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DBMS > Apache Impala vs. Fujitsu Enterprise Postgres

System Properties Comparison Apache Impala vs. Fujitsu Enterprise Postgres

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Editorial information provided by DB-Engines
NameApache Impala  Xexclude from comparisonFujitsu Enterprise Postgres  Xexclude from comparison
DescriptionAnalytic DBMS for HadoopEnterprise-grade PostgreSQL-based DBMS with security enhancements such as Transparent Data Encryption and Data Masking, plus high-availability and performance improvement features.
Primary database modelRelational DBMSRelational DBMS
Secondary database modelsDocument storeDocument store
Spatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score11.58
Rank#40  Overall
#24  Relational DBMS
Score0.27
Rank#290  Overall
#131  Relational DBMS
Websiteimpala.apache.orgwww.postgres.global.fujitsu.com
Technical documentationimpala.apache.org/­impala-docs.htmlwww.postgres.global.fujitsu.com/­product-manuals
DeveloperApache Software Foundation infoApache top-level project, originally developed by ClouderaFujitsu Limited
Initial release2013
Current release4.1.0, June 2022Fujitsu Enterprise Postgres 16, May 2024
License infoCommercial or Open SourceOpen Source infoApache Version 2commercial
Cloud-based only infoOnly available as a cloud servicenono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC++C
Server operating systemsLinuxLinux
Windows
Data schemeyesyes
Typing infopredefined data types such as float or dateyesyes
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.no
Secondary indexesyesyes
SQL infoSupport of SQLSQL-like DML and DDL statementsyes
APIs and other access methodsJDBC
ODBC
ADO.NET
JDBC
native C library
ODBC
streaming API for large objects
Supported programming languagesAll languages supporting JDBC/ODBC.Net
C
C++
Delphi
Java
JavaScript (Node.js)
Perl
PHP
Python
Tcl
Server-side scripts infoStored proceduresyes infouser defined functions and integration of map-reduceuser defined functions
Triggersnoyes
Partitioning methods infoMethods for storing different data on different nodesShardingpartitioning by range, list and by hash
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factorSource-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infoquery execution via MapReduceno
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual ConsistencyImmediate Consistency
Foreign keys infoReferential integritynoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACID
Concurrency infoSupport for concurrent manipulation of datayesyes, multi-version concurrency control (MVCC)
Durability infoSupport for making data persistentyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.no
User concepts infoAccess controlAccess rights for users, groups and roles infobased on Apache Sentry and Kerberosfine grained access rights according to SQL-standard

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More resources
Apache ImpalaFujitsu Enterprise Postgres
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