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DBMS > Amazon Redshift vs. Netezza vs. Snowflake vs. Splice Machine

System Properties Comparison Amazon Redshift vs. Netezza vs. Snowflake vs. Splice Machine

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Editorial information provided by DB-Engines
NameAmazon Redshift  Xexclude from comparisonNetezza infoAlso called PureData System for Analytics by IBM  Xexclude from comparisonSnowflake  Xexclude from comparisonSplice Machine  Xexclude from comparison
DescriptionLarge scale data warehouse service for use with business intelligence toolsData warehouse and analytics appliance part of IBM PureSystemsCloud-based data warehousing service for structured and semi-structured dataOpen-Source SQL RDBMS for Operational and Analytical use cases with native Machine Learning, powered by Hadoop and Spark
Primary database modelRelational DBMSRelational DBMSRelational DBMSRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score16.88
Rank#35  Overall
#22  Relational DBMS
Score8.59
Rank#45  Overall
#29  Relational DBMS
Score130.36
Rank#8  Overall
#5  Relational DBMS
Score0.54
Rank#252  Overall
#115  Relational DBMS
Websiteaws.amazon.com/­redshiftwww.ibm.com/­products/­netezzawww.snowflake.comsplicemachine.com
Technical documentationdocs.aws.amazon.com/­redshiftdocs.snowflake.net/­manuals/­index.htmlsplicemachine.com/­how-it-works
DeveloperAmazon (based on PostgreSQL)IBMSnowflake Computing Inc.Splice Machine
Initial release2012200020142014
Current release3.1, March 2021
License infoCommercial or Open SourcecommercialcommercialcommercialOpen Source infoAGPL 3.0, commercial license available
Cloud-based only infoOnly available as a cloud serviceyesnoyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageCJava
Server operating systemshostedLinux infoincluded in appliancehostedLinux
OS X
Solaris
Windows
Data schemeyesyesyes infosupport of semi-structured data formats (JSON, XML, Avro)yes
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.noyes
Secondary indexesrestrictedyesyes
SQL infoSupport of SQLyes infodoes not fully support an SQL-standardyesyesyes
APIs and other access methodsJDBC
ODBC
JDBC
ODBC
OLE DB
CLI Client
JDBC
ODBC
JDBC
Native Spark Datasource
ODBC
Supported programming languagesAll languages supporting JDBC/ODBCC
C++
Fortran
Java
Lua
Perl
Python
R
JavaScript (Node.js)
Python
C#
C++
Java
JavaScript (Node.js)
Python
R
Scala
Server-side scripts infoStored proceduresuser defined functions infoin Pythonyesuser defined functionsyes infoJava
Triggersnonono infosimilar concept for controling cloud resourcesyes
Partitioning methods infoMethods for storing different data on different nodesShardingShardingyesShared Nothhing Auto-Sharding, Columnar Partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesyesSource-replica replicationyesMulti-source replication
Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyesnoYes, via Full Spark Integration
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integrityyes infoinformational only, not enforced by the systemnoyesyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACIDACIDACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes, multi-version concurrency control (MVCC)
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.yesnoyes
User concepts infoAccess controlfine grained access rights according to SQL-standardUsers with fine-grained authorization conceptUsers with fine-grained authorization concept, user roles and pluggable authenticationAccess rights for users, groups and roles according to SQL-standard

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More resources
Amazon RedshiftNetezza infoAlso called PureData System for Analytics by IBMSnowflakeSplice Machine
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Recent citations in the news

Amazon Redshift Serverless is now generally available in the AWS China (Ningxia) Region
28 May 2024, AWS Blog

AWS analytics services streamline user access to data, permissions setting, and auditing | Amazon Web Services
29 May 2024, AWS Blog

Amazon Redshift adds new AI capabilities, including Amazon Q, to boost efficiency and productivity | Amazon Web ...
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Amazon Redshift now supports multi-data warehouse writes through data sharing (preview)
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provided by Google News

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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

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22 March 2023, Business Wire

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Threat actor compromising Snowflake database customers
31 May 2024, TechTarget

The Ticketmaster Data Breach May Be Just the Beginning
1 June 2024, WIRED

Massive Ticketmaster, Santander data breaches linked to Snowflake cloud storage
31 May 2024, The Verge

Snowflake denies breach, blames data theft on poorly secured customer accounts
1 June 2024, Help Net Security

Snowflake denies miscreants melted its security to steal data from top customers
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Machine learning data pipeline outfit Splice Machine files for insolvency
26 August 2021, The Register

Splice Machine Launches Feature Store to Simplify Feature Engineering
19 January 2021, Datanami

New Splice Machine RDBMS unites OLTP and OLAP
18 November 2015, CIO

Big Data News: Splice Machine, Carpathia, Altiscale, DataGravity
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