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DBMS > Apache Druid vs. Rockset vs. Spark SQL

System Properties Comparison Apache Druid vs. Rockset vs. Spark SQL

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Editorial information provided by DB-Engines
NameApache Druid  Xexclude from comparisonRockset  Xexclude from comparisonSpark SQL  Xexclude from comparison
DescriptionOpen-source analytics data store designed for sub-second OLAP queries on high dimensionality and high cardinality dataA scalable, reliable search and analytics service in the cloud, built on RocksDBSpark SQL is a component on top of 'Spark Core' for structured data processing
Primary database modelRelational DBMS
Time Series DBMS
Document storeRelational DBMS
Secondary database modelsRelational DBMS
Search engine
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
Score0.79
Rank#211  Overall
#35  Document stores
Score18.96
Rank#33  Overall
#20  Relational DBMS
Websitedruid.apache.orgrockset.comspark.apache.org/­sql
Technical documentationdruid.apache.org/­docs/­latest/­designdocs.rockset.comspark.apache.org/­docs/­latest/­sql-programming-guide.html
DeveloperApache Software Foundation and contributorsRocksetApache Software Foundation
Initial release201220192014
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 languageJavaC++Scala
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 dateyesdynamic typingyes
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.nono infoingestion from XML files supportedno
Secondary indexesyesall fields are automatically indexedno
SQL infoSupport of SQLSQL for queryingRead-only SQL queries, including JOINsSQL-like DML and DDL statements
APIs and other access methodsJDBC
RESTful HTTP/JSON API
HTTP RESTJDBC
ODBC
Supported programming languagesClojure
JavaScript
PHP
Python
R
Ruby
Scala
Go
Java
JavaScript (Node.js)
Python
Java
Python
R
Scala
Server-side scripts infoStored proceduresnonono
Triggersnonono
Partitioning methods infoMethods for storing different data on different nodesSharding infomanual/auto, time-basedAutomatic shardingyes, utilizing Spark Core
Replication methods infoMethods for redundantly storing data on multiple nodesyes, via HDFS, S3 or other storage enginesyesnone
MapReduce infoOffers an API for user-defined Map/Reduce methodsnono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyEventual Consistency
Foreign keys infoReferential integritynonono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanonono
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 systemAccess rights for users and organizations can be defined via Rockset consoleno

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More resources
Apache DruidRocksetSpark SQL
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