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DBMS > EsgynDB vs. Impala vs. Netezza

System Properties Comparison EsgynDB vs. Impala vs. Netezza

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Editorial information provided by DB-Engines
NameEsgynDB  Xexclude from comparisonImpala  Xexclude from comparisonNetezza infoAlso called PureData System for Analytics by IBM  Xexclude from comparison
DescriptionEnterprise-class SQL-on-Hadoop solution, powered by Apache TrafodionAnalytic DBMS for HadoopData warehouse and analytics appliance part of IBM PureSystems
Primary database modelRelational DBMSRelational DBMSRelational DBMS
Secondary database modelsDocument store
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.24
Rank#278  Overall
#129  Relational DBMS
Score18.71
Rank#38  Overall
#23  Relational DBMS
Score20.25
Rank#36  Overall
#22  Relational DBMS
Websitewww.esgyn.cnwww.cloudera.com/­products/­open-source/­apache-hadoop/­impala.htmlwww.ibm.com/­products/­netezza
Technical documentationdocs.cloudera.com/­documentation/­enterprise/­latest/­topics/­impala.html
DeveloperEsgynClouderaIBM
Initial release201520132000
Current release3.4.0, April 2020
License infoCommercial or Open SourcecommercialOpen Source infoApache Version 2commercial
Cloud-based only infoOnly available as a cloud servicenonono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC++, JavaC++
Server operating systemsLinuxLinuxLinux infoincluded in appliance
Data schemeyesyesyes
Typing infopredefined data types such as float or dateyesyesyes
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 indexesyesyesyes
SQL infoSupport of SQLyesSQL-like DML and DDL statementsyes
APIs and other access methodsADO.NET
JDBC
ODBC
JDBC
ODBC
JDBC
ODBC
OLE DB
Supported programming languagesAll languages supporting JDBC/ODBC/ADO.NetAll languages supporting JDBC/ODBCC
C++
Fortran
Java
Lua
Perl
Python
R
Server-side scripts infoStored proceduresJava Stored Proceduresyes infouser defined functions and integration of map-reduceyes
Triggersnonono
Partitioning methods infoMethods for storing different data on different nodesShardingShardingSharding
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication between multi datacentersselectable replication factorSource-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsyesyes infoquery execution via MapReduceyes
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyEventual Consistency
Foreign keys infoReferential integrityyesnono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDnoACID
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 controlfine grained access rights according to SQL-standardAccess rights for users, groups and roles infobased on Apache Sentry and KerberosUsers with fine-grained authorization concept

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More resources
EsgynDBImpalaNetezza infoAlso called PureData System for Analytics by IBM
Recent citations in the news

Cloudera Boosts Hadoop App Development On Impala
10 November 2014, InformationWeek

Cloudera’s Impala brings Hadoop to SQL and BI
25 October 2012, ZDNet

Man Busts Out of Google, Rebuilds Top-Secret Query Machine
24 October 2012, Wired

Cloudera aims to bring real-time queries to Hadoop, big data
24 October 2012, ZDNet

Unravel Data Adds Native Support for Impala and Kafka
29 June 2017, insideBIGDATA

provided by Google News

IBM Brings Back a Netezza, Attacks Yellowbrick
29 June 2020, Datanami

The Accelerated Path To Petabyte-Scale Graph Databases
28 October 2021, The Next Platform

IBM to Acquire Netezza for $1.78 Billion - WSJ
20 September 2010, Wall Street Journal

IBM to buy analytics company Netezza for $1.7 billion
20 September 2010, Reuters

Accelerated Databases In The Fast Lane
25 June 2020, The Next Platform

provided by Google News

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