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DBMS > Apache Impala vs. Databricks vs. EDB Postgres vs. HBase vs. Sequoiadb

System Properties Comparison Apache Impala vs. Databricks vs. EDB Postgres vs. HBase vs. Sequoiadb

Editorial information provided by DB-Engines
NameApache Impala  Xexclude from comparisonDatabricks  Xexclude from comparisonEDB Postgres  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.The EDB Postgres Platform is an enterprise-class data management platform based on the open source database PostgreSQL with flexible deployment options and Oracle compatibility features, complemented by tool kits for management, integration, and migration.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 storeDocument store
Spatial DBMS
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
Score1.90
Rank#135  Overall
#63  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.comwww.enterprisedb.comhbase.apache.orgwww.sequoiadb.com
Technical documentationimpala.apache.org/­impala-docs.htmldocs.databricks.comwww.enterprisedb.com/­docshbase.apache.org/­book.htmlwww.sequoiadb.com/­en/­index.php?m=Files&a=index
DeveloperApache Software Foundation infoApache top-level project, originally developed by ClouderaDatabricksEnterpriseDBApache Software Foundation infoApache top-level project, originally developed by PowersetSequoiadb Ltd.
Initial release20132013200520082013
Current release4.1.0, June 202214, December 20212.3.4, January 2021
License infoCommercial or Open SourceOpen Source infoApache Version 2commercialcommercial infoBSD for PostgreSQL-componentsOpen 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++CJavaC++
Server operating systemsLinuxhostedLinux
Windows
Linux
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.noyesyes infospecific XML-type available, but no XML query functionality.nono
Secondary indexesyesyesyesnoyes
SQL infoSupport of SQLSQL-like DML and DDL statementswith Databricks SQLyes infostandard with numerous extensionsnoSQL-like query language
APIs and other access methodsJDBC
ODBC
JDBC
ODBC
RESTful HTTP API
ADO.NET
JDBC
native C library
ODBC
streaming API for large objects
Java API
RESTful HTTP API
Thrift
proprietary protocol using JSON
Supported programming languagesAll languages supporting JDBC/ODBCPython
R
Scala
.Net
C
C++
Delphi
Java
Perl
PHP
Python
Tcl
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 aggregatesuser defined functions inforealized in proprietary language PL/pgSQL or with common languages like Perl, Python, Tcl etc.yes infoCoprocessors in JavaJavaScript
Triggersnoyesyesno
Partitioning methods infoMethods for storing different data on different nodesShardinghorizontal partitioning infoby hash, list or rangeShardingSharding
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factoryesMulti-source 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 datayesyesyes, multi-version concurrency control (MVCC)yesyes
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.nononoyesno
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 ImpalaDatabricksEDB PostgresHBaseSequoiadb
Specific characteristicsSupported database models : In addition to the Document store and Relational DBMS...
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More resources
Apache ImpalaDatabricksEDB PostgresHBaseSequoiadb
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