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DBMS > Databricks vs. Drizzle vs. Firebase Realtime Database vs. Spark SQL

System Properties Comparison Databricks vs. Drizzle vs. Firebase Realtime Database vs. Spark SQL

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Editorial information provided by DB-Engines
NameDatabricks  Xexclude from comparisonDrizzle  Xexclude from comparisonFirebase Realtime Database  Xexclude from comparisonSpark SQL  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.Cloud-hosted realtime document store. iOS, Android, and JavaScript clients share one Realtime Database instance and automatically receive updates with the newest data.Spark SQL is a component on top of 'Spark Core' for structured data processing
Primary database modelDocument store
Relational DBMS
Relational DBMSDocument 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
Score14.29
Rank#39  Overall
#6  Document stores
Score18.96
Rank#33  Overall
#20  Relational DBMS
Websitewww.databricks.comfirebase.google.com/­products/­realtime-databasespark.apache.org/­sql
Technical documentationdocs.databricks.comfirebase.google.com/­docs/­databasespark.apache.org/­docs/­latest/­sql-programming-guide.html
DeveloperDatabricksDrizzle project, originally started by Brian AkerGoogle infoacquired by Google 2014Apache Software Foundation
Initial release2013200820122014
Current release7.2.4, September 20123.5.0 ( 2.13), September 2023
License infoCommercial or Open SourcecommercialOpen Source infoGNU GPLcommercialOpen Source infoApache 2.0
Cloud-based only infoOnly available as a cloud serviceyesnoyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC++Scala
Server operating systemshostedFreeBSD
Linux
OS X
hostedLinux
OS X
Windows
Data schemeFlexible Schema (defined schema, partial schema, schema free)yesschema-freeyes
Typing infopredefined data types such as float or dateyesyesyes
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 indexesyesyesyesno
SQL infoSupport of SQLwith Databricks SQLyes infowith proprietary extensionsnoSQL-like DML and DDL statements
APIs and other access methodsJDBC
ODBC
RESTful HTTP API
JDBCAndroid
iOS
JavaScript API
RESTful HTTP API
JDBC
ODBC
Supported programming languagesPython
R
Scala
C
C++
Java
PHP
Java
JavaScript
Objective-C
Java
Python
R
Scala
Server-side scripts infoStored proceduresuser defined functions and aggregatesnolimited functionality with using 'rules'no
Triggersno infohooks for callbacks inside the server can be used.Callbacks are triggered when data changesno
Partitioning methods infoMethods for storing different data on different nodesShardingyes, utilizing Spark Core
Replication methods infoMethods for redundantly storing data on multiple nodesyesMulti-source replication
Source-replica replication
none
MapReduce infoOffers an API for user-defined Map/Reduce methodsnono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyEventual Consistency infoif the client is offline
Immediate Consistency infoif the client is online
Foreign keys infoReferential integrityyesnono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACIDyesno
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.nono
User concepts infoAccess controlPluggable authentication mechanisms infoe.g. LDAP, HTTPyes, based on authentication and database rulesno
More information provided by the system vendor
DatabricksDrizzleFirebase Realtime DatabaseSpark SQL
Specific characteristicsSupported database models : In addition to the Document store and Relational DBMS...
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More resources
DatabricksDrizzleFirebase Realtime DatabaseSpark SQL
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