCommercial or Open SourcecommercialOpen Source infoGNU GPLOpen Source infoApache 2.0
Cloud-based only infoOnly available as a cloud serviceyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageC++Java
Server operating systemshostedFreeBSD
Linux
OS X
Linux
OS X
Windows
Data schemeFlexible Schema (defined schema, partial schema, schema free)yesschema-free
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.yesno
Secondary indexesyesyesno
SQL infoSupport of SQLwith Databricks SQLyes infowith proprietary extensionsno
APIs and other access methodsJDBC
ODBC
RESTful HTTP API
JDBCHTTP REST
Supported programming languagesPython
R
Scala
C
C++
Java
PHP
Go
Java
Python
Ruby
Server-side scripts infoStored proceduresuser defined functions and aggregatesnono
Triggersno infohooks for callbacks inside the server can be used.yes infovia Hawkular Alerting
Partitioning methods infoMethods for storing different data on different nodesShardingSharding infobased on Cassandra
Replication methods infoMethods for redundantly storing data on multiple nodesyesMulti-source replication
Source-replica replication
selectable replication factor infobased on Cassandra
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
Foreign keys infoReferential integrityyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACIDno
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 controlPluggable authentication mechanisms infoe.g. LDAP, HTTPno
More information provided by the system vendor
DatabricksDrizzleHawkular Metrics
Specific characteristicsSupported database models : In addition to the Document store and Relational DBMS...
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DatabricksDrizzleHawkular Metrics
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