DB-EnginesInfluxDB: Focus on building software with an easy-to-use serverless, scalable time series platformEnglish
Deutsch
Knowledge Base of Relational and NoSQL Database Management Systemsprovided by solid IT

DBMS > InterSystems Caché vs. Netezza vs. Spark SQL vs. Trafodion

System Properties Comparison InterSystems Caché vs. Netezza vs. Spark SQL vs. Trafodion

Please select another system to include it in the comparison.

Editorial information provided by DB-Engines
NameInterSystems Caché  Xexclude from comparisonNetezza infoAlso called PureData System for Analytics by IBM  Xexclude from comparisonSpark SQL  Xexclude from comparisonTrafodion  Xexclude from comparison
Caché is a deprecated database engine which is substituted with InterSystems IRIS. It therefore is removed from the DB-Engines Ranking.Apache Trafodion has been retired in 2021. Therefore it is excluded from the DB-Engines Ranking.
DescriptionA multi-model DBMS and application serverData warehouse and analytics appliance part of IBM PureSystemsSpark SQL is a component on top of 'Spark Core' for structured data processingTransactional SQL-on-Hadoop DBMS
Primary database modelKey-value store
Object oriented DBMS
Relational DBMS
Relational DBMSRelational DBMSRelational DBMS
Secondary database modelsDocument store
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score8.59
Rank#45  Overall
#29  Relational DBMS
Score18.04
Rank#33  Overall
#20  Relational DBMS
Websitewww.intersystems.com/­products/­cachewww.ibm.com/­products/­netezzaspark.apache.org/­sqltrafodion.apache.org
Technical documentationdocs.intersystems.comspark.apache.org/­docs/­latest/­sql-programming-guide.htmltrafodion.apache.org/­documentation.html
DeveloperInterSystemsIBMApache Software FoundationApache Software Foundation, originally developed by HP
Initial release1997200020142014
Current release2018.1.4, May 20203.5.0 ( 2.13), September 20232.3.0, February 2019
License infoCommercial or Open SourcecommercialcommercialOpen Source infoApache 2.0Open Source infoApache 2.0
Cloud-based only infoOnly available as a cloud servicenononono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageScalaC++, Java
Server operating systemsAIX
HP Open VMS
HP-UX
Linux
OS X
Solaris
Windows
Linux infoincluded in applianceLinux
OS X
Windows
Linux
Data schemedepending on used data modelyesyesyes
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.yesnono
Secondary indexesyesyesnoyes
SQL infoSupport of SQLyesyesSQL-like DML and DDL statementsyes
APIs and other access methods.NET Client API
JDBC
ODBC
RESTful HTTP API
JDBC
ODBC
OLE DB
JDBC
ODBC
ADO.NET
JDBC
ODBC
Supported programming languagesC#
C++
Java
C
C++
Fortran
Java
Lua
Perl
Python
R
Java
Python
R
Scala
All languages supporting JDBC/ODBC/ADO.Net
Server-side scripts infoStored proceduresyesyesnoJava Stored Procedures
Triggersyesnonono
Partitioning methods infoMethods for storing different data on different nodesnoneShardingyes, utilizing Spark CoreSharding
Replication methods infoMethods for redundantly storing data on multiple nodesSource-replica replicationSource-replica replicationnoneyes, via HBase
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyesyes infovia user defined functions and HBase
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integrityyesnonoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACIDnoACID
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.yesnono
User concepts infoAccess controlAccess rights for users, groups and rolesUsers with fine-grained authorization conceptnofine grained access rights according to SQL-standard

More information provided by the system vendor

We invite representatives of system vendors to contact us for updating and extending the system information,
and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.

Related products and services

We invite representatives of vendors of related products to contact us for presenting information about their offerings here.

More resources
InterSystems CachéNetezza infoAlso called PureData System for Analytics by IBMSpark SQLTrafodion
Recent citations in the news

Cognizant Deploys a Comprehensive Hospital Performance Management Solution at Hunterdon Healthcare
21 February 2012, Cognizant news

AWS, GCP, Oracle, Azure, SAP Lead Cloud DBMS Market: Gartner
12 February 2022, CRN

Epic On EHR Interoperability: Not A '1-Time Project'
10 April 2015, InformationWeek

Associative Data Modeling Demystified – Part1
9 July 2016, Data Science Central

Announcing IBM Spectrum Sentinel: Building a Cyber Resilient Future
24 June 2022, ibm.com

provided by Google News

IBM announces availability of the high-performance, cloud-native Netezza Performance Server as a Service on AWS
11 July 2023, ibm.com

AWS and IBM Netezza come out in support of Iceberg in table format face-off
1 August 2023, The Register

Migrating your Netezza data warehouse to Amazon Redshift | Amazon Web Services
27 May 2020, AWS Blog

Netezza Performance Server
12 August 2020, ibm.com

U.S. Navy Chooses Yellowbrick, Sunsets IBM Netezza
22 March 2023, Business Wire

provided by Google News

Use Amazon Athena with Spark SQL for your open-source transactional table formats | Amazon Web Services
24 January 2024, AWS Blog

What is Apache Spark? The big data platform that crushed Hadoop
3 April 2024, InfoWorld

Cracking the Apache Spark Interview: 80+ Top Questions and Answers for 2024
1 April 2024, Simplilearn

Performant IPv4 Range Spark Joins | by Jean-Claude Cote
24 January 2024, Towards Data Science

Simba Technologies(R) Introduces New, Powerful JDBC Driver With SQL Connector for Apache Spark(TM)
17 March 2024, Yahoo Singapore News

provided by Google News

Evaluating HTAP Databases for Machine Learning Applications
2 November 2016, KDnuggets

HP Throws Trafodion Hat into OLTP Hadoop Ring
14 July 2014, Datanami

Low-latency, distributed database architectures are critical for emerging fog applications
7 April 2022, Embedded Computing Design

Apache Software Foundation Releases its 2019 Fiscal Year Report
17 August 2019, Open Source For You

provided by Google News



Share this page

Featured Products

Datastax Astra logo

Bring all your data to Generative AI applications with vector search enabled by the most scalable
vector database available.
Try for Free

Milvus logo

Vector database designed for GenAI, fully equipped for enterprise implementation.
Try Managed Milvus for Free

Neo4j logo

See for yourself how a graph database can make your life easier.
Use Neo4j online for free.

Present your product here