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DBMS > Apache Impala vs. Fujitsu Enterprise Postgres vs. HBase vs. Hive

System Properties Comparison Apache Impala vs. Fujitsu Enterprise Postgres vs. HBase vs. Hive

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Editorial information provided by DB-Engines
NameApache Impala  Xexclude from comparisonFujitsu Enterprise Postgres  Xexclude from comparisonHBase  Xexclude from comparisonHive  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.Wide-column store based on Apache Hadoop and on concepts of BigTabledata warehouse software for querying and managing large distributed datasets, built on Hadoop
Primary database modelRelational DBMSRelational DBMSWide column storeRelational DBMS
Secondary database modelsDocument storeDocument store
Spatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score14.03
Rank#40  Overall
#24  Relational DBMS
Score0.37
Rank#281  Overall
#127  Relational DBMS
Score31.25
Rank#26  Overall
#2  Wide column stores
Score62.59
Rank#18  Overall
#12  Relational DBMS
Websiteimpala.apache.orgwww.postgresql.fastware.comhbase.apache.orghive.apache.org
Technical documentationimpala.apache.org/­impala-docs.htmlwww.postgresql.fastware.com/­product-manualshbase.apache.org/­book.htmlcwiki.apache.org/­confluence/­display/­Hive/­Home
DeveloperApache Software Foundation infoApache top-level project, originally developed by ClouderaPostgreSQL Global Development Group, Fujitsu Australia Software TechnologyApache Software Foundation infoApache top-level project, originally developed by PowersetApache Software Foundation infoinitially developed by Facebook
Initial release201320082012
Current release4.1.0, June 2022Fujitsu Enterprise Postgres 14, January 20222.3.4, January 20213.1.3, April 2022
License infoCommercial or Open SourceOpen Source infoApache Version 2commercialOpen Source infoApache version 2Open Source infoApache Version 2
Cloud-based only infoOnly available as a cloud servicenononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC++CJavaJava
Server operating systemsLinuxLinux
Windows
Linux
Unix
Windows infousing Cygwin
All OS with a Java VM
Data schemeyesyesschema-free, schema definition possibleyes
Typing infopredefined data types such as float or dateyesyesoptions to bring your own types, AVROyes
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.nono
Secondary indexesyesyesnoyes
SQL infoSupport of SQLSQL-like DML and DDL statementsyesnoSQL-like DML and DDL statements
APIs and other access methodsJDBC
ODBC
ADO.NET
JDBC
native C library
ODBC
streaming API for large objects
Java API
RESTful HTTP API
Thrift
JDBC
ODBC
Thrift
Supported programming languagesAll languages supporting JDBC/ODBC.Net
C
C++
Delphi
Java
JavaScript (Node.js)
Perl
PHP
Python
Tcl
C
C#
C++
Groovy
Java
PHP
Python
Scala
C++
Java
PHP
Python
Server-side scripts infoStored proceduresyes infouser defined functions and integration of map-reduceuser defined functionsyes infoCoprocessors in Javayes infouser defined functions and integration of map-reduce
Triggersnoyesyesno
Partitioning methods infoMethods for storing different data on different nodesShardingpartitioning by range, list and by hashShardingSharding
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factorSource-replica replicationMulti-source replication
Source-replica replication
selectable replication factor
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infoquery execution via MapReducenoyesyes infoquery execution via MapReduce
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual ConsistencyImmediate ConsistencyImmediate Consistency or Eventual ConsistencyEventual Consistency
Foreign keys infoReferential integritynoyesnono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDSingle row ACID (across millions of columns)no
Concurrency infoSupport for concurrent manipulation of datayesyes, multi-version concurrency control (MVCC)yesyes
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.noyes
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 & ABACAccess rights for users, groups and roles
More information provided by the system vendor
Apache ImpalaFujitsu Enterprise PostgresHBaseHive
Specific characteristics100% compatible with community PostgreSQL
» more
Competitive advantagesBuilt-in TDE and Data Masking security. In-Memory Columnar Index, and a high speed...
» more
Typical application scenariosTransactional payments applications, reporting and mixed workloads.
» more
Market metricsOver 30 years experience in database technology. Over 20 years in Postgres development...
» more
Licensing and pricing modelsCore based licensing
» more

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Apache ImpalaFujitsu Enterprise PostgresHBaseHive
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