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DBMS > Apache Druid vs. Databricks vs. Rockset

System Properties Comparison Apache Druid vs. Databricks vs. Rockset

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Editorial information provided by DB-Engines
NameApache Druid  Xexclude from comparisonDatabricks  Xexclude from comparisonRockset  Xexclude from comparison
DescriptionOpen-source analytics data store designed for sub-second OLAP queries on high dimensionality and high cardinality dataThe 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.A scalable, reliable search and analytics service in the cloud, built on RocksDB
Primary database modelRelational DBMS
Time Series DBMS
Document store
Relational DBMS
Document store
Secondary database modelsRelational DBMS
Search engine
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score3.18
Rank#84  Overall
#45  Relational DBMS
#7  Time Series DBMS
Score102.66
Rank#12  Overall
#2  Document stores
#8  Relational DBMS
Score0.88
Rank#200  Overall
#34  Document stores
Websitedruid.apache.orgwww.databricks.comrockset.com
Technical documentationdruid.apache.org/­docs/­latest/­designdocs.databricks.comdocs.rockset.com
DeveloperApache Software Foundation and contributorsDatabricksRockset
Initial release201220132019
Current release30.0.0, June 2024
License infoCommercial or Open SourceOpen Source infoApache license v2commercialcommercial
Cloud-based only infoOnly available as a cloud servicenoyesyes
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaC++
Server operating systemsLinux
OS X
Unix
hostedhosted
Data schemeyes infoschema-less columns are supportedFlexible Schema (defined schema, partial schema, schema free)schema-free
Typing infopredefined data types such as float or dateyesdynamic typing
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.noyesno infoingestion from XML files supported
Secondary indexesyesyesall fields are automatically indexed
SQL infoSupport of SQLSQL for queryingwith Databricks SQLRead-only SQL queries, including JOINs
APIs and other access methodsJDBC
RESTful HTTP/JSON API
JDBC
ODBC
RESTful HTTP API
HTTP REST
Supported programming languagesClojure
JavaScript
PHP
Python
R
Ruby
Scala
Python
R
Scala
Go
Java
JavaScript (Node.js)
Python
Server-side scripts infoStored proceduresnouser defined functions and aggregatesno
Triggersnono
Partitioning methods infoMethods for storing different data on different nodesSharding infomanual/auto, time-basedAutomatic sharding
Replication methods infoMethods for redundantly storing data on multiple nodesyes, via HDFS, S3 or other storage enginesyesyes
MapReduce infoOffers an API for user-defined Map/Reduce methodsnono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyEventual Consistency
Foreign keys infoReferential integritynono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDno
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 console

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More resources
Apache DruidDatabricksRockset
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