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DBMS > Apache Impala vs. Netezza vs. PostgreSQL vs. XTDB vs. Yaacomo

System Properties Comparison Apache Impala vs. Netezza vs. PostgreSQL vs. XTDB vs. Yaacomo

Editorial information provided by DB-Engines
NameApache Impala  Xexclude from comparisonNetezza infoAlso called PureData System for Analytics by IBM  Xexclude from comparisonPostgreSQL  Xexclude from comparisonXTDB infoformerly named Crux  Xexclude from comparisonYaacomo  Xexclude from comparison
Yaacomo seems to be discontinued and is removed from the DB-Engines ranking
DescriptionAnalytic DBMS for HadoopData warehouse and analytics appliance part of IBM PureSystemsWidely used open source RDBMS infoDeveloped as objectoriented DBMS (Postgres), gradually enhanced with 'standards' like SQLA general purpose database with bitemporal SQL and Datalog and graph queriesOpenCL based in-memory RDBMS, designed for efficiently utilizing the hardware via parallel computing
Primary database modelRelational DBMSRelational DBMSRelational DBMS infowith object oriented extensions, e.g.: user defined types/functions and inheritance. Handling of key/value pairs with hstore module.Document storeRelational DBMS
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
Score14.03
Rank#40  Overall
#24  Relational DBMS
Score10.18
Rank#46  Overall
#29  Relational DBMS
Score645.05
Rank#4  Overall
#4  Relational DBMS
Score0.09
Rank#351  Overall
#47  Document stores
Websiteimpala.apache.orgwww.ibm.com/­products/­netezzawww.postgresql.orggithub.com/­xtdb/­xtdb
www.xtdb.com
yaacomo.com
Technical documentationimpala.apache.org/­impala-docs.htmlwww.postgresql.org/­docswww.xtdb.com/­docs
DeveloperApache Software Foundation infoApache top-level project, originally developed by ClouderaIBMPostgreSQL Global Development Group infowww.postgresql.org/­developerJuxt Ltd.Q2WEB GmbH
Initial release201320001989 info1989: Postgres, 1996: PostgreSQL20192009
Current release4.1.0, June 202216.2, February 20241.19, September 2021
License infoCommercial or Open SourceOpen Source infoApache Version 2commercialOpen Source infoBSDOpen Source infoMIT Licensecommercial
Cloud-based only infoOnly available as a cloud servicenonononono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Aiven for PostgreSQL: Fully managed PostgreSQL for developers with 70+ extensions and flexible orchestration tools.
Implementation languageC++CClojure
Server operating systemsLinuxLinux infoincluded in applianceFreeBSD
HP-UX
Linux
NetBSD
OpenBSD
OS X
Solaris
Unix
Windows
All OS with a Java 8 (and higher) VM
Linux
Android
Linux
Windows
Data schemeyesyesyesschema-freeyes
Typing infopredefined data types such as float or dateyesyesyesyes, extensible-data-notation formatyes
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.noyes infospecific XML-type available, but no XML query functionality.nono
Secondary indexesyesyesyesyesyes
SQL infoSupport of SQLSQL-like DML and DDL statementsyesyes infostandard with numerous extensionslimited SQL, making use of Apache Calciteyes
APIs and other access methodsJDBC
ODBC
JDBC
ODBC
OLE DB
ADO.NET
JDBC
native C library
ODBC
streaming API for large objects
HTTP REST
JDBC
JDBC
ODBC
Supported programming languagesAll languages supporting JDBC/ODBCC
C++
Fortran
Java
Lua
Perl
Python
R
.Net
C
C++
Delphi
Java infoJDBC
JavaScript (Node.js)
Perl
PHP
Python
Tcl
Clojure
Java
Server-side scripts infoStored proceduresyes infouser defined functions and integration of map-reduceyesuser defined functions inforealized in proprietary language PL/pgSQL or with common languages like Perl, Python, Tcl etc.no
Triggersnonoyesnoyes
Partitioning methods infoMethods for storing different data on different nodesShardingShardingpartitioning by range, list and (since PostgreSQL 11) by hashnonehorizontal partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factorSource-replica replicationSource-replica replication infoother methods possible by using 3rd party extensionsyes, each node contains all dataSource-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infoquery execution via MapReduceyesnonono
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual ConsistencyImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynonoyesnoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDACIDACIDACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentyesyesyesyes, flexibel persistency by using storage technologies like Apache Kafka, RocksDB or LMDByes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.nonoyes
User concepts infoAccess controlAccess rights for users, groups and roles infobased on Apache Sentry and KerberosUsers with fine-grained authorization conceptfine grained access rights according to SQL-standardfine grained access rights according to SQL-standard

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More resources
Apache ImpalaNetezza infoAlso called PureData System for Analytics by IBMPostgreSQLXTDB infoformerly named CruxYaacomo
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