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DBMS > Databricks vs. Drizzle vs. Hawkular Metrics vs. HBase vs. IBM Db2 warehouse

System Properties Comparison Databricks vs. Drizzle vs. Hawkular Metrics vs. HBase vs. IBM Db2 warehouse

Editorial information provided by DB-Engines
NameDatabricks  Xexclude from comparisonDrizzle  Xexclude from comparisonHawkular Metrics  Xexclude from comparisonHBase  Xexclude from comparisonIBM Db2 warehouse infoformerly named IBM dashDB  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 BigTableCloud-based data warehousing service
Primary database modelDocument store
Relational DBMS
Relational DBMSTime Series DBMSWide column storeRelational 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
Score30.50
Rank#26  Overall
#2  Wide column stores
Score1.30
Rank#164  Overall
#75  Relational DBMS
Websitewww.databricks.comwww.hawkular.orghbase.apache.orgwww.ibm.com/­products/­db2/­warehouse
Technical documentationdocs.databricks.comwww.hawkular.org/­hawkular-metrics/­docs/­user-guidehbase.apache.org/­book.html
DeveloperDatabricksDrizzle project, originally started by Brian AkerCommunity supported by Red HatApache Software Foundation infoApache top-level project, originally developed by PowersetIBM
Initial release20132008201420082014
Current release7.2.4, September 20122.3.4, January 2021
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 possibleyes
Typing infopredefined data types such as float or dateyesyesoptions to bring your own types, AVROyes
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.yesnonono infoImport/export of XML data possible
Secondary indexesyesyesnonoyes
SQL infoSupport of SQLwith Databricks SQLyes infowith proprietary extensionsnonoyes
APIs and other access methodsJDBC
ODBC
RESTful HTTP API
JDBCHTTP RESTJava API
RESTful HTTP API
Thrift
.NET Client API
JDBC
ODBC
OLE DB
Supported programming languagesPython
R
Scala
C
C++
Java
PHP
Go
Java
Python
Ruby
C
C#
C++
Groovy
Java
PHP
Python
Scala
Java
JavaScript (Node.js)
Perl
PHP
Python
R
Ruby
Server-side scripts infoStored proceduresuser defined functions and aggregatesnonoyes infoCoprocessors in JavaPL/SQL, SQL PL
Triggersno infohooks for callbacks inside the server can be used.yes infovia Hawkular Alertingyesyes
Partitioning methods infoMethods for storing different data on different nodesShardingSharding infobased on CassandraShardingSharding
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
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonoyesno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyEventual Consistency infobased on Cassandra
Immediate Consistency infobased on Cassandra
Immediate Consistency or Eventual ConsistencyImmediate Consistency
Foreign keys infoReferential integrityyesnonoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACIDnoSingle row ACID (across millions of columns)ACID
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.nonoyesyes
User concepts infoAccess controlPluggable authentication mechanisms infoe.g. LDAP, HTTPnoAccess Control Lists (ACL) for RBAC, integration with Apache Ranger for RBAC & ABACfine grained access rights according to SQL-standard
More information provided by the system vendor
DatabricksDrizzleHawkular MetricsHBaseIBM Db2 warehouse infoformerly named IBM dashDB
Specific characteristicsSupported database models : In addition to the Document store and Relational DBMS...
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More resources
DatabricksDrizzleHawkular MetricsHBaseIBM Db2 warehouse infoformerly named IBM dashDB
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