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DBMS > Apache Phoenix vs. Databricks vs. FeatureBase

System Properties Comparison Apache Phoenix vs. Databricks vs. FeatureBase

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Editorial information provided by DB-Engines
NameApache Phoenix  Xexclude from comparisonDatabricks  Xexclude from comparisonFeatureBase  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.Real-time database platform that powers real-time analytics and machine learning applications by simultaneously executing low-latency, high-throughput, and highly concurrent workloads.
Primary database modelRelational DBMSDocument store
Relational DBMS
Relational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score2.06
Rank#123  Overall
#58  Relational DBMS
Score81.08
Rank#15  Overall
#2  Document stores
#10  Relational DBMS
Score0.31
Rank#292  Overall
#135  Relational DBMS
Websitephoenix.apache.orgwww.databricks.comwww.featurebase.com
Technical documentationphoenix.apache.orgdocs.databricks.comdocs.featurebase.com
DeveloperApache Software FoundationDatabricksMolecula and Pilosa Open Source Contributors
Initial release201420132017
Current release5.0-HBase2, July 2018 and 4.15-HBase1, December 20192022, May 2022
License infoCommercial or Open SourceOpen Source infoApache Version 2.0commercialcommercial
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
Unix
Windows
hostedLinux
macOS
Data schemeyes infolate-bound, schema-on-read capabilitiesFlexible 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 indexesyesyesno
SQL infoSupport of SQLyeswith Databricks SQLSQL queries
APIs and other access methodsJDBCJDBC
ODBC
RESTful HTTP API
gRPC
JDBC
Kafka Connector
ODBC
Supported programming languagesC
C#
C++
Go
Groovy
Java
PHP
Python
Scala
Python
R
Scala
Java
Python
Server-side scripts infoStored proceduresuser defined functionsuser defined functions and aggregates
Triggersnono
Partitioning methods infoMethods for storing different data on different nodesShardingSharding
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication
Source-replica replication
yesyes
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 Consistency
Foreign keys infoReferential integritynoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACIDyes
Concurrency infoSupport for concurrent manipulation of datayesyesyes
Durability infoSupport for making data persistentyesyesyes, using Linux fsync
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-tenancy
More information provided by the system vendor
Apache PhoenixDatabricksFeatureBase
Specific characteristicsSupported database models : In addition to the Document store and Relational DBMS...
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Apache PhoenixDatabricksFeatureBase
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