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DBMS > Apache Impala vs. OpenQM vs. Postgres-XL

System Properties Comparison Apache Impala vs. OpenQM vs. Postgres-XL

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Editorial information provided by DB-Engines
NameApache Impala  Xexclude from comparisonOpenQM infoalso called QM  Xexclude from comparisonPostgres-XL  Xexclude from comparison
DescriptionAnalytic DBMS for HadoopQpenQM is a high-performance, self-tuning, multi-value DBMSBased on PostgreSQL enhanced with MPP and write-scale-out cluster features
Primary database modelRelational DBMSMultivalue DBMSRelational DBMS
Secondary database modelsDocument storeDocument store
Spatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score12.57
Rank#40  Overall
#24  Relational DBMS
Score0.26
Rank#296  Overall
#10  Multivalue DBMS
Score0.46
Rank#258  Overall
#120  Relational DBMS
Websiteimpala.apache.orgwww.rocketsoftware.com/­products/­rocket-multivalue-application-development-platform/­rocket-open-qmwww.postgres-xl.org
Technical documentationimpala.apache.org/­impala-docs.htmlwww.postgres-xl.org/­documentation
DeveloperApache Software Foundation infoApache top-level project, originally developed by ClouderaRocket Software, originally Martin Phillips
Initial release201319932014 infosince 2012, originally named StormDB
Current release4.1.0, June 20223.4-1210 R1, October 2018
License infoCommercial or Open SourceOpen Source infoApache Version 2Open Source infoGPLv2, extended commercial license availableOpen Source infoMozilla public license
Cloud-based only infoOnly available as a cloud servicenonono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC++C
Server operating systemsLinuxAIX
FreeBSD
Linux
macOS
Raspberry Pi
Solaris
Windows
Linux
macOS
Data schemeyesyes infowith some exceptionsyes
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.noyesyes infoXML type, but no XML query functionality
Secondary indexesyesyesyes
SQL infoSupport of SQLSQL-like DML and DDL statementsnoyes infodistributed, parallel query execution
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
Basic
C
Java
Objective C
PHP
Python
.Net
C
C++
Delphi
Erlang
Java
JavaScript (Node.js)
Perl
PHP
Python
Tcl
Server-side scripts infoStored proceduresyes infouser defined functions and integration of map-reduceyesuser defined functions
Triggersnoyesyes
Partitioning methods infoMethods for storing different data on different nodesShardingyeshorizontal partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factoryes
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infoquery execution via MapReducenono
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual ConsistencyImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynonoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDACID infoMVCC
Concurrency infoSupport for concurrent manipulation of datayesyesyes
Durability infoSupport for making data persistentyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.nono
User concepts infoAccess controlAccess rights for users, groups and roles infobased on Apache Sentry and KerberosAccess rights can be defined down to the item levelfine grained access rights according to SQL-standard

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More resources
Apache ImpalaOpenQM infoalso called QMPostgres-XL
Recent citations in the news

Apache Impala becomes Top-Level Project
28 November 2017, SDTimes.com

Cloudera Bringing Impala to AWS Cloud
28 November 2017, Datanami

How different SQL-on-Hadoop engines satisfy BI workloads
24 February 2016, CIO

Hudi: Uber Engineering’s Incremental Processing Framework on Apache Hadoop
12 March 2017, Uber

Updates & Upserts in Hadoop Ecosystem with Apache Kudu
27 October 2017, KDnuggets

provided by Google News



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