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DBMS > Apache Druid vs. Firebase Realtime Database vs. Spark SQL

System Properties Comparison Apache Druid vs. Firebase Realtime Database vs. Spark SQL

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Editorial information provided by DB-Engines
NameApache Druid  Xexclude from comparisonFirebase Realtime Database  Xexclude from comparisonSpark SQL  Xexclude from comparison
DescriptionOpen-source analytics data store designed for sub-second OLAP queries on high dimensionality and high cardinality dataCloud-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 modelRelational DBMS
Time Series DBMS
Document storeRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score3.34
Rank#88  Overall
#48  Relational DBMS
#7  Time Series DBMS
Score14.29
Rank#39  Overall
#6  Document stores
Score18.96
Rank#33  Overall
#20  Relational DBMS
Websitedruid.apache.orgfirebase.google.com/­products/­realtime-databasespark.apache.org/­sql
Technical documentationdruid.apache.org/­docs/­latest/­designfirebase.google.com/­docs/­databasespark.apache.org/­docs/­latest/­sql-programming-guide.html
DeveloperApache Software Foundation and contributorsGoogle infoacquired by Google 2014Apache Software Foundation
Initial release201220122014
Current release29.0.1, April 20243.5.0 ( 2.13), September 2023
License infoCommercial or Open SourceOpen Source infoApache license v2commercialOpen Source infoApache 2.0
Cloud-based only infoOnly available as a cloud servicenoyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaScala
Server operating systemsLinux
OS X
Unix
hostedLinux
OS X
Windows
Data schemeyes infoschema-less columns are supportedschema-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.nonono
Secondary indexesyesyesno
SQL infoSupport of SQLSQL for queryingnoSQL-like DML and DDL statements
APIs and other access methodsJDBC
RESTful HTTP/JSON API
Android
iOS
JavaScript API
RESTful HTTP API
JDBC
ODBC
Supported programming languagesClojure
JavaScript
PHP
Python
R
Ruby
Scala
Java
JavaScript
Objective-C
Java
Python
R
Scala
Server-side scripts infoStored proceduresnolimited functionality with using 'rules'no
TriggersnoCallbacks are triggered when data changesno
Partitioning methods infoMethods for storing different data on different nodesSharding infomanual/auto, time-basedyes, utilizing Spark Core
Replication methods infoMethods for redundantly storing data on multiple nodesyes, via HDFS, S3 or other storage enginesnone
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 integritynonono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoyesno
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 controlRBAC using LDAP or Druid internals for users and groups for read/write by datasource and systemyes, based on authentication and database rulesno

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More resources
Apache DruidFirebase Realtime DatabaseSpark SQL
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