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DBMS > Databricks vs. Drizzle vs. Firebolt vs. Hawkular Metrics vs. HBase

System Properties Comparison Databricks vs. Drizzle vs. Firebolt vs. Hawkular Metrics vs. HBase

Editorial information provided by DB-Engines
NameDatabricks  Xexclude from comparisonDrizzle  Xexclude from comparisonFirebolt  Xexclude from comparisonHawkular Metrics  Xexclude from comparisonHBase  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.Highly scalable cloud data warehouse and analytics product infoForked from ClickhouseHawkular 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 BigTable
Primary database modelDocument store
Relational DBMS
Relational DBMSRelational DBMSTime 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
Score1.90
Rank#134  Overall
#62  Relational DBMS
Score0.00
Rank#379  Overall
#40  Time Series DBMS
Score30.50
Rank#26  Overall
#2  Wide column stores
Websitewww.databricks.comwww.firebolt.iowww.hawkular.orghbase.apache.org
Technical documentationdocs.databricks.comdocs.firebolt.iowww.hawkular.org/­hawkular-metrics/­docs/­user-guidehbase.apache.org/­book.html
DeveloperDatabricksDrizzle project, originally started by Brian AkerFirebolt Analytics Inc.Community supported by Red HatApache Software Foundation infoApache top-level project, originally developed by Powerset
Initial release20132008202020142008
Current release7.2.4, September 20122.3.4, January 2021
License infoCommercial or Open SourcecommercialOpen Source infoGNU GPLcommercialOpen Source infoApache 2.0Open Source infoApache version 2
Cloud-based only infoOnly available as a cloud serviceyesnoyesnono
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
hostedLinux
OS X
Windows
Linux
Unix
Windows infousing Cygwin
Data schemeFlexible Schema (defined schema, partial schema, schema free)yesyesschema-freeschema-free, schema definition possible
Typing infopredefined data types such as float or dateyesyesyesoptions to bring your own types, AVRO
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.yesnono
Secondary indexesyesyesyesnono
SQL infoSupport of SQLwith Databricks SQLyes infowith proprietary extensionsyesnono
APIs and other access methodsJDBC
ODBC
RESTful HTTP API
JDBC.Net
ODBC
RESTful HTTP API
HTTP RESTJava API
RESTful HTTP API
Thrift
Supported programming languagesPython
R
Scala
C
C++
Java
PHP
Go
JavaScript (Node.js)
Python
Go
Java
Python
Ruby
C
C#
C++
Groovy
Java
PHP
Python
Scala
Server-side scripts infoStored proceduresuser defined functions and aggregatesnononoyes infoCoprocessors in Java
Triggersno infohooks for callbacks inside the server can be used.noyes infovia Hawkular Alertingyes
Partitioning methods infoMethods for storing different data on different nodesShardingSharding infobased on CassandraSharding
Replication methods infoMethods for redundantly storing data on multiple nodesyesMulti-source replication
Source-replica replication
depending on storage layerselectable replication factor infobased on CassandraMulti-source replication
Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonoyes
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyEventual Consistency infobased on Cassandra
Immediate Consistency infobased on Cassandra
Immediate Consistency or Eventual Consistency
Foreign keys infoReferential integrityyesnono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACIDnoSingle row ACID (across millions of columns)
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.nonoyes
User concepts infoAccess controlPluggable authentication mechanisms infoe.g. LDAP, HTTPnoAccess Control Lists (ACL) for RBAC, integration with Apache Ranger for RBAC & ABAC
More information provided by the system vendor
DatabricksDrizzleFireboltHawkular MetricsHBase
Specific characteristicsSupported database models : In addition to the Document store and Relational DBMS...
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DatabricksDrizzleFireboltHawkular MetricsHBase
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