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DBMS > Apache Impala vs. Bangdb vs. Hive vs. Netezza

System Properties Comparison Apache Impala vs. Bangdb vs. Hive vs. Netezza

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Editorial information provided by DB-Engines
NameApache Impala  Xexclude from comparisonBangdb  Xexclude from comparisonHive  Xexclude from comparisonNetezza infoAlso called PureData System for Analytics by IBM  Xexclude from comparison
DescriptionAnalytic DBMS for HadoopConverged and high performance database for device data, events, time series, document and graphdata warehouse software for querying and managing large distributed datasets, built on HadoopData warehouse and analytics appliance part of IBM PureSystems
Primary database modelRelational DBMSDocument store
Graph DBMS
Time Series DBMS
Relational DBMSRelational DBMS
Secondary database modelsDocument storeSpatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score12.45
Rank#40  Overall
#24  Relational DBMS
Score0.16
Rank#338  Overall
#47  Document stores
#32  Graph DBMS
#31  Time Series DBMS
Score59.76
Rank#18  Overall
#12  Relational DBMS
Score8.59
Rank#45  Overall
#29  Relational DBMS
Websiteimpala.apache.orgbangdb.comhive.apache.orgwww.ibm.com/­products/­netezza
Technical documentationimpala.apache.org/­impala-docs.htmldocs.bangdb.comcwiki.apache.org/­confluence/­display/­Hive/­Home
DeveloperApache Software Foundation infoApache top-level project, originally developed by ClouderaSachin Sinha, BangDBApache Software Foundation infoinitially developed by FacebookIBM
Initial release2013201220122000
Current release4.1.0, June 2022BangDB 2.0, October 20213.1.3, April 2022
License infoCommercial or Open SourceOpen Source infoApache Version 2Open Source infoBSD 3Open Source infoApache Version 2commercial
Cloud-based only infoOnly available as a cloud servicenononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC++C, C++Java
Server operating systemsLinuxLinuxAll OS with a Java VMLinux infoincluded in appliance
Data schemeyesschema-freeyesyes
Typing infopredefined data types such as float or dateyesyes: string, long, double, int, geospatial, stream, eventsyesyes
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 indexesyesyes infosecondary, composite, nested, reverse, geospatialyesyes
SQL infoSupport of SQLSQL-like DML and DDL statementsSQL like support with command line toolSQL-like DML and DDL statementsyes
APIs and other access methodsJDBC
ODBC
Proprietary protocol
RESTful HTTP API
JDBC
ODBC
Thrift
JDBC
ODBC
OLE DB
Supported programming languagesAll languages supporting JDBC/ODBCC
C#
C++
Java
Python
C++
Java
PHP
Python
C
C++
Fortran
Java
Lua
Perl
Python
R
Server-side scripts infoStored proceduresyes infouser defined functions and integration of map-reducenoyes infouser defined functions and integration of map-reduceyes
Triggersnoyes, Notifications (with Streaming only)nono
Partitioning methods infoMethods for storing different data on different nodesShardingSharding (enterprise version only). P2P based virtual network overlay with consistent hashing and chord algorithmShardingSharding
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factorselectable replication factor, Knob for CAP (enterprise version only)selectable replication factorSource-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infoquery execution via MapReducenoyes infoquery execution via MapReduceyes
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual ConsistencyTunable consistency, set CAP knob accordinglyEventual Consistency
Foreign keys infoReferential integritynononono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDnoACID
Concurrency infoSupport for concurrent manipulation of datayesyes, optimistic concurrency controlyesyes
Durability infoSupport for making data persistentyesyes, implements WAL (Write ahead log) as wellyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyes, run db with in-memory only mode
User concepts infoAccess controlAccess rights for users, groups and roles infobased on Apache Sentry and Kerberosyes (enterprise version only)Access rights for users, groups and rolesUsers with fine-grained authorization concept

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