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DBMS > Alibaba Cloud TSDB vs. DuckDB vs. Netezza vs. TimescaleDB vs. Yanza

System Properties Comparison Alibaba Cloud TSDB vs. DuckDB vs. Netezza vs. TimescaleDB vs. Yanza

Editorial information provided by DB-Engines
NameAlibaba Cloud TSDB  Xexclude from comparisonDuckDB  Xexclude from comparisonNetezza infoAlso called PureData System for Analytics by IBM  Xexclude from comparisonTimescaleDB  Xexclude from comparisonYanza  Xexclude from comparison
Yanza seems to be discontinued. Therefore it is excluded from the DB-Engines Ranking.
DescriptionA stable, reliable, and cost-effective online high-performance time series database serviceAn embeddable, in-process, column-oriented SQL OLAP RDBMSData warehouse and analytics appliance part of IBM PureSystemsA time series DBMS optimized for fast ingest and complex queries, based on PostgreSQLTime Series DBMS for IoT Applications
Primary database modelTime Series DBMSRelational DBMSRelational DBMSTime Series DBMSTime Series DBMS
Secondary database modelsRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.29
Rank#301  Overall
#26  Time Series DBMS
Score4.63
Rank#69  Overall
#37  Relational DBMS
Score8.59
Rank#45  Overall
#29  Relational DBMS
Score4.46
Rank#71  Overall
#5  Time Series DBMS
Websitewww.alibabacloud.com/­product/­hitsdbduckdb.orgwww.ibm.com/­products/­netezzawww.timescale.comyanza.com
Technical documentationwww.alibabacloud.com/­help/­en/­time-series-database/­latest/­what-is-tsdbduckdb.org/­docsdocs.timescale.com
DeveloperAlibabaIBMTimescaleYanza
Initial release2018200020172015
Current release0.10, February 20242.15.0, May 2024
License infoCommercial or Open SourcecommercialOpen Source infoMIT LicensecommercialOpen Source infoApache 2.0commercial infofree version available
Cloud-based only infoOnly available as a cloud serviceyesnononono infobut mainly used as a service provided by Yanza
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageC++C
Server operating systemshostedserver-lessLinux infoincluded in applianceLinux
OS X
Windows
Windows
Data schemeschema-freeyesyesyesschema-free
Typing infopredefined data types such as float or dateNumeric data and Stringsyesyesnumerics, strings, booleans, arrays, JSON blobs, geospatial dimensions, currencies, binary data, other complex data typesno
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.nonoyesno
Secondary indexesnoyesyesyesno
SQL infoSupport of SQLnoyesyesyes infofull PostgreSQL SQL syntaxno
APIs and other access methodsHTTP RESTArrow Database Connectivity (ADBC)
CLI Client
JDBC
ODBC
JDBC
ODBC
OLE DB
ADO.NET
JDBC
native C library
ODBC
streaming API for large objects
HTTP API
Supported programming languagesJavaC
C# info3rd party driver
C++
Crystal info3rd party driver
Go info3rd party driver
Java
Lisp info3rd party driver
Python
R
Ruby info3rd party driver
Rust
Swift
Zig info3rd party driver
C
C++
Fortran
Java
Lua
Perl
Python
R
.Net
C
C++
Delphi
Java infoJDBC
JavaScript
Perl
PHP
Python
R
Ruby
Scheme
Tcl
any language that supports HTTP calls
Server-side scripts infoStored proceduresnonoyesuser defined functions, PL/pgSQL, PL/Tcl, PL/Perl, PL/Python, PL/Java, PL/PHP, PL/R, PL/Ruby, PL/Scheme, PL/Unix shellno
Triggersnononoyesyes infoTimer and event based
Partitioning methods infoMethods for storing different data on different nodesnoneShardingyes, across time and space (hash partitioning) attributesnone
Replication methods infoMethods for redundantly storing data on multiple nodesnoneSource-replica replicationSource-replica replication with hot standby and reads on replicas infonone
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonoyesnono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynononoyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDACIDACIDno
Concurrency infoSupport for concurrent manipulation of datayesyes, multi-version concurrency control (MVCC)yesyesyes
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.noyesno
User concepts infoAccess controlAccess managed on TSDB instance levelnoUsers with fine-grained authorization conceptfine grained access rights according to SQL-standardno

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More resources
Alibaba Cloud TSDBDuckDBNetezza infoAlso called PureData System for Analytics by IBMTimescaleDBYanza
Recent citations in the news

DuckDB: In-Process Python Analytics for Not-Quite-Big Data
31 May 2024, The New Stack

My First Billion (of Rows) in DuckDB | by João Pedro | May, 2024
1 May 2024, Towards Data Science

DuckDB Walks to the Beat of Its Own Analytics Drum
5 March 2024, Datanami

DuckDB: The tiny but powerful analytics database
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MotherDuck launches its DuckDB-based cloud analytics platform
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IBM announces availability of the high-performance, cloud-native Netezza Performance Server as a Service on AWS
11 July 2023, ibm.com

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

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, businesswire.com

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

provided by Google News



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