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

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

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Editorial information provided by DB-Engines
NameApache Impala  Xexclude from comparisonEsgynDB  Xexclude from comparisonITTIA  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 TrafodionEdge Time Series DBMS with Real-Time Stream ProcessingData warehouse and analytics appliance part of IBM PureSystems
Primary database modelRelational DBMSRelational DBMSTime Series DBMSRelational DBMS
Secondary database modelsDocument storeRelational DBMS
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
Score0.44
Rank#267  Overall
#23  Time Series DBMS
Score8.59
Rank#45  Overall
#29  Relational DBMS
Websiteimpala.apache.orgwww.esgyn.cnwww.ittia.comwww.ibm.com/­products/­netezza
Technical documentationimpala.apache.org/­impala-docs.html
DeveloperApache Software Foundation infoApache top-level project, originally developed by ClouderaEsgynITTIA L.L.C.IBM
Initial release2013201520072000
Current release4.1.0, June 20228.7
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++, JavaC and C++
Server operating systemsLinuxLinuxLinux
Windows
Linux infoincluded in appliance
Data schemeyesyesFixed schemayes
Typing infopredefined data types such as float or dateyesyesFloat/Blob/Integer/String/Unicode/Date/Time/Timestamp/Intervalyes
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 indexesyesyesyesyes
SQL infoSupport of SQLSQL-like DML and DDL statementsyesyesyes
APIs and other access methodsJDBC
ODBC
ADO.NET
JDBC
ODBC
JDBC
ODBC
RESTful HTTP API
WebSocket
JDBC
ODBC
OLE DB
Supported programming languagesAll languages supporting JDBC/ODBCAll languages supporting JDBC/ODBC/ADO.NetC
C++
JavaScript (Node.js)
Python
C
C++
Fortran
Java
Lua
Perl
Python
R
Server-side scripts infoStored proceduresyes infouser defined functions and integration of map-reduceJava Stored Proceduresyesyes
Triggersnononono
Partitioning methods infoMethods for storing different data on different nodesShardingShardingSharding
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 MapReduceyesnoyes
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 datayesyesyes, multi-version concurrency control (MVCC)yes
Durability infoSupport for making data persistentyesyesyesyes
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-standardDatabase file passwordsUsers with fine-grained authorization concept

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