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

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

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Editorial information provided by DB-Engines
NameApache Impala  Xexclude from comparisonEsgynDB  Xexclude from comparisonNetezza infoAlso called PureData System for Analytics by IBM  Xexclude from comparisonPrometheus  Xexclude from comparison
DescriptionAnalytic DBMS for HadoopEnterprise-class SQL-on-Hadoop solution, powered by Apache TrafodionData warehouse and analytics appliance part of IBM PureSystemsOpen-source Time Series DBMS and monitoring system
Primary database modelRelational DBMSRelational DBMSRelational DBMSTime Series DBMS
Secondary database modelsDocument store
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score10.63
Rank#40  Overall
#24  Relational DBMS
Score0.15
Rank#325  Overall
#144  Relational DBMS
Score7.56
Rank#48  Overall
#31  Relational DBMS
Score7.56
Rank#49  Overall
#3  Time Series DBMS
Websiteimpala.apache.orgwww.esgyn.cnwww.ibm.com/­products/­netezzaprometheus.io
Technical documentationimpala.apache.org/­impala-docs.htmlprometheus.io/­docs
DeveloperApache Software Foundation infoApache top-level project, originally developed by ClouderaEsgynIBM
Initial release2013201520002015
Current release4.1.0, June 2022
License infoCommercial or Open SourceOpen Source infoApache Version 2commercialcommercialOpen Source infoApache 2.0
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 infoincluded in applianceLinux
Windows
Data schemeyesyesyesyes
Typing infopredefined data types such as float or dateyesyesyesNumeric data only
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 infoImport of XML data possible
Secondary indexesyesyesyesno
SQL infoSupport of SQLSQL-like DML and DDL statementsyesyesno
APIs and other access methodsJDBC
ODBC
ADO.NET
JDBC
ODBC
JDBC
ODBC
OLE DB
RESTful HTTP/JSON API
Supported programming languagesAll languages supporting JDBC/ODBCAll languages supporting JDBC/ODBC/ADO.NetC
C++
Fortran
Java
Lua
Perl
Python
R
.Net
C++
Go
Haskell
Java
JavaScript (Node.js)
Python
Ruby
Server-side scripts infoStored proceduresyes infouser defined functions and integration of map-reduceJava Stored Proceduresyesno
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 datacentersSource-replica replicationyes infoby Federation
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infoquery execution via MapReduceyesyesno
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual ConsistencyImmediate Consistencynone
Foreign keys infoReferential integritynoyesnono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDACIDno
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
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.nonono
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 conceptno

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More resources
Apache ImpalaEsgynDBNetezza infoAlso called PureData System for Analytics by IBMPrometheus
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