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DBMS > Amazon Redshift vs. Apache Phoenix vs. Databricks vs. Hive

System Properties Comparison Amazon Redshift vs. Apache Phoenix vs. Databricks vs. Hive

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Editorial information provided by DB-Engines
NameAmazon Redshift  Xexclude from comparisonApache Phoenix  Xexclude from comparisonDatabricks  Xexclude from comparisonHive  Xexclude from comparison
DescriptionLarge scale data warehouse service for use with business intelligence toolsA 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.data warehouse software for querying and managing large distributed datasets, built on Hadoop
Primary database modelRelational DBMSRelational DBMSDocument store
Relational DBMS
Relational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score17.94
Rank#34  Overall
#21  Relational DBMS
Score1.97
Rank#126  Overall
#59  Relational DBMS
Score78.61
Rank#15  Overall
#2  Document stores
#10  Relational DBMS
Score61.17
Rank#18  Overall
#12  Relational DBMS
Websiteaws.amazon.com/­redshiftphoenix.apache.orgwww.databricks.comhive.apache.org
Technical documentationdocs.aws.amazon.com/­redshiftphoenix.apache.orgdocs.databricks.comcwiki.apache.org/­confluence/­display/­Hive/­Home
DeveloperAmazon (based on PostgreSQL)Apache Software FoundationDatabricksApache Software Foundation infoinitially developed by Facebook
Initial release2012201420132012
Current release5.0-HBase2, July 2018 and 4.15-HBase1, December 20193.1.3, April 2022
License infoCommercial or Open SourcecommercialOpen Source infoApache Version 2.0commercialOpen Source infoApache Version 2
Cloud-based only infoOnly available as a cloud serviceyesnoyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageCJavaJava
Server operating systemshostedLinux
Unix
Windows
hostedAll OS with a Java VM
Data schemeyesyes infolate-bound, schema-on-read capabilitiesFlexible Schema (defined schema, partial schema, schema free)yes
Typing infopredefined data types such as float or dateyesyesyes
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.nonoyes
Secondary indexesrestrictedyesyesyes
SQL infoSupport of SQLyes infodoes not fully support an SQL-standardyeswith Databricks SQLSQL-like DML and DDL statements
APIs and other access methodsJDBC
ODBC
JDBCJDBC
ODBC
RESTful HTTP API
JDBC
ODBC
Thrift
Supported programming languagesAll languages supporting JDBC/ODBCC
C#
C++
Go
Groovy
Java
PHP
Python
Scala
Python
R
Scala
C++
Java
PHP
Python
Server-side scripts infoStored proceduresuser defined functions infoin Pythonuser defined functionsuser defined functions and aggregatesyes infouser defined functions and integration of map-reduce
Triggersnonono
Partitioning methods infoMethods for storing different data on different nodesShardingShardingSharding
Replication methods infoMethods for redundantly storing data on multiple nodesyesMulti-source replication
Source-replica replication
yesselectable replication factor
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoHadoop integrationyes infoquery execution via MapReduce
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate Consistency or Eventual ConsistencyImmediate ConsistencyEventual Consistency
Foreign keys infoReferential integrityyes infoinformational only, not enforced by the systemnono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACIDACIDno
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesyesno
User concepts infoAccess controlfine grained access rights according to SQL-standardAccess Control Lists (using HBase ACL) for RBAC, integration with Apache Ranger for RBAC & ABAC, multi-tenancyAccess rights for users, groups and roles
More information provided by the system vendor
Amazon RedshiftApache PhoenixDatabricksHive
Specific characteristicsSupported database models : In addition to the Document store and Relational DBMS...
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More resources
Amazon RedshiftApache PhoenixDatabricksHive
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