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DBMS > Netezza vs. Spark SQL vs. Splunk vs. SurrealDB

System Properties Comparison Netezza vs. Spark SQL vs. Splunk vs. SurrealDB

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Editorial information provided by DB-Engines
NameNetezza infoAlso called PureData System for Analytics by IBM  Xexclude from comparisonSpark SQL  Xexclude from comparisonSplunk  Xexclude from comparisonSurrealDB  Xexclude from comparison
DescriptionData warehouse and analytics appliance part of IBM PureSystemsSpark SQL is a component on top of 'Spark Core' for structured data processingAnalytics Platform for Big DataA fully ACID transactional, developer-friendly, multi-model DBMS
Primary database modelRelational DBMSRelational DBMSSearch engineDocument store
Graph DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score9.06
Rank#46  Overall
#29  Relational DBMS
Score18.96
Rank#33  Overall
#20  Relational DBMS
Score86.45
Rank#14  Overall
#2  Search engines
Score0.86
Rank#203  Overall
#34  Document stores
#18  Graph DBMS
Websitewww.ibm.com/­products/­netezzaspark.apache.org/­sqlwww.splunk.comsurrealdb.com
Technical documentationspark.apache.org/­docs/­latest/­sql-programming-guide.htmldocs.splunk.com/­Documentation/­Splunksurrealdb.com/­docs
DeveloperIBMApache Software FoundationSplunk Inc.SurrealDB Ltd
Initial release2000201420032022
Current release3.5.0 ( 2.13), September 2023v1.5.0, May 2024
License infoCommercial or Open SourcecommercialOpen Source infoApache 2.0commercial infoLimited free edition and free developer edition availableOpen Source
Cloud-based only infoOnly available as a cloud servicenononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageScalaRust
Server operating systemsLinux infoincluded in applianceLinux
OS X
Windows
Linux
OS X
Solaris
Windows
Linux
macOS
Windows
Data schemeyesyesyesschema-free
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 indexesyesnoyes
SQL infoSupport of SQLyesSQL-like DML and DDL statementsno infoSplunk Search Processing Language for search commandsSQL-like query language
APIs and other access methodsJDBC
ODBC
OLE DB
JDBC
ODBC
HTTP RESTGraphQL
RESTful HTTP API
WebSocket
Supported programming languagesC
C++
Fortran
Java
Lua
Perl
Python
R
Java
Python
R
Scala
C#
Java
JavaScript
PHP
Python
Ruby
Deno
Go
JavaScript (Node.js)
Rust
Server-side scripts infoStored proceduresyesnoyes
Triggersnonoyes
Partitioning methods infoMethods for storing different data on different nodesShardingyes, utilizing Spark CoreSharding
Replication methods infoMethods for redundantly storing data on multiple nodesSource-replica replicationnoneMulti-source replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsyesyesno
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual Consistency
Foreign keys infoReferential integritynonono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDnono infoA 'Transaction' in Splunk has a different meaning: grouping related events into a single one for later searchingACID
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.nono
User concepts infoAccess controlUsers with fine-grained authorization conceptnoAccess rights for users and rolesyes, based on authentication and database rules

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More resources
Netezza infoAlso called PureData System for Analytics by IBMSpark SQLSplunkSurrealDB
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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
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Migrating your Netezza data warehouse to Amazon Redshift | Amazon Web Services
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