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DBMS > Apache Phoenix vs. Databricks vs. OpenMLDB

System Properties Comparison Apache Phoenix vs. Databricks vs. OpenMLDB

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Editorial information provided by DB-Engines
NameApache Phoenix  Xexclude from comparisonDatabricks  Xexclude from comparisonOpenMLDB  Xexclude from comparison
DescriptionA scale-out RDBMS with evolutionary schema built on Apache HBaseThe 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 machine learning database that provides a feature platform for training and inference
Primary database modelRelational DBMSDocument store
Relational DBMS
Time Series DBMS
Secondary database modelsRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.90
Rank#125  Overall
#59  Relational DBMS
Score84.24
Rank#14  Overall
#2  Document stores
#9  Relational DBMS
Score0.11
Rank#339  Overall
#30  Time Series DBMS
Websitephoenix.apache.orgwww.databricks.comopenmldb.ai
Technical documentationphoenix.apache.orgdocs.databricks.comopenmldb.ai/­docs/­zh/­main
DeveloperApache Software FoundationDatabricks4 Paradigm Inc.
Initial release201420132020
Current release5.0-HBase2, July 2018 and 4.15-HBase1, December 20192024-2 February 2024
License infoCommercial or Open SourceOpen Source infoApache Version 2.0commercialOpen Source
Cloud-based only infoOnly available as a cloud servicenoyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaC++, Java, Scala
Server operating systemsLinux
Unix
Windows
hostedLinux
Data schemeyes infolate-bound, schema-on-read capabilitiesFlexible Schema (defined schema, partial schema, schema free)Fixed schema
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 SQLyeswith Databricks SQLyes
APIs and other access methodsJDBCJDBC
ODBC
RESTful HTTP API
JDBC
SQLAlchemy
Supported programming languagesC
C#
C++
Go
Groovy
Java
PHP
Python
Scala
Python
R
Scala
C++
Go
Java
Python
Scala
Server-side scripts infoStored proceduresuser defined functionsuser defined functions and aggregatesno
Triggersnono
Partitioning methods infoMethods for storing different data on different nodesShardinghorizontal partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication
Source-replica replication
yesSource-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsHadoop integration
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate Consistency or Eventual ConsistencyImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACIDno
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.yesnoyes
User concepts infoAccess controlAccess Control Lists (using HBase ACL) for RBAC, integration with Apache Ranger for RBAC & ABAC, multi-tenancyfine grained access rights according to SQL-standard
More information provided by the system vendor
Apache PhoenixDatabricksOpenMLDB
Specific characteristicsSupported database models : In addition to the Document store and Relational DBMS...
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Apache PhoenixDatabricksOpenMLDB
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