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DBMS > Spark SQL vs. Teradata vs. TimescaleDB

System Properties Comparison Spark SQL vs. Teradata vs. TimescaleDB

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Editorial information provided by DB-Engines
NameSpark SQL  Xexclude from comparisonTeradata  Xexclude from comparisonTimescaleDB  Xexclude from comparison
DescriptionSpark SQL is a component on top of 'Spark Core' for structured data processingA hybrid cloud data analytics software platform (Teradata Vantage)A time series DBMS optimized for fast ingest and complex queries, based on PostgreSQL
Primary database modelRelational DBMSRelational DBMSTime Series DBMS
Secondary database modelsDocument store
Graph DBMS
Spatial DBMS
Time Series DBMS
Relational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score18.96
Rank#33  Overall
#20  Relational DBMS
Score45.33
Rank#21  Overall
#15  Relational DBMS
Score4.64
Rank#71  Overall
#4  Time Series DBMS
Websitespark.apache.org/­sqlwww.teradata.comwww.timescale.com
Technical documentationspark.apache.org/­docs/­latest/­sql-programming-guide.htmldocs.teradata.comdocs.timescale.com
DeveloperApache Software FoundationTeradataTimescale
Initial release201419842017
Current release3.5.0 ( 2.13), September 2023Teradata Vantage 1.0 MU2, January 20192.13.0, November 2023
License infoCommercial or Open SourceOpen Source infoApache 2.0commercialOpen Source infoApache 2.0
Cloud-based only infoOnly available as a cloud servicenonono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageScalaC
Server operating systemsLinux
OS X
Windows
hosted
Linux
Linux
OS X
Windows
Data schemeyesyesyes
Typing infopredefined data types such as float or dateyesyesnumerics, 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.noyesyes
Secondary indexesnoyes infoJoin-index to prejoin tables, aggregate index, sparse index, hash indexyes
SQL infoSupport of SQLSQL-like DML and DDL statementsyes infoSQL 2016 + extensionsyes infofull PostgreSQL SQL syntax
APIs and other access methodsJDBC
ODBC
.NET Client API
HTTP REST
JDBC
JMS Adapter
ODBC
OLE DB
ADO.NET
JDBC
native C library
ODBC
streaming API for large objects
Supported programming languagesJava
Python
R
Scala
C
C++
Cobol
Java (JDBC-ODBC)
Perl
PL/1
Python
R
Ruby
.Net
C
C++
Delphi
Java infoJDBC
JavaScript
Perl
PHP
Python
R
Ruby
Scheme
Tcl
Server-side scripts infoStored proceduresnoyes infoUDFs, stored procedures, table functions in paralleluser defined functions, PL/pgSQL, PL/Tcl, PL/Perl, PL/Python, PL/Java, PL/PHP, PL/R, PL/Ruby, PL/Scheme, PL/Unix shell
Triggersnoyesyes
Partitioning methods infoMethods for storing different data on different nodesyes, utilizing Spark CoreSharding infoHashingyes, across time and space (hash partitioning) attributes
Replication methods infoMethods for redundantly storing data on multiple nodesnoneMulti-source replication
Source-replica replication
Source-replica replication with hot standby and reads on replicas info
MapReduce infoOffers an API for user-defined Map/Reduce methodsnono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynoyesyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDACID
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.noyesno
User concepts infoAccess controlnofine grained access rights according to SQL-standardfine grained access rights according to SQL-standard

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More resources
Spark SQLTeradataTimescaleDB
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