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DBMS > Netezza vs. SiriDB vs. SpaceTime vs. Spark SQL vs. TimescaleDB

System Properties Comparison Netezza vs. SiriDB vs. SpaceTime vs. Spark SQL vs. TimescaleDB

Editorial information provided by DB-Engines
NameNetezza infoAlso called PureData System for Analytics by IBM  Xexclude from comparisonSiriDB  Xexclude from comparisonSpaceTime  Xexclude from comparisonSpark SQL  Xexclude from comparisonTimescaleDB  Xexclude from comparison
DescriptionData warehouse and analytics appliance part of IBM PureSystemsOpen Source Time Series DBMSSpaceTime is a spatio-temporal DBMS with a focus on performance.Spark SQL is a component on top of 'Spark Core' for structured data processingA time series DBMS optimized for fast ingest and complex queries, based on PostgreSQL
Primary database modelRelational DBMSTime Series DBMSSpatial DBMSRelational DBMSTime Series DBMS
Secondary database modelsRelational DBMSRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score9.06
Rank#46  Overall
#29  Relational DBMS
Score0.00
Rank#383  Overall
#41  Time Series DBMS
Score0.00
Rank#383  Overall
#7  Spatial DBMS
Score18.96
Rank#33  Overall
#20  Relational DBMS
Score4.64
Rank#71  Overall
#4  Time Series DBMS
Websitewww.ibm.com/­products/­netezzasiridb.comwww.mireo.com/­spacetimespark.apache.org/­sqlwww.timescale.com
Technical documentationdocs.siridb.comspark.apache.org/­docs/­latest/­sql-programming-guide.htmldocs.timescale.com
DeveloperIBMCesbitMireoApache Software FoundationTimescale
Initial release20002017202020142017
Current release3.5.0 ( 2.13), September 20232.15.0, May 2024
License infoCommercial or Open SourcecommercialOpen Source infoMIT LicensecommercialOpen Source infoApache 2.0Open Source infoApache 2.0
Cloud-based only infoOnly available as a cloud servicenonononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageCC++ScalaC
Server operating systemsLinux infoincluded in applianceLinuxLinuxLinux
OS X
Windows
Linux
OS X
Windows
Data schemeyesyesyesyesyes
Typing infopredefined data types such as float or dateyesyes infoNumeric datayesyesnumerics, strings, booleans, arrays, JSON blobs, geospatial dimensions, currencies, binary data, other complex data types
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.nononoyes
Secondary indexesyesyesnonoyes
SQL infoSupport of SQLyesnoA subset of ANSI SQL is implementedSQL-like DML and DDL statementsyes infofull PostgreSQL SQL syntax
APIs and other access methodsJDBC
ODBC
OLE DB
HTTP APIRESTful HTTP APIJDBC
ODBC
ADO.NET
JDBC
native C library
ODBC
streaming API for large objects
Supported programming languagesC
C++
Fortran
Java
Lua
Perl
Python
R
C
C++
Go
Java
JavaScript (Node.js)
PHP
Python
R
C#
C++
Python
Java
Python
R
Scala
.Net
C
C++
Delphi
Java infoJDBC
JavaScript
Perl
PHP
Python
R
Ruby
Scheme
Tcl
Server-side scripts infoStored proceduresyesnononouser defined functions, PL/pgSQL, PL/Tcl, PL/Perl, PL/Python, PL/Java, PL/PHP, PL/R, PL/Ruby, PL/Scheme, PL/Unix shell
Triggersnonononoyes
Partitioning methods infoMethods for storing different data on different nodesShardingShardingFixed-grid hypercubesyes, utilizing Spark Coreyes, across time and space (hash partitioning) attributes
Replication methods infoMethods for redundantly storing data on multiple nodesSource-replica replicationyesReal-time block device replication (DRBD)noneSource-replica replication with hot standby and reads on replicas info
MapReduce infoOffers an API for user-defined Map/Reduce methodsyesnonono
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.yesnonono
User concepts infoAccess controlUsers with fine-grained authorization conceptsimple rights management via user accountsyesnofine grained access rights according to SQL-standard

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More resources
Netezza infoAlso called PureData System for Analytics by IBMSiriDBSpaceTimeSpark SQLTimescaleDB
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

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

Netezza Performance Server
12 August 2020, IBM

provided by Google News

Use Amazon Athena with Spark SQL for your open-source transactional table formats | Amazon Web Services
24 January 2024, AWS Blog

What is Apache Spark? The big data platform that crushed Hadoop
3 April 2024, InfoWorld

Cracking the Apache Spark Interview: 80+ Top Questions and Answers for 2024
1 April 2024, Simplilearn

Performant IPv4 Range Spark Joins | by Jean-Claude Cote
24 January 2024, Towards Data Science

18 Top Big Data Tools and Technologies to Know About in 2024
24 January 2024, TechTarget

provided by Google News

TimescaleDB Is a Vector Database Now, Too
25 September 2023, Datanami

Timescale Acquires PopSQL to Bring a Modern, Collaborative SQL GUI to PostgreSQL Developers
4 April 2024, PR Newswire

Power IoT and time-series workloads with TimescaleDB for Azure Database for PostgreSQL
18 March 2019, Microsoft

Timescale Valuation Rockets to Over $1B with $110M Round, Marking the Explosive Rise of Time-Series Data
22 February 2022, Business Wire

TimescaleDB goes distributed; implements ‘Chunking’ over ‘Sharding’ for scaling-out
22 August 2019, Packt Hub

provided by Google News



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