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DBMS > Apache Impala vs. Faircom DB vs. Netezza vs. PostgreSQL

System Properties Comparison Apache Impala vs. Faircom DB vs. Netezza vs. PostgreSQL

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Editorial information provided by DB-Engines
NameApache Impala  Xexclude from comparisonFaircom DB infoformerly c-treeACE  Xexclude from comparisonNetezza infoAlso called PureData System for Analytics by IBM  Xexclude from comparisonPostgreSQL  Xexclude from comparison
DescriptionAnalytic DBMS for HadoopNative high-speed multi-model DBMS for relational and key-value store data simultaneously accessible through SQL and NoSQL APIs.Data warehouse and analytics appliance part of IBM PureSystemsWidely used open source RDBMS infoDeveloped as objectoriented DBMS (Postgres), gradually enhanced with 'standards' like SQL
Primary database modelRelational DBMSKey-value store
Relational DBMS
Relational DBMSRelational DBMS infowith object oriented extensions, e.g.: user defined types/functions and inheritance. Handling of key/value pairs with hstore module.
Secondary database modelsDocument storeDocument store
Graph DBMS infowith Apache Age
Spatial DBMS
Vector DBMS infowith pgvector extension
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score13.77
Rank#40  Overall
#24  Relational DBMS
Score0.20
Rank#318  Overall
#48  Key-value stores
#141  Relational DBMS
Score9.06
Rank#46  Overall
#29  Relational DBMS
Score645.54
Rank#4  Overall
#4  Relational DBMS
Websiteimpala.apache.orgwww.faircom.com/­products/­faircom-dbwww.ibm.com/­products/­netezzawww.postgresql.org
Technical documentationimpala.apache.org/­impala-docs.htmldocs.faircom.com/­docs/­en/­UUID-7446ae34-a1a7-c843-c894-d5322e395184.htmlwww.postgresql.org/­docs
DeveloperApache Software Foundation infoApache top-level project, originally developed by ClouderaFairCom CorporationIBMPostgreSQL Global Development Group infowww.postgresql.org/­developer
Initial release2013197920001989 info1989: Postgres, 1996: PostgreSQL
Current release4.1.0, June 2022V12, November 202016.3, May 2024
License infoCommercial or Open SourceOpen Source infoApache Version 2commercial infoRestricted, free version availablecommercialOpen Source infoBSD
Cloud-based only infoOnly available as a cloud servicenononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC++ANSI C, C++C
Server operating systemsLinuxAIX
FreeBSD
HP-UX
Linux
NetBSD
OS X
QNX
SCO
Solaris
VxWorks
Windows infoeasily portable to other OSs
Linux infoincluded in applianceFreeBSD
HP-UX
Linux
NetBSD
OpenBSD
OS X
Solaris
Unix
Windows
Data schemeyesschema free, schema optional, schema required, partial schema,yesyes
Typing infopredefined data types such as float or dateyesyes, ANSI SQL Types, JSON, typed binary structuresyesyes
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.nonoyes infospecific XML-type available, but no XML query functionality.
Secondary indexesyesyesyesyes
SQL infoSupport of SQLSQL-like DML and DDL statementsyes, ANSI SQL with proprietary extensionsyesyes infostandard with numerous extensions
APIs and other access methodsJDBC
ODBC
ADO.NET
Direct SQL
JDBC
JPA
ODBC
RESTful HTTP/JSON API
RESTful MQTT/JSON API
RPC
JDBC
ODBC
OLE DB
ADO.NET
JDBC
native C library
ODBC
streaming API for large objects
Supported programming languagesAll languages supporting JDBC/ODBC.Net
C
C#
C++
Java
JavaScript (Node.js and browser)
PHP
Python
Visual Basic
C
C++
Fortran
Java
Lua
Perl
Python
R
.Net
C
C++
Delphi
Java infoJDBC
JavaScript (Node.js)
Perl
PHP
Python
Tcl
Server-side scripts infoStored proceduresyes infouser defined functions and integration of map-reduceyes info.Net, JavaScript, C/C++yesuser defined functions inforealized in proprietary language PL/pgSQL or with common languages like Perl, Python, Tcl etc.
Triggersnoyesnoyes
Partitioning methods infoMethods for storing different data on different nodesShardingFile partitioning, horizontal partitioning, sharding infoCustomizable business rules for table partitioningShardingpartitioning by range, list and (since PostgreSQL 11) by hash
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factoryes, configurable to be parallel or serial, synchronous or asynchronous, uni-directional or bi-directional, ACID-consistent or eventually consistent (with custom conflict resolution).Source-replica replicationSource-replica replication infoother methods possible by using 3rd party extensions
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infoquery execution via MapReducenoyesno
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual ConsistencyEventual Consistency
Immediate Consistency
Tunable consistency per server, database, table, and transaction
Immediate Consistency
Foreign keys infoReferential integritynoyesnoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanotunable from ACID to Eventually ConsistentACIDACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesYes, tunable from durable to delayed durability to in-memoryyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyesno
User concepts infoAccess controlAccess rights for users, groups and roles infobased on Apache Sentry and KerberosFine grained access rights according to SQL-standard with additional protections for filesUsers with fine-grained authorization conceptfine grained access rights according to SQL-standard

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More resources
Apache ImpalaFaircom DB infoformerly c-treeACENetezza infoAlso called PureData System for Analytics by IBMPostgreSQL
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