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DBMS > Apache Impala vs. Databricks vs. FatDB vs. Hive

System Properties Comparison Apache Impala vs. Databricks vs. FatDB vs. Hive

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Editorial information provided by DB-Engines
NameApache Impala  Xexclude from comparisonDatabricks  Xexclude from comparisonFatDB  Xexclude from comparisonHive  Xexclude from comparison
FatDB/FatCloud has ceased operations as a company with February 2014. FatDB is discontinued and excluded from the ranking.
DescriptionAnalytic DBMS for HadoopThe 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.A .NET NoSQL DBMS that can integrate with and extend SQL Server.data warehouse software for querying and managing large distributed datasets, built on Hadoop
Primary database modelRelational DBMSDocument store
Relational DBMS
Document store
Key-value store
Relational DBMS
Secondary database modelsDocument store
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score13.77
Rank#40  Overall
#24  Relational DBMS
Score78.61
Rank#15  Overall
#2  Document stores
#10  Relational DBMS
Score61.17
Rank#18  Overall
#12  Relational DBMS
Websiteimpala.apache.orgwww.databricks.comhive.apache.org
Technical documentationimpala.apache.org/­impala-docs.htmldocs.databricks.comcwiki.apache.org/­confluence/­display/­Hive/­Home
DeveloperApache Software Foundation infoApache top-level project, originally developed by ClouderaDatabricksFatCloudApache Software Foundation infoinitially developed by Facebook
Initial release2013201320122012
Current release4.1.0, June 20223.1.3, April 2022
License infoCommercial or Open SourceOpen Source infoApache Version 2commercialcommercialOpen Source infoApache Version 2
Cloud-based only infoOnly available as a cloud servicenoyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC++C#Java
Server operating systemsLinuxhostedWindowsAll OS with a Java VM
Data schemeyesFlexible Schema (defined schema, partial schema, schema free)schema-freeyes
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 indexesyesyesyesyes
SQL infoSupport of SQLSQL-like DML and DDL statementswith Databricks SQLno infoVia inetgration in SQL ServerSQL-like DML and DDL statements
APIs and other access methodsJDBC
ODBC
JDBC
ODBC
RESTful HTTP API
.NET Client API
LINQ
RESTful HTTP API
RPC
Windows WCF Bindings
JDBC
ODBC
Thrift
Supported programming languagesAll languages supporting JDBC/ODBCPython
R
Scala
C#C++
Java
PHP
Python
Server-side scripts infoStored proceduresyes infouser defined functions and integration of map-reduceuser defined functions and aggregatesyes infovia applicationsyes infouser defined functions and integration of map-reduce
Triggersnoyes infovia applicationsno
Partitioning methods infoMethods for storing different data on different nodesShardingShardingSharding
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factoryesselectable replication factorselectable replication factor
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infoquery execution via MapReduceyesyes infoquery execution via MapReduce
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual ConsistencyImmediate ConsistencyEventual Consistency
Immediate Consistency
Eventual Consistency
Foreign keys infoReferential integritynonono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDnono
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.nono
User concepts infoAccess controlAccess rights for users, groups and roles infobased on Apache Sentry and Kerberosno infoCan implement custom security layer via applicationsAccess rights for users, groups and roles
More information provided by the system vendor
Apache ImpalaDatabricksFatDBHive
Specific characteristicsSupported database models : In addition to the Document store and Relational DBMS...
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More resources
Apache ImpalaDatabricksFatDBHive
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