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

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

Editorial information provided by DB-Engines
NameApache Impala  Xexclude from comparisonInfinityDB  Xexclude from comparisonNetezza infoAlso called PureData System for Analytics by IBM  Xexclude from comparisonPostgreSQL  Xexclude from comparisonYaacomo  Xexclude from comparison
Yaacomo seems to be discontinued and is removed from the DB-Engines ranking
DescriptionAnalytic DBMS for HadoopA Java embedded Key-Value Store which extends the Java Map interfaceData warehouse and analytics appliance part of IBM PureSystemsWidely used open source RDBMS infoDeveloped as objectoriented DBMS (Postgres), gradually enhanced with 'standards' like SQLOpenCL based in-memory RDBMS, designed for efficiently utilizing the hardware via parallel computing
Primary database modelRelational DBMSKey-value storeRelational DBMSRelational DBMS infowith object oriented extensions, e.g.: user defined types/functions and inheritance. Handling of key/value pairs with hstore module.Relational 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
Score10.63
Rank#40  Overall
#24  Relational DBMS
Score0.00
Rank#383  Overall
#59  Key-value stores
Score7.56
Rank#48  Overall
#31  Relational DBMS
Score644.36
Rank#4  Overall
#4  Relational DBMS
Websiteimpala.apache.orgboilerbay.comwww.ibm.com/­products/­netezzawww.postgresql.orgyaacomo.com
Technical documentationimpala.apache.org/­impala-docs.htmlboilerbay.com/­infinitydb/­manualwww.postgresql.org/­docs
DeveloperApache Software Foundation infoApache top-level project, originally developed by ClouderaBoiler Bay Inc.IBMPostgreSQL Global Development Group infowww.postgresql.org/­developerQ2WEB GmbH
Initial release2013200220001989 info1989: Postgres, 1996: PostgreSQL2009
Current release4.1.0, June 20224.016.4, August 2024
License infoCommercial or Open SourceOpen Source infoApache Version 2commercialcommercialOpen Source infoBSDcommercial
Cloud-based only infoOnly available as a cloud servicenonononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC++JavaC
Server operating systemsLinuxAll OS with a Java VMLinux infoincluded in applianceFreeBSD
HP-UX
Linux
NetBSD
OpenBSD
OS X
Solaris
Unix
Windows
Android
Linux
Windows
Data schemeyesyes infonested virtual Java Maps, multi-value, logical ‘tuple space’ runtime Schema upgradeyesyesyes
Typing infopredefined data types such as float or dateyesyes infoall Java primitives, Date, CLOB, BLOB, huge sparse arraysyesyesyes
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.no
Secondary indexesyesno infomanual creation possible, using inversions based on multi-value capabilityyesyesyes
SQL infoSupport of SQLSQL-like DML and DDL statementsnoyesyes infostandard with numerous extensionsyes
APIs and other access methodsJDBC
ODBC
Access via java.util.concurrent.ConcurrentNavigableMap Interface
Proprietary API to InfinityDB ItemSpace (boilerbay.com/­docs/­ItemSpaceDataStructures.htm)
JDBC
ODBC
OLE DB
ADO.NET
JDBC
native C library
ODBC
streaming API for large objects
JDBC
ODBC
Supported programming languagesAll languages supporting JDBC/ODBCJavaC
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-reducenoyesuser defined functions inforealized in proprietary language PL/pgSQL or with common languages like Perl, Python, Tcl etc.
Triggersnononoyesyes
Partitioning methods infoMethods for storing different data on different nodesShardingnoneShardingpartitioning by range, list and (since PostgreSQL 11) by hashhorizontal partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factornoneSource-replica replicationSource-replica replication infoother methods possible by using 3rd party extensionsSource-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infoquery execution via MapReducenoyesnono
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual ConsistencyImmediate Consistency infoREAD-COMMITTED or SERIALIZEDImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynono infomanual creation possible, using inversions based on multi-value capabilitynoyesyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACID infoOptimistic locking for transactions; no isolation for bulk loadsACIDACIDACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
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.nononoyes
User concepts infoAccess controlAccess rights for users, groups and roles infobased on Apache Sentry and KerberosnoUsers 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 ImpalaInfinityDBNetezza infoAlso called PureData System for Analytics by IBMPostgreSQLYaacomo
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Conferences, events and webinars

PASS Data Community Summit
Seattle, Washington, 4-8 November 2024

Recent citations in the news

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