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DBMS > Databricks vs. Hawkular Metrics vs. Hypertable

System Properties Comparison Databricks vs. Hawkular Metrics vs. Hypertable

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Editorial information provided by DB-Engines
NameDatabricks  Xexclude from comparisonHawkular Metrics  Xexclude from comparisonHypertable  Xexclude from comparison
Hypertable has stopped its further development with March 2016 and is removed 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.Hawkular metrics is the metric storage of the Red Hat sponsored Hawkular monitoring system. It is based on Cassandra.An open source BigTable implementation based on distributed file systems such as Hadoop
Primary database modelDocument store
Relational DBMS
Time Series DBMSWide column store
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
DeveloperDatabricksCommunity supported by Red HatHypertable Inc.
Initial release201320142009
Current release0.9.8.11, March 2016
License infoCommercial or Open SourcecommercialOpen Source infoApache 2.0Open Source infoGNU version 3. Commercial license available
Cloud-based only infoOnly available as a cloud serviceyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaC++
Server operating systemshostedLinux
OS X
Windows
Linux
OS X
Windows infoan inofficial Windows port is available
Data schemeFlexible Schema (defined schema, partial schema, schema free)schema-freeschema-free
Typing infopredefined data types such as float or dateyesno
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 indexesyesnorestricted infoonly exact value or prefix value scans
SQL infoSupport of SQLwith Databricks SQLnono
APIs and other access methodsJDBC
ODBC
RESTful HTTP API
HTTP RESTC++ API
Thrift
Supported programming languagesPython
R
Scala
Go
Java
Python
Ruby
C++
Java
Perl
PHP
Python
Ruby
Server-side scripts infoStored proceduresuser defined functions and aggregatesnono
Triggersyes infovia Hawkular Alertingno
Partitioning methods infoMethods for storing different data on different nodesSharding infobased on CassandraSharding
Replication methods infoMethods for redundantly storing data on multiple nodesyesselectable replication factor infobased on Cassandraselectable replication factor on file system level
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyes
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 integritynono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDnono
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 controlnono
More information provided by the system vendor
DatabricksHawkular MetricsHypertable
Specific characteristicsSupported database models : In addition to the Document store and Relational DBMS...
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DatabricksHawkular MetricsHypertable
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