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DBMS > JaguarDB vs. Netezza vs. Snowflake vs. Splice Machine

System Properties Comparison JaguarDB vs. Netezza vs. Snowflake vs. Splice Machine

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Editorial information provided by DB-Engines
NameJaguarDB  Xexclude from comparisonNetezza infoAlso called PureData System for Analytics by IBM  Xexclude from comparisonSnowflake  Xexclude from comparisonSplice Machine  Xexclude from comparison
DescriptionPerformant, highly scalable DBMS for AI and IoT applicationsData 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 modelKey-value store
Vector DBMS
Relational DBMSRelational DBMSRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.00
Rank#383  Overall
#60  Key-value stores
#13  Vector DBMS
Score9.06
Rank#46  Overall
#29  Relational DBMS
Score121.33
Rank#9  Overall
#6  Relational DBMS
Score0.54
Rank#250  Overall
#114  Relational DBMS
Websitewww.jaguardb.comwww.ibm.com/­products/­netezzawww.snowflake.comsplicemachine.com
Technical documentationwww.jaguardb.com/­support.htmldocs.snowflake.net/­manuals/­index.htmlsplicemachine.com/­how-it-works
DeveloperDataJaguar, Inc.IBMSnowflake Computing Inc.Splice Machine
Initial release2015200020142014
Current release3.3 July 20233.1, March 2021
License infoCommercial or Open SourceOpen Source infoGPL V3.0commercialcommercialOpen Source infoAGPL 3.0, commercial license available
Cloud-based only infoOnly available as a cloud servicenonoyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC++ infothe server part. Clients available in other languagesJava
Server operating systemsLinuxLinux 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 indexesyesyesyes
SQL infoSupport of SQLA subset of ANSI SQL is implemented infobut no views, foreign keys, triggersyesyesyes
APIs and other access methodsJDBC
ODBC
JDBC
ODBC
OLE DB
CLI Client
JDBC
ODBC
JDBC
Native Spark Datasource
ODBC
Supported programming languagesC
C++
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
Scala
C
C++
Fortran
Java
Lua
Perl
Python
R
JavaScript (Node.js)
Python
C#
C++
Java
JavaScript (Node.js)
Python
R
Scala
Server-side scripts infoStored proceduresnoyesuser 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 nodesMulti-source replicationSource-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 systemEventual ConsistencyImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynonoyesyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDACIDACID
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.nonoyes
User concepts infoAccess controlrights management via user accountsUsers 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
JaguarDBNetezza infoAlso called PureData System for Analytics by IBMSnowflakeSplice Machine
DB-Engines blog posts

Snowflake is the DBMS of the Year 2022, defending the title from last year
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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

IBM Brings Back a Netezza, Attacks Yellowbrick
29 June 2020, Datanami

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8 May 2024, Business Wire

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17 April 2024, AWS Blog

Infosys at Snowflake Data Cloud Summit 2024
3 May 2024, Infosys

Snowflake Data Clean Rooms Democratize Secure Data Sharing Across Clouds
24 April 2024, Acceleration Economy

Coalesce raises more cash to transform data for Snowflake customers
4 April 2024, TechCrunch

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Machine learning data pipeline outfit Splice Machine files for insolvency
26 August 2021, The Register

Splice Machine Launches the Splice Machine Feature Store to Simplify Feature Engineering and Democratize Machine ...
19 January 2021, PR Newswire

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

Distributed SQL System Review: Snowflake vs Splice Machine
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