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DBMS > Amazon Redshift vs. Kinetica vs. Spark SQL vs. TDengine

System Properties Comparison Amazon Redshift vs. Kinetica vs. Spark SQL vs. TDengine

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Editorial information provided by DB-Engines
NameAmazon Redshift  Xexclude from comparisonKinetica  Xexclude from comparisonSpark SQL  Xexclude from comparisonTDengine  Xexclude from comparison
DescriptionLarge scale data warehouse service for use with business intelligence toolsFully vectorized database across both GPUs and CPUsSpark SQL is a component on top of 'Spark Core' for structured data processingTime Series DBMS and big data platform
Primary database modelRelational DBMSRelational DBMSRelational DBMSTime Series DBMS
Secondary database modelsSpatial DBMS
Time Series DBMS
Relational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score19.03
Rank#34  Overall
#21  Relational DBMS
Score0.69
Rank#234  Overall
#107  Relational DBMS
Score19.15
Rank#33  Overall
#20  Relational DBMS
Score2.68
Rank#109  Overall
#8  Time Series DBMS
Websiteaws.amazon.com/­redshiftwww.kinetica.comspark.apache.org/­sqlgithub.com/­taosdata/­TDengine
tdengine.com
Technical documentationdocs.aws.amazon.com/­redshiftdocs.kinetica.comspark.apache.org/­docs/­latest/­sql-programming-guide.htmldocs.tdengine.com
DeveloperAmazon (based on PostgreSQL)KineticaApache Software FoundationTDEngine, previously Taos Data
Initial release2012201220142019
Current release7.1, August 20213.5.0 ( 2.13), September 20233.0, August 2022
License infoCommercial or Open SourcecommercialcommercialOpen Source infoApache 2.0Open Source infoGPL V3, also commercial editions available
Cloud-based only infoOnly available as a cloud serviceyesnonono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageCC, C++ScalaC
Server operating systemshostedLinuxLinux
OS X
Windows
Linux
Windows
Data schemeyesyesyesyes
Typing infopredefined data types such as float or dateyesyesyesyes
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 indexesrestrictedyesnono
SQL infoSupport of SQLyes infodoes not fully support an SQL-standardSQL-like DML and DDL statementsSQL-like DML and DDL statementsStandard SQL with extensions for time-series applications
APIs and other access methodsJDBC
ODBC
JDBC
ODBC
RESTful HTTP API
JDBC
ODBC
JDBC
RESTful HTTP API
Supported programming languagesAll languages supporting JDBC/ODBCC++
Java
JavaScript (Node.js)
Python
Java
Python
R
Scala
C
C#
C++
Go
Java
JavaScript (Node.js)
PHP
Python
Rust
Server-side scripts infoStored proceduresuser defined functions infoin Pythonuser defined functionsnono
Triggersnoyes infotriggers when inserted values for one or more columns fall within a specified rangenoyes, via alarm monitoring
Partitioning methods infoMethods for storing different data on different nodesShardingShardingyes, utilizing Spark CoreSharding
Replication methods infoMethods for redundantly storing data on multiple nodesyesSource-replica replicationnoneyes
MapReduce infoOffers an API for user-defined Map/Reduce methodsnono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate Consistency or Eventual Consistency depending on configuration
Foreign keys infoReferential integrityyes infoinformational only, not enforced by the systemyesnono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDnono
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
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.yesyes infoGPU vRAM or System RAMno
User concepts infoAccess controlfine grained access rights according to SQL-standardAccess rights for users and roles on table levelnoyes
More information provided by the system vendor
Amazon RedshiftKineticaSpark SQLTDengine
Specific characteristicsTDengineā„¢ 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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