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DBMS > Apache Impala vs. Databricks vs. FoundationDB vs. HBase vs. Sequoiadb

System Properties Comparison Apache Impala vs. Databricks vs. FoundationDB vs. HBase vs. Sequoiadb

Editorial information provided by DB-Engines
NameApache Impala  Xexclude from comparisonDatabricks  Xexclude from comparisonFoundationDB  Xexclude from comparisonHBase  Xexclude from comparisonSequoiadb  Xexclude from comparison
Created as commercial project in 2013, FoundationDB has been acquired by Apple in March 2015 and was withdrawn from the market. As a consequence, the product was removed from the DB-Engines ranking. In April 2018, Apple open-sourced FoundationDB and it therefore reappears in 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.Ordered key-value store. Core features are complimented by layers.Wide-column store based on Apache Hadoop and on concepts of BigTableNewSQL database with distributed OLTP and SQL
Primary database modelRelational DBMSDocument store
Relational DBMS
Document store infosupported via specific layer
Key-value store
Relational DBMS infosupported via specific SQL-layer
Wide column storeDocument 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
Score1.03
Rank#190  Overall
#31  Document stores
#28  Key-value stores
#89  Relational DBMS
Score30.50
Rank#26  Overall
#2  Wide column stores
Score0.45
Rank#261  Overall
#41  Document stores
#122  Relational DBMS
Websiteimpala.apache.orgwww.databricks.comgithub.com/­apple/­foundationdbhbase.apache.orgwww.sequoiadb.com
Technical documentationimpala.apache.org/­impala-docs.htmldocs.databricks.comapple.github.io/­foundationdbhbase.apache.org/­book.htmlwww.sequoiadb.com/­en/­index.php?m=Files&a=index
DeveloperApache Software Foundation infoApache top-level project, originally developed by ClouderaDatabricksFoundationDBApache Software Foundation infoApache top-level project, originally developed by PowersetSequoiadb Ltd.
Initial release20132013201320082013
Current release4.1.0, June 20226.2.28, November 20202.3.4, January 2021
License infoCommercial or Open SourceOpen Source infoApache Version 2commercialOpen Source infoApache 2.0Open Source infoApache version 2Open Source infoServer: AGPL; Client: Apache V2
Cloud-based only infoOnly available as a cloud servicenoyesnonono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC++C++JavaC++
Server operating systemsLinuxhostedLinux
OS X
Windows
Linux
Unix
Windows infousing Cygwin
Linux
Data schemeyesFlexible Schema (defined schema, partial schema, schema free)schema-free infosome layers support schemasschema-free, schema definition possibleschema-free
Typing infopredefined data types such as float or dateyesno infosome layers support typingoptions to bring your own types, AVROyes infooid, date, timestamp, binary, regex
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.noyesnono
Secondary indexesyesyesnonoyes
SQL infoSupport of SQLSQL-like DML and DDL statementswith Databricks SQLsupported in specific SQL layer onlynoSQL-like query language
APIs and other access methodsJDBC
ODBC
JDBC
ODBC
RESTful HTTP API
Java API
RESTful HTTP API
Thrift
proprietary protocol using JSON
Supported programming languagesAll languages supporting JDBC/ODBCPython
R
Scala
.Net
C
C++
Go
Java
JavaScript infoNode.js
PHP
Python
Ruby
Swift
C
C#
C++
Groovy
Java
PHP
Python
Scala
.Net
C++
Java
PHP
Python
Server-side scripts infoStored proceduresyes infouser defined functions and integration of map-reduceuser defined functions and aggregatesin SQL-layer onlyyes infoCoprocessors in JavaJavaScript
Triggersnonoyesno
Partitioning methods infoMethods for storing different data on different nodesShardingShardingShardingSharding
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factoryesyesMulti-source replication
Source-replica replication
Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infoquery execution via MapReducenoyesno
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual ConsistencyImmediate ConsistencyLinearizable consistencyImmediate Consistency or Eventual ConsistencyEventual Consistency
Foreign keys infoReferential integritynoin SQL-layer onlynono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDACIDSingle row ACID (across millions of columns)Document is locked during a transaction
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentyesyesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.nonoyesno
User concepts infoAccess controlAccess rights for users, groups and roles infobased on Apache Sentry and KerberosnoAccess Control Lists (ACL) for RBAC, integration with Apache Ranger for RBAC & ABACsimple password-based access control
More information provided by the system vendor
Apache ImpalaDatabricksFoundationDBHBaseSequoiadb
Specific characteristicsSupported database models : In addition to the Document store and Relational DBMS...
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Apache ImpalaDatabricksFoundationDBHBaseSequoiadb
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