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DBMS > Amazon Redshift vs. Databricks vs. Hive vs. Splice Machine

System Properties Comparison Amazon Redshift vs. Databricks vs. Hive vs. Splice Machine

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Editorial information provided by DB-Engines
NameAmazon Redshift  Xexclude from comparisonDatabricks  Xexclude from comparisonHive  Xexclude from comparisonSplice Machine  Xexclude from comparison
DescriptionLarge scale data warehouse service for use with business intelligence toolsThe 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 HadoopOpen-Source SQL RDBMS for Operational and Analytical use cases with native Machine Learning, powered by Hadoop and Spark
Primary database modelRelational DBMSDocument store
Relational DBMS
Relational DBMSRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score16.88
Rank#35  Overall
#22  Relational DBMS
Score81.08
Rank#15  Overall
#2  Document stores
#10  Relational DBMS
Score59.76
Rank#18  Overall
#12  Relational DBMS
Score0.54
Rank#252  Overall
#115  Relational DBMS
Websiteaws.amazon.com/­redshiftwww.databricks.comhive.apache.orgsplicemachine.com
Technical documentationdocs.aws.amazon.com/­redshiftdocs.databricks.comcwiki.apache.org/­confluence/­display/­Hive/­Homesplicemachine.com/­how-it-works
DeveloperAmazon (based on PostgreSQL)DatabricksApache Software Foundation infoinitially developed by FacebookSplice Machine
Initial release2012201320122014
Current release3.1.3, April 20223.1, March 2021
License infoCommercial or Open SourcecommercialcommercialOpen Source infoApache Version 2Open Source infoAGPL 3.0, commercial license available
Cloud-based only infoOnly available as a cloud serviceyesyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageCJavaJava
Server operating systemshostedhostedAll OS with a Java VMLinux
OS X
Solaris
Windows
Data schemeyesFlexible Schema (defined schema, partial schema, schema free)yesyes
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.noyes
Secondary indexesrestrictedyesyesyes
SQL infoSupport of SQLyes infodoes not fully support an SQL-standardwith Databricks SQLSQL-like DML and DDL statementsyes
APIs and other access methodsJDBC
ODBC
JDBC
ODBC
RESTful HTTP API
JDBC
ODBC
Thrift
JDBC
Native Spark Datasource
ODBC
Supported programming languagesAll languages supporting JDBC/ODBCPython
R
Scala
C++
Java
PHP
Python
C#
C++
Java
JavaScript (Node.js)
Python
R
Scala
Server-side scripts infoStored proceduresuser defined functions infoin Pythonuser defined functions and aggregatesyes infouser defined functions and integration of map-reduceyes infoJava
Triggersnonoyes
Partitioning methods infoMethods for storing different data on different nodesShardingShardingShared Nothhing Auto-Sharding, Columnar Partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesyesyesselectable replication factorMulti-source replication
Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyes infoquery execution via MapReduceYes, via Full Spark Integration
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyEventual ConsistencyImmediate Consistency
Foreign keys infoReferential integrityyes infoinformational only, not enforced by the systemnoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACIDnoACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes, multi-version concurrency control (MVCC)
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.yesnoyes
User concepts infoAccess controlfine grained access rights according to SQL-standardAccess rights for users, groups and rolesAccess rights for users, groups and roles according to SQL-standard
More information provided by the system vendor
Amazon RedshiftDatabricksHiveSplice Machine
Specific characteristicsSupported database models : In addition to the Document store and Relational DBMS...
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More resources
Amazon RedshiftDatabricksHiveSplice Machine
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