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DBMS > Netezza vs. Sadas Engine vs. Spark SQL vs. XTDB

System Properties Comparison Netezza vs. Sadas Engine vs. Spark SQL vs. XTDB

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Editorial information provided by DB-Engines
NameNetezza infoAlso called PureData System for Analytics by IBM  Xexclude from comparisonSadas Engine  Xexclude from comparisonSpark SQL  Xexclude from comparisonXTDB infoformerly named Crux  Xexclude from comparison
DescriptionData warehouse and analytics appliance part of IBM PureSystemsSADAS Engine is a columnar DBMS specifically designed for high performance in data warehouse environmentsSpark SQL is a component on top of 'Spark Core' for structured data processingA general purpose database with bitemporal SQL and Datalog and graph queries
Primary database modelRelational DBMSRelational DBMSRelational DBMSDocument store
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score10.18
Rank#46  Overall
#29  Relational DBMS
Score0.03
Rank#379  Overall
#156  Relational DBMS
Score19.15
Rank#33  Overall
#20  Relational DBMS
Score0.09
Rank#351  Overall
#47  Document stores
Websitewww.ibm.com/­products/­netezzawww.sadasengine.comspark.apache.org/­sqlgithub.com/­xtdb/­xtdb
www.xtdb.com
Technical documentationwww.sadasengine.com/­en/­sadas-engine-download-free-trial-and-documentation/­#documentationspark.apache.org/­docs/­latest/­sql-programming-guide.htmlwww.xtdb.com/­docs
DeveloperIBMSADAS s.r.l.Apache Software FoundationJuxt Ltd.
Initial release2000200620142019
Current release8.03.5.0 ( 2.13), September 20231.19, September 2021
License infoCommercial or Open Sourcecommercialcommercial infofree trial version availableOpen Source infoApache 2.0Open Source infoMIT License
Cloud-based only infoOnly available as a cloud servicenononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC++ScalaClojure
Server operating systemsLinux infoincluded in applianceAIX
Linux
Windows
Linux
OS X
Windows
All OS with a Java 8 (and higher) VM
Linux
Data schemeyesyesyesschema-free
Typing infopredefined data types such as float or dateyesyesyesyes, extensible-data-notation format
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 indexesyesyesnoyes
SQL infoSupport of SQLyesyesSQL-like DML and DDL statementslimited SQL, making use of Apache Calcite
APIs and other access methodsJDBC
ODBC
OLE DB
JDBC
ODBC
Proprietary protocol
JDBC
ODBC
HTTP REST
JDBC
Supported programming languagesC
C++
Fortran
Java
Lua
Perl
Python
R
.Net
C
C#
C++
Groovy
Java
PHP
Python
Java
Python
R
Scala
Clojure
Java
Server-side scripts infoStored proceduresyesnonono
Triggersnononono
Partitioning methods infoMethods for storing different data on different nodesShardinghorizontal partitioningyes, utilizing Spark Corenone
Replication methods infoMethods for redundantly storing data on multiple nodesSource-replica replicationnonenoneyes, each node contains all data
MapReduce infoOffers an API for user-defined Map/Reduce methodsyesnono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate Consistency
Foreign keys infoReferential integritynoyesnono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDnoACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyesyesyes, flexibel persistency by using storage technologies like Apache Kafka, RocksDB or LMDB
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yes infomanaged by 'Learn by Usage'no
User concepts infoAccess controlUsers with fine-grained authorization conceptAccess rights for users, groups and roles according to SQL-standardno

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More resources
Netezza infoAlso called PureData System for Analytics by IBMSadas EngineSpark SQLXTDB infoformerly named Crux
Recent citations in the news

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

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

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

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29 June 2020, Datanami

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23 December 2023, Towards Data Science

Run Apache Hive workloads using Spark SQL with Amazon EMR on EKS | Amazon Web Services
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