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DBMS > Apache Impala vs. GigaSpaces vs. Kdb vs. Netezza

System Properties Comparison Apache Impala vs. GigaSpaces vs. Kdb vs. Netezza

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Editorial information provided by DB-Engines
NameApache Impala  Xexclude from comparisonGigaSpaces  Xexclude from comparisonKdb  Xexclude from comparisonNetezza infoAlso called PureData System for Analytics by IBM  Xexclude from comparison
DescriptionAnalytic DBMS for HadoopHigh performance in-memory data grid platform, powering three products: Smart Cache, Smart ODS (Operational Data Store), Smart Augmented TransactionsHigh performance Time Series DBMSData warehouse and analytics appliance part of IBM PureSystems
Primary database modelRelational DBMSDocument store
Object oriented DBMS infoValues are user defined objects
Time Series DBMS
Vector DBMS
Relational DBMS
Secondary database modelsDocument storeGraph DBMS
Search engine
Relational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score10.63
Rank#40  Overall
#24  Relational DBMS
Score0.91
Rank#197  Overall
#33  Document stores
#7  Object oriented DBMS
Score7.73
Rank#45  Overall
#2  Time Series DBMS
#1  Vector DBMS
Score7.56
Rank#48  Overall
#31  Relational DBMS
Websiteimpala.apache.orgwww.gigaspaces.comkx.comwww.ibm.com/­products/­netezza
Technical documentationimpala.apache.org/­impala-docs.htmldocs.gigaspaces.com/­latest/­landing.htmlcode.kx.com
DeveloperApache Software Foundation infoApache top-level project, originally developed by ClouderaGigaspaces TechnologiesKx Systems, a division of First Derivatives plcIBM
Initial release201320002000 infokdb was released 2000, kdb+ in 20032000
Current release4.1.0, June 202215.5, September 20203.6, May 2018
License infoCommercial or Open SourceOpen Source infoApache Version 2Open Source infoApache Version 2; Commercial licenses availablecommercial infofree 32-bit versioncommercial
Cloud-based only infoOnly available as a cloud servicenononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC++Java, C++, .Netq
Server operating systemsLinuxLinux
macOS
Solaris
Windows
Linux
OS X
Solaris
Windows
Linux infoincluded in appliance
Data schemeyesschema-freeyesyes
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.nono infoXML can be used for describing objects metadatayes
Secondary indexesyesyesyes infotable attribute 'grouped'yes
SQL infoSupport of SQLSQL-like DML and DDL statementsSQL-99 for query and DML statementsSQL-like query language (q)yes
APIs and other access methodsJDBC
ODBC
GigaSpaces LRMI
Hibernate
JCache
JDBC
JPA
ODBC
RESTful HTTP API
Spring Data
HTTP API
JDBC
Jupyter
Kafka
ODBC
WebSocket
JDBC
ODBC
OLE DB
Supported programming languagesAll languages supporting JDBC/ODBC.Net
C++
Java
Python
Scala
C
C#
C++
Go
J
Java
JavaScript
Lua
MatLab
Perl
PHP
Python
R
Scala
C
C++
Fortran
Java
Lua
Perl
Python
R
Server-side scripts infoStored proceduresyes infouser defined functions and integration of map-reduceyesuser defined functionsyes
Triggersnoyes, event driven architectureyes infowith viewsno
Partitioning methods infoMethods for storing different data on different nodesShardingShardinghorizontal partitioningSharding
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factorMulti-source replication infosynchronous or asynchronous
Source-replica replication infosynchronous or asynchronous
Source-replica replicationSource-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infoquery execution via MapReduceyes infoMap-Reduce pattern can be built with XAP task executorsno infosimilar paradigm used for internal processingyes
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual ConsistencyImmediate Consistency infoConsistency level configurable: ALL, QUORUM, ANYImmediate Consistency
Foreign keys infoReferential integritynonoyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDnoACID
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.noyesyes
User concepts infoAccess controlAccess rights for users, groups and roles infobased on Apache Sentry and KerberosRole-based access controlrights management via user accountsUsers with fine-grained authorization concept
More information provided by the system vendor
Apache ImpalaGigaSpacesKdbNetezza infoAlso called PureData System for Analytics by IBM
Specific characteristicsIntegrated columnar database & programming system for streaming, real time and historical...
» more
Competitive advantagesprovides seamless scalability; runs on industry standard server platforms; is top-ranked...
» more
Typical application scenariostick database streaming sensor data massive intelligence applications oil and gas...
» more
Key customersGoldman Sachs Morgan Stanley Merrill Lynch J.P. Morgan Deutsche Bank IEX Securities...
» more
Market metricskdb+ performance and reliability proven by our customers in critical infrastructure...
» more
Licensing and pricing modelsupon request
» more

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