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

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

Editorial information provided by DB-Engines
NameDatabricks  Xexclude from comparisonDrizzle  Xexclude from comparisonFauna infopreviously named FaunaDB  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.Fauna provides a web-native interface, with support for GraphQL and custom business logic that integrates seamlessly with the rest of the serverless ecosystem. The underlying globally distributed storage and compute platform is fast, consistent, and reliable, with a modern security infrastructure.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 BigTable
Primary database modelDocument store
Relational DBMS
Relational DBMSDocument store
Graph DBMS
Relational DBMS
Time Series 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
Score1.52
Rank#153  Overall
#26  Document stores
#14  Graph DBMS
#71  Relational DBMS
#13  Time Series DBMS
Score0.00
Rank#379  Overall
#40  Time Series DBMS
Score30.50
Rank#26  Overall
#2  Wide column stores
Websitewww.databricks.comfauna.comwww.hawkular.orghbase.apache.org
Technical documentationdocs.databricks.comdocs.fauna.comwww.hawkular.org/­hawkular-metrics/­docs/­user-guidehbase.apache.org/­book.html
DeveloperDatabricksDrizzle project, originally started by Brian AkerFauna, Inc.Community supported by Red HatApache Software Foundation infoApache top-level project, originally developed by Powerset
Initial release20132008201420142008
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++ScalaJavaJava
Server operating systemshostedFreeBSD
Linux
OS X
hostedLinux
OS X
Windows
Linux
Unix
Windows infousing Cygwin
Data schemeFlexible Schema (defined schema, partial schema, schema free)yesschema-freeschema-freeschema-free, schema definition possible
Typing infopredefined data types such as float or dateyesnoyesoptions 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.yesnonono
Secondary indexesyesyesyesnono
SQL infoSupport of SQLwith Databricks SQLyes infowith proprietary extensionsnonono
APIs and other access methodsJDBC
ODBC
RESTful HTTP API
JDBCRESTful HTTP APIHTTP RESTJava API
RESTful HTTP API
Thrift
Supported programming languagesPython
R
Scala
C
C++
Java
PHP
C#
Go
Java
JavaScript
Python
Ruby
Scala
Swift
Go
Java
Python
Ruby
C
C#
C++
Groovy
Java
PHP
Python
Scala
Server-side scripts infoStored proceduresuser defined functions and aggregatesnouser defined functionsnoyes 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 nodesShardinghorizontal partitioning infoconsistent hashingSharding infobased on CassandraSharding
Replication methods infoMethods for redundantly storing data on multiple nodesyesMulti-source replication
Source-replica replication
Multi-source replicationselectable replication factor infobased on CassandraMulti-source replication
Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnononoyes
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyEventual Consistency infobased on Cassandra
Immediate Consistency infobased on Cassandra
Immediate Consistency or Eventual Consistency
Foreign keys infoReferential integrityyesyesnono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACIDACIDnoSingle row ACID (across millions of columns)
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.nononoyes
User concepts infoAccess controlPluggable authentication mechanisms infoe.g. LDAP, HTTPIdentity management, authentication, and access controlnoAccess Control Lists (ACL) for RBAC, integration with Apache Ranger for RBAC & ABAC
More information provided by the system vendor
DatabricksDrizzleFauna infopreviously named FaunaDBHawkular MetricsHBase
Specific characteristicsSupported database models : In addition to the Document store and Relational DBMS...
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DatabricksDrizzleFauna infopreviously named FaunaDBHawkular MetricsHBase
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