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DBMS > Amazon Redshift vs. FoundationDB vs. Spark SQL vs. TDengine vs. WakandaDB

System Properties Comparison Amazon Redshift vs. FoundationDB vs. Spark SQL vs. TDengine vs. WakandaDB

Editorial information provided by DB-Engines
NameAmazon Redshift  Xexclude from comparisonFoundationDB  Xexclude from comparisonSpark SQL  Xexclude from comparisonTDengine  Xexclude from comparisonWakandaDB  Xexclude from comparison
Created as commercial project in 2013, FoundationDB has been acquired by Apple in March 2015 and was withdrawn from the market. As a consequence, the product was removed from the DB-Engines ranking. In April 2018, Apple open-sourced FoundationDB and it therefore reappears in the ranking.
DescriptionLarge scale data warehouse service for use with business intelligence toolsOrdered key-value store. Core features are complimented by layers.Spark SQL is a component on top of 'Spark Core' for structured data processingTime Series DBMS and big data platformWakandaDB is embedded in a server that provides a REST API and a server-side javascript engine to access data
Primary database modelRelational DBMSDocument store infosupported via specific layer
Key-value store
Relational DBMS infosupported via specific SQL-layer
Relational DBMSTime Series DBMSObject oriented DBMS
Secondary database modelsRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score17.94
Rank#34  Overall
#21  Relational DBMS
Score1.03
Rank#190  Overall
#31  Document stores
#28  Key-value stores
#89  Relational DBMS
Score18.96
Rank#33  Overall
#20  Relational DBMS
Score2.60
Rank#107  Overall
#8  Time Series DBMS
Score0.03
Rank#364  Overall
#17  Object oriented DBMS
Websiteaws.amazon.com/­redshiftgithub.com/­apple/­foundationdbspark.apache.org/­sqlgithub.com/­taosdata/­TDengine
tdengine.com
wakanda.github.io
Technical documentationdocs.aws.amazon.com/­redshiftapple.github.io/­foundationdbspark.apache.org/­docs/­latest/­sql-programming-guide.htmldocs.tdengine.comwakanda.github.io/­doc
DeveloperAmazon (based on PostgreSQL)FoundationDBApache Software FoundationTDEngine, previously Taos DataWakanda SAS
Initial release20122013201420192012
Current release6.2.28, November 20203.5.0 ( 2.13), September 20233.0, August 20222.7.0 (April 29, 2019), April 2019
License infoCommercial or Open SourcecommercialOpen Source infoApache 2.0Open Source infoApache 2.0Open Source infoAGPL V3, also commercial editions availableOpen Source infoAGPLv3, extended commercial license available
Cloud-based only infoOnly available as a cloud serviceyesnononono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageCC++ScalaCC++, JavaScript
Server operating systemshostedLinux
OS X
Windows
Linux
OS X
Windows
Linux
Windows
Linux
OS X
Windows
Data schemeyesschema-free infosome layers support schemasyesyesyes
Typing infopredefined data types such as float or dateyesno infosome layers support typingyesyesyes
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.nononono
Secondary indexesrestrictednonono
SQL infoSupport of SQLyes infodoes not fully support an SQL-standardsupported in specific SQL layer onlySQL-like DML and DDL statementsStandard SQL with extensions for time-series applicationsno
APIs and other access methodsJDBC
ODBC
JDBC
ODBC
JDBC
RESTful HTTP API
RESTful HTTP API
Supported programming languagesAll languages supporting JDBC/ODBC.Net
C
C++
Go
Java
JavaScript infoNode.js
PHP
Python
Ruby
Swift
Java
Python
R
Scala
C
C#
C++
Go
Java
JavaScript (Node.js)
PHP
Python
Rust
JavaScript
Server-side scripts infoStored proceduresuser defined functions infoin Pythonin SQL-layer onlynonoyes
Triggersnononoyes, via alarm monitoringyes
Partitioning methods infoMethods for storing different data on different nodesShardingShardingyes, utilizing Spark CoreShardingnone
Replication methods infoMethods for redundantly storing data on multiple nodesyesyesnoneyesnone
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyLinearizable consistencyImmediate Consistency
Foreign keys infoReferential integrityyes infoinformational only, not enforced by the systemin SQL-layer onlynono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACIDnoACID
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.yesnono
User concepts infoAccess controlfine grained access rights according to SQL-standardnonoyesyes
More information provided by the system vendor
Amazon RedshiftFoundationDBSpark SQLTDengineWakandaDB
Specific characteristicsTDengine™ is a next generation data historian purpose-built for Industry 4.0 and...
» more
Competitive advantagesHigh Performance at any Scale: TDengine is purpose-built for handling massive industrial...
» more
Typical application scenariosTDengine is designed for Industrial IoT scenarios, including: Manufacturing Connected...
» more
Market metricsTDengine has garnered over 22,500 stars on GitHub and is used in over 50 countries...
» more
Licensing and pricing modelsTDengine OSS is an open source, cloud native time series database. It includes built-in...
» more
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More resources
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