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DBMS > Netezza vs. SiteWhere vs. Spark SQL vs. STSdb vs. Vertica

System Properties Comparison Netezza vs. SiteWhere vs. Spark SQL vs. STSdb vs. Vertica

Editorial information provided by DB-Engines
NameNetezza infoAlso called PureData System for Analytics by IBM  Xexclude from comparisonSiteWhere  Xexclude from comparisonSpark SQL  Xexclude from comparisonSTSdb  Xexclude from comparisonVertica infoOpenText™ Vertica™  Xexclude from comparison
DescriptionData warehouse and analytics appliance part of IBM PureSystemsM2M integration platform for persisting/querying time series dataSpark SQL is a component on top of 'Spark Core' for structured data processingKey-Value Store with special method for indexing infooptimized for high performance using a special indexing methodCloud or off-cloud analytical database and query engine for structured and semi-structured streaming and batch data. Machine learning platform with built-in algorithms, data preparation capabilities, and model evaluation and management via SQL or Python.
Primary database modelRelational DBMSTime Series DBMSRelational DBMSKey-value storeRelational DBMS infoColumn oriented
Secondary database modelsSpatial DBMS
Time Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score9.06
Rank#46  Overall
#29  Relational DBMS
Score0.06
Rank#356  Overall
#35  Time Series DBMS
Score18.96
Rank#33  Overall
#20  Relational DBMS
Score0.04
Rank#360  Overall
#52  Key-value stores
Score10.68
Rank#43  Overall
#27  Relational DBMS
Websitewww.ibm.com/­products/­netezzagithub.com/­sitewhere/­sitewherespark.apache.org/­sqlgithub.com/­STSSoft/­STSdb4www.vertica.com
Technical documentationsitewhere1.sitewhere.io/­index.htmlspark.apache.org/­docs/­latest/­sql-programming-guide.htmlvertica.com/­documentation
DeveloperIBMSiteWhereApache Software FoundationSTS Soft SCOpenText infopreviously Micro Focus and Hewlett Packard
Initial release20002010201420112005
Current release3.5.0 ( 2.13), September 20234.0.8, September 201512.0.3, January 2023
License infoCommercial or Open SourcecommercialOpen Source infoCommon Public Attribution License Version 1.0Open Source infoApache 2.0Open Source infoGPLv2, commercial license availablecommercial infoLimited community edition free
Cloud-based only infoOnly available as a cloud servicenonononono infoon-premises, all major clouds - Amazon AWS, Microsoft Azure, Google Cloud Platform and containers
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaScalaC#C++
Server operating systemsLinux infoincluded in applianceLinux
OS X
Windows
Linux
OS X
Windows
WindowsLinux
Data schemeyespredefined schemeyesyesYes, but also semi-structure/unstructured data storage, and complex hierarchical data (like Parquet) stored and/or queried.
Typing infopredefined data types such as float or dateyesyesyesyes infoprimitive types and user defined types (classes)yes
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 indexesyesnononoNo Indexes Required. Different internal optimization strategy, but same functionality included.
SQL infoSupport of SQLyesnoSQL-like DML and DDL statementsnoFull 1999 standard plus machine learning, time series and geospatial. Over 650 functions.
APIs and other access methodsJDBC
ODBC
OLE DB
HTTP RESTJDBC
ODBC
.NET Client APIADO.NET
JDBC
Kafka Connector
ODBC
RESTful HTTP API
Spark Connector
vSQL infocharacter-based, interactive, front-end utility
Supported programming languagesC
C++
Fortran
Java
Lua
Perl
Python
R
Java
Python
R
Scala
C#
Java
C#
C++
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
R
Server-side scripts infoStored proceduresyesnonoyes, PostgreSQL PL/pgSQL, with minor differences
Triggersnononoyes, called Custom Alerts
Partitioning methods infoMethods for storing different data on different nodesShardingSharding infobased on HBaseyes, utilizing Spark Corenonehorizontal partitioning, hierarchical partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesSource-replica replicationselectable replication factor infobased on HBasenonenoneMulti-source replication infoOne, or more copies of data replicated across nodes, or object-store used for repository.
MapReduce infoOffers an API for user-defined Map/Reduce methodsyesnonono infoBi-directional Spark integration
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynonononoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDnononoACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentyesyesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.nonono
User concepts infoAccess controlUsers with fine-grained authorization conceptUsers with fine-grained authorization conceptnonofine grained access rights according to SQL-standard; supports Kerberos, LDAP, Ident and hash
More information provided by the system vendor
Netezza infoAlso called PureData System for Analytics by IBMSiteWhereSpark SQLSTSdbVertica infoOpenText™ Vertica™
Specific characteristicsDeploy-anywhere database for large-scale analytical deployments. Deploy off-cloud,...
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Competitive advantagesFast, scalable, and capable of high concurrency. Separation of compute/storage leverages...
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Typical application scenariosCommunication and network analytics, Embedded analytics, Fraud monitoring and Risk...
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Key customersAbiba Systems, Adform, adMarketplace, AmeriPride, Anritsu, AOL, Avito, Auckland Transport,...
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Licensing and pricing modelsCost-based models and subscription-based models are both available. One license is...
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More resources
Netezza infoAlso called PureData System for Analytics by IBMSiteWhereSpark SQLSTSdbVertica infoOpenText™ Vertica™
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