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

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

Editorial information provided by DB-Engines
NameApache Impala  Xexclude from comparisonDatabricks  Xexclude from comparisonDerby infooften called Apache Derby, originally IBM Cloudscape; contained in the Java SDK as JavaDB  Xexclude from comparisonHBase  Xexclude from comparisonSequoiadb  Xexclude from comparison
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.Full-featured RDBMS with a small footprint, either embedded into a Java application or used as a database server.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
Relational DBMSWide 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
Score4.71
Rank#69  Overall
#37  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.comdb.apache.org/­derbyhbase.apache.orgwww.sequoiadb.com
Technical documentationimpala.apache.org/­impala-docs.htmldocs.databricks.comdb.apache.org/­derby/­manuals/­index.htmlhbase.apache.org/­book.htmlwww.sequoiadb.com/­en/­index.php?m=Files&a=index
DeveloperApache Software Foundation infoApache top-level project, originally developed by ClouderaDatabricksApache Software FoundationApache Software Foundation infoApache top-level project, originally developed by PowersetSequoiadb Ltd.
Initial release20132013199720082013
Current release4.1.0, June 202210.17.1.0, November 20232.3.4, January 2021
License infoCommercial or Open SourceOpen Source infoApache Version 2commercialOpen Source infoApache version 2Open 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++JavaJavaC++
Server operating systemsLinuxhostedAll OS with a Java VMLinux
Unix
Windows infousing Cygwin
Linux
Data schemeyesFlexible Schema (defined schema, partial schema, schema free)yesschema-free, schema definition possibleschema-free
Typing infopredefined data types such as float or dateyesyesoptions 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.noyesyesnono
Secondary indexesyesyesyesnoyes
SQL infoSupport of SQLSQL-like DML and DDL statementswith Databricks SQLyesnoSQL-like query language
APIs and other access methodsJDBC
ODBC
JDBC
ODBC
RESTful HTTP API
JDBCJava API
RESTful HTTP API
Thrift
proprietary protocol using JSON
Supported programming languagesAll languages supporting JDBC/ODBCPython
R
Scala
JavaC
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 aggregatesJava Stored Proceduresyes infoCoprocessors in JavaJavaScript
Triggersnoyesyesno
Partitioning methods infoMethods for storing different data on different nodesShardingnoneShardingSharding
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factoryesSource-replica replicationMulti-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 ConsistencyImmediate ConsistencyImmediate Consistency or Eventual ConsistencyEventual Consistency
Foreign keys infoReferential integritynoyesnono
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.nonoyesyesno
User concepts infoAccess controlAccess rights for users, groups and roles infobased on Apache Sentry and Kerberosfine grained access rights according to SQL-standardAccess Control Lists (ACL) for RBAC, integration with Apache Ranger for RBAC & ABACsimple password-based access control
More information provided by the system vendor
Apache ImpalaDatabricksDerby infooften called Apache Derby, originally IBM Cloudscape; contained in the Java SDK as JavaDBHBaseSequoiadb
Specific characteristicsSupported database models : In addition to the Document store and Relational DBMS...
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More resources
Apache ImpalaDatabricksDerby infooften called Apache Derby, originally IBM Cloudscape; contained in the Java SDK as JavaDBHBaseSequoiadb
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