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DBMS > Apache Druid vs. Databricks vs. DolphinDB

System Properties Comparison Apache Druid vs. Databricks vs. DolphinDB

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Editorial information provided by DB-Engines
NameApache Druid  Xexclude from comparisonDatabricks  Xexclude from comparisonDolphinDB  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.DolphinDB is a high performance Time Series DBMS. It is integrated with an easy-to-use fully featured programming language and a high-volume high-velocity streaming analytics system. It offers operational simplicity, scalability, fault tolerance, and concurrency.
Primary database modelRelational DBMS
Time Series DBMS
Document store
Relational DBMS
Time Series DBMS
Secondary database modelsRelational 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
Score78.61
Rank#15  Overall
#2  Document stores
#10  Relational DBMS
Score4.13
Rank#80  Overall
#6  Time Series DBMS
Websitedruid.apache.orgwww.databricks.comwww.dolphindb.com
Technical documentationdruid.apache.org/­docs/­latest/­designdocs.databricks.comdocs.dolphindb.cn/­en/­help200/­index.html
DeveloperApache Software Foundation and contributorsDatabricksDolphinDB, Inc
Initial release201220132018
Current release29.0.1, April 2024v2.00.4, January 2022
License infoCommercial or Open SourceOpen Source infoApache license v2commercialcommercial infofree community version available
Cloud-based only infoOnly available as a cloud servicenoyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaC++
Server operating systemsLinux
OS X
Unix
hostedLinux
Windows
Data schemeyes infoschema-less columns are supportedFlexible Schema (defined schema, partial schema, schema free)yes
Typing infopredefined data types such as float or dateyesyes
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
Secondary indexesyesyesyes
SQL infoSupport of SQLSQL for queryingwith Databricks SQLSQL-like query language
APIs and other access methodsJDBC
RESTful HTTP/JSON API
JDBC
ODBC
RESTful HTTP API
JDBC
JSON over HTTP
Kafka
MQTT (Message Queue Telemetry Transport)
ODBC
OPC DA
OPC UA
RabbitMQ
WebSocket
Supported programming languagesClojure
JavaScript
PHP
Python
R
Ruby
Scala
Python
R
Scala
C#
C++
Go
Java
JavaScript
MatLab
Python
R
Rust
Server-side scripts infoStored proceduresnouser defined functions and aggregatesyes
Triggersnono
Partitioning methods infoMethods for storing different data on different nodesSharding infomanual/auto, time-basedhorizontal partitioning
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 methodsnoyes
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDyes
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.nonoyes
User concepts infoAccess controlRBAC using LDAP or Druid internals for users and groups for read/write by datasource and systemAdministrators, Users, Groups
More information provided by the system vendor
Apache DruidDatabricksDolphinDB
Specific characteristicsSupported database models : In addition to the Document store and Relational DBMS...
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More resources
Apache DruidDatabricksDolphinDB
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