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DBMS > Apache Impala vs. EsgynDB vs. FeatureBase vs. Netezza

System Properties Comparison Apache Impala vs. EsgynDB vs. FeatureBase vs. Netezza

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Editorial information provided by DB-Engines
NameApache Impala  Xexclude from comparisonEsgynDB  Xexclude from comparisonFeatureBase  Xexclude from comparisonNetezza infoAlso called PureData System for Analytics by IBM  Xexclude from comparison
DescriptionAnalytic DBMS for HadoopEnterprise-class SQL-on-Hadoop solution, powered by Apache TrafodionReal-time database platform that powers real-time analytics and machine learning applications by simultaneously executing low-latency, high-throughput, and highly concurrent workloads.Data warehouse and analytics appliance part of IBM PureSystems
Primary database modelRelational DBMSRelational DBMSRelational DBMSRelational DBMS
Secondary database modelsDocument store
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score12.45
Rank#40  Overall
#24  Relational DBMS
Score0.25
Rank#312  Overall
#138  Relational DBMS
Score0.31
Rank#292  Overall
#135  Relational DBMS
Score8.59
Rank#45  Overall
#29  Relational DBMS
Websiteimpala.apache.orgwww.esgyn.cnwww.featurebase.comwww.ibm.com/­products/­netezza
Technical documentationimpala.apache.org/­impala-docs.htmldocs.featurebase.com
DeveloperApache Software Foundation infoApache top-level project, originally developed by ClouderaEsgynMolecula and Pilosa Open Source ContributorsIBM
Initial release2013201520172000
Current release4.1.0, June 20222022, May 2022
License infoCommercial or Open SourceOpen Source infoApache Version 2commercialcommercialcommercial
Cloud-based only infoOnly available as a cloud servicenononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC++C++, JavaGo
Server operating systemsLinuxLinuxLinux
macOS
Linux infoincluded in appliance
Data schemeyesyesyesyes
Typing infopredefined data types such as float or dateyesyesyesyes
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.nonono
Secondary indexesyesyesnoyes
SQL infoSupport of SQLSQL-like DML and DDL statementsyesSQL queriesyes
APIs and other access methodsJDBC
ODBC
ADO.NET
JDBC
ODBC
gRPC
JDBC
Kafka Connector
ODBC
JDBC
ODBC
OLE DB
Supported programming languagesAll languages supporting JDBC/ODBCAll languages supporting JDBC/ODBC/ADO.NetJava
Python
C
C++
Fortran
Java
Lua
Perl
Python
R
Server-side scripts infoStored proceduresyes infouser defined functions and integration of map-reduceJava Stored Proceduresyes
Triggersnononono
Partitioning methods infoMethods for storing different data on different nodesShardingShardingShardingSharding
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factorMulti-source replication between multi datacentersyesSource-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infoquery execution via MapReduceyesyes
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual ConsistencyImmediate Consistency
Foreign keys infoReferential integritynoyesyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDyesACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyesyes, using Linux fsyncyes
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 Kerberosfine grained access rights according to SQL-standardUsers with fine-grained authorization concept

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More resources
Apache ImpalaEsgynDBFeatureBaseNetezza infoAlso called PureData System for Analytics by IBM
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