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DBMS > Netezza vs. RisingWave vs. SpaceTime vs. Vertica

System Properties Comparison Netezza vs. RisingWave vs. SpaceTime vs. Vertica

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Editorial information provided by DB-Engines
NameNetezza infoAlso called PureData System for Analytics by IBM  Xexclude from comparisonRisingWave  Xexclude from comparisonSpaceTime  Xexclude from comparisonVertica infoOpenText™ Vertica™  Xexclude from comparison
DescriptionData warehouse and analytics appliance part of IBM PureSystemsA distributed RDBMS for stream processing, wire-compatible with PostgreSQLSpaceTime is a spatio-temporal DBMS with a focus on performance.Cloud 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 DBMSRelational DBMSSpatial DBMSRelational DBMS infoColumn oriented
Secondary database modelsRelational DBMSSpatial DBMS
Time Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score7.56
Rank#48  Overall
#31  Relational DBMS
Score0.61
Rank#237  Overall
#111  Relational DBMS
Score0.00
Rank#385  Overall
#7  Spatial DBMS
Score9.62
Rank#42  Overall
#26  Relational DBMS
Websitewww.ibm.com/­products/­netezzawww.risingwave.com/­databasewww.mireo.com/­spacetimewww.vertica.com
Technical documentationdocs.risingwave.com/­docs/­current/­introvertica.com/­documentation
DeveloperIBMRisingWave LabsMireoOpenText infopreviously Micro Focus and Hewlett Packard
Initial release2000202220202005
Current release1.2, September 202312.0.3, January 2023
License infoCommercial or Open SourcecommercialOpen Source infoApache Version 2.0commercialcommercial infoLimited community edition free
Cloud-based only infoOnly available as a cloud servicenononono infoon-premises, all major clouds - Amazon AWS, Microsoft Azure, Google Cloud Platform and containers
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageRustC++C++
Server operating systemsLinux infoincluded in applianceDocker
Linux
macOS
LinuxLinux
Data schemeyesyesyesYes, 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 dateyesStandard SQL-types and JSONyesyes
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 indexesyesyesnoNo Indexes Required. Different internal optimization strategy, but same functionality included.
SQL infoSupport of SQLyesyesA subset of ANSI SQL is implementedFull 1999 standard plus machine learning, time series and geospatial. Over 650 functions.
APIs and other access methodsJDBC
ODBC
OLE DB
JDBC
PostgreSQL wire protocol
RESTful HTTP 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
Go
Java
JavaScript (Node.js)
Python
C#
C++
Python
C#
C++
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
R
Server-side scripts infoStored proceduresyesUDFs in Python or Javanoyes, PostgreSQL PL/pgSQL, with minor differences
Triggersnononoyes, called Custom Alerts
Partitioning methods infoMethods for storing different data on different nodesShardingFixed-grid hypercubeshorizontal partitioning, hierarchical partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesSource-replica replicationReal-time block device replication (DRBD)Multi-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 integritynononoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDnonoACID
Concurrency infoSupport for concurrent manipulation of datayesyesyes
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.yesnono
User concepts infoAccess controlUsers with fine-grained authorization conceptUsers and Rolesyesfine grained access rights according to SQL-standard; supports Kerberos, LDAP, Ident and hash

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More resources
Netezza infoAlso called PureData System for Analytics by IBMRisingWaveSpaceTimeVertica infoOpenText™ Vertica™
Recent citations in the news

Unify and share data across Netezza and watsonx.data for new generative AI applications
21 June 2024, IBM

How to migrate a large data warehouse from IBM Netezza to Amazon Redshift with no downtime
21 August 2019, AWS Blog

AWS and IBM Netezza come out in support of Iceberg in table format face-off
1 August 2023, The Register

Copy data from Netezza to Azure with Azure Data Factory
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18 October 2022, SiliconANGLE News

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Vertica on Kubernetes
20 June 2024, blogs.opentext.com

OpenText Analytics Database: The ELT Advantage
9 August 2024, blogs.opentext.com

MapR Hadoop Upgrade Spins YARN, Supports HP Vertica Analytics Platform
31 May 2024, Data Center Knowledge

Stonebraker Seeks to Invert the Computing Paradigm with DBOS
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What’s New in OpenText Vertica
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