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DBMS > Apache Druid vs. Databricks vs. openGemini

System Properties Comparison Apache Druid vs. Databricks vs. openGemini

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Editorial information provided by DB-Engines
NameApache Druid  Xexclude from comparisonDatabricks  Xexclude from comparisonopenGemini  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.An open source distributed Time Series DBMS with high concurrency, high performance, and high scalability
Primary database modelRelational DBMS
Time Series DBMS
Document store
Relational DBMS
Time Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score2.85
Rank#96  Overall
#50  Relational DBMS
#6  Time Series DBMS
Score84.24
Rank#14  Overall
#2  Document stores
#9  Relational DBMS
Score0.00
Rank#385  Overall
#40  Time Series DBMS
Websitedruid.apache.orgwww.databricks.comwww.opengemini.org
github.com/­openGemini
Technical documentationdruid.apache.org/­docs/­latest/­designdocs.databricks.comdocs.opengemini.org/­guide
DeveloperApache Software Foundation and contributorsDatabricksHuawei and openGemini community
Initial release201220132022
Current release30.0.0, June 20241.1, July 2023
License infoCommercial or Open SourceOpen Source infoApache license v2commercialOpen Source infoApache Version 2.0
Cloud-based only infoOnly available as a cloud servicenoyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaGo
Server operating systemsLinux
OS X
Unix
hostedLinux
Windows
Data schemeyes infoschema-less columns are supportedFlexible Schema (defined schema, partial schema, schema free)schema-free
Typing infopredefined data types such as float or dateyesInteger, Float, Boolean, String
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
HTTP REST
Supported programming languagesClojure
JavaScript
PHP
Python
R
Ruby
Scala
Python
R
Scala
C
C++
Go
Java
JavaScript (Node.js)
Python
Rust
Server-side scripts infoStored proceduresnouser defined functions and aggregatesno
Triggersnono
Partitioning methods infoMethods for storing different data on different nodesSharding infomanual/auto, time-basedSharding
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 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.nonoyes
User concepts infoAccess controlRBAC using LDAP or Druid internals for users and groups for read/write by datasource and systemAdministrators and common users accounts
More information provided by the system vendor
Apache DruidDatabricksopenGemini
Specific characteristicsSupported database models : In addition to the Document store and Relational DBMS...
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More resources
Apache DruidDatabricksopenGemini
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