DB-EnginesInfluxDB: Focus on building software with an easy-to-use serverless, scalable time series platformEnglish
Deutsch
Knowledge Base of Relational and NoSQL Database Management Systemsprovided by solid IT

DBMS > Kinetica vs. Spark SQL vs. Teradata

System Properties Comparison Kinetica vs. Spark SQL vs. Teradata

Please select another system to include it in the comparison.

Editorial information provided by DB-Engines
NameKinetica  Xexclude from comparisonSpark SQL  Xexclude from comparisonTeradata  Xexclude from comparison
DescriptionFully vectorized database across both GPUs and CPUsSpark SQL is a component on top of 'Spark Core' for structured data processingA hybrid cloud data analytics software platform (Teradata Vantage)
Primary database modelRelational DBMSRelational DBMSRelational DBMS
Secondary database modelsSpatial DBMS
Time Series DBMS
Document store
Graph DBMS
Spatial DBMS
Time Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.69
Rank#234  Overall
#107  Relational DBMS
Score19.15
Rank#33  Overall
#20  Relational DBMS
Score47.84
Rank#21  Overall
#15  Relational DBMS
Websitewww.kinetica.comspark.apache.org/­sqlwww.teradata.com
Technical documentationdocs.kinetica.comspark.apache.org/­docs/­latest/­sql-programming-guide.htmldocs.teradata.com
DeveloperKineticaApache Software FoundationTeradata
Initial release201220141984
Current release7.1, August 20213.5.0 ( 2.13), September 2023Teradata Vantage 1.0 MU2, January 2019
License infoCommercial or Open SourcecommercialOpen Source infoApache 2.0commercial
Cloud-based only infoOnly available as a cloud servicenonono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageC, C++Scala
Server operating systemsLinuxLinux
OS X
Windows
hosted
Linux
Data schemeyesyesyes
Typing infopredefined data types such as float or dateyesyesyes
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.nonoyes
Secondary indexesyesnoyes infoJoin-index to prejoin tables, aggregate index, sparse index, hash index
SQL infoSupport of SQLSQL-like DML and DDL statementsSQL-like DML and DDL statementsyes infoSQL 2016 + extensions
APIs and other access methodsJDBC
ODBC
RESTful HTTP API
JDBC
ODBC
.NET Client API
HTTP REST
JDBC
JMS Adapter
ODBC
OLE DB
Supported programming languagesC++
Java
JavaScript (Node.js)
Python
Java
Python
R
Scala
C
C++
Cobol
Java (JDBC-ODBC)
Perl
PL/1
Python
R
Ruby
Server-side scripts infoStored proceduresuser defined functionsnoyes infoUDFs, stored procedures, table functions in parallel
Triggersyes infotriggers when inserted values for one or more columns fall within a specified rangenoyes
Partitioning methods infoMethods for storing different data on different nodesShardingyes, utilizing Spark CoreSharding infoHashing
Replication methods infoMethods for redundantly storing data on multiple nodesSource-replica replicationnoneMulti-source replication
Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate Consistency or Eventual Consistency depending on configurationImmediate Consistency
Foreign keys infoReferential integrityyesnoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanonoACID
Concurrency infoSupport for concurrent manipulation of datayesyesyes
Durability infoSupport for making data persistentyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yes infoGPU vRAM or System RAMnoyes
User concepts infoAccess controlAccess rights for users and roles on table levelnofine grained access rights according to SQL-standard

More information provided by the system vendor

We invite representatives of system vendors to contact us for updating and extending the system information,
and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.

Related products and services

We invite representatives of vendors of related products to contact us for presenting information about their offerings here.

More resources
KineticaSpark SQLTeradata
DB-Engines blog posts

Teradata is the most popular data warehouse DBMS
2 April 2013, Paul Andlinger

show all

Recent citations in the news

Kinetica Delivers Real-Time Vector Similarity Search
21 March 2024, insideBIGDATA

Kinetica Elevates RAG with Fast Access to Real-Time Data
26 March 2024, Datanami

Kinetica ramps up RAG for generative AI, empowering enterprises with real-time operational data
18 March 2024, SiliconANGLE News

Kinetica Launches Generative AI Solution for Real-Time Inferencing Powered by NVIDIA AI Enterprise
18 March 2024, GlobeNewswire

Transforming spatiotemporal data analysis with GPUs and generative AI
30 October 2023, InfoWorld

provided by Google News

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

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

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

Cloudera: Impala's it for interactive SQL on Hadoop; everything else will move to Spark
11 April 2024, Yahoo Movies Canada

1.5 Years of Spark Knowledge in 8 Tips | by Michael Berk
23 December 2023, Towards Data Science

provided by Google News

Connecting Teradata Vantage to Amazon Athena | AWS Partner Network (APN) Blog
23 April 2024, AWS Blog

An interview with Teradata CFO Claire Bramley
9 February 2024, McKinsey

Teradata's stock tumbles on flat revenue and soft guidance
12 February 2024, SiliconANGLE News

Teradata Appoints Richard Petley as Chief Revenue Officer
5 April 2024, Business Wire

Louisiana State Employees Retirement System Purchases New Shares in Teradata Co. (NYSE:TDC)
23 April 2024, MarketBeat

provided by Google News



Share this page

Featured Products

Neo4j logo

See for yourself how a graph database can make your life easier.
Use Neo4j online for free.

Datastax Astra logo

Bring all your data to Generative AI applications with vector search enabled by the most scalable
vector database available.
Try for Free

SingleStore logo

The database to transact, analyze and contextualize your data in real time.
Try it today.

Milvus logo

Vector database designed for GenAI, fully equipped for enterprise implementation.
Try Managed Milvus for Free

Ontotext logo

GraphDB allows you to link diverse data, index it for semantic search and enrich it via text analysis to build big knowledge graphs. Get it free.

Present your product here