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DBMS > Spark SQL vs. Teradata vs. Virtuoso

System Properties Comparison Spark SQL vs. Teradata vs. Virtuoso

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Editorial information provided by DB-Engines
NameSpark SQL  Xexclude from comparisonTeradata  Xexclude from comparisonVirtuoso  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)Virtuoso is a multi-model hybrid-RDBMS that supports management of data represented as relational tables and/or property graphs
Primary database modelRelational DBMSRelational DBMSDocument store
Graph DBMS
Native XML DBMS
Relational DBMS
RDF store
Search engine
Secondary database modelsDocument store
Graph DBMS
Spatial DBMS
Time Series DBMS
Spatial 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
Score4.26
Rank#78  Overall
#13  Document stores
#4  Graph DBMS
#2  Native XML DBMS
#42  Relational DBMS
#2  RDF stores
#9  Search engines
Websitespark.apache.org/­sqlwww.teradata.comvirtuoso.openlinksw.com
Technical documentationspark.apache.org/­docs/­latest/­sql-programming-guide.htmldocs.teradata.comdocs.openlinksw.com/­virtuoso
DeveloperApache Software FoundationTeradataOpenLink Software
Initial release201419841998
Current release3.5.0 ( 2.13), September 2023Teradata Vantage 1.0 MU2, January 20197.2.11, September 2023
License infoCommercial or Open SourceOpen Source infoApache 2.0commercialOpen Source infoGPLv2, extended commercial license available
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
AIX
FreeBSD
HP-UX
Linux
OS X
Solaris
Windows
Data schemeyesyesyes infoSQL - Standard relational schema
RDF - Quad (S, P, O, G) or Triple (S, P, O)
XML - DTD, XML Schema
DAV - freeform filesystem objects, plus User Defined Types a/k/a Dynamic Extension Type
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.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 infoSQL-92, SQL-200x, SQL-3, SQLX
APIs and other access methodsJDBC
ODBC
.NET Client API
HTTP REST
JDBC
JMS Adapter
ODBC
OLE DB
ADO.NET
GeoSPARQL
HTTP API
JDBC
Jena RDF API
ODBC
OLE DB
RDF4J API
RESTful HTTP API
Sesame REST HTTP Protocol
SOAP webservices
SPARQL 1.1
WebDAV
XPath
XQuery
XSLT
Supported programming languagesJava
Python
R
Scala
C
C++
Cobol
Java (JDBC-ODBC)
Perl
PL/1
Python
R
Ruby
.Net
C
C#
C++
Java
JavaScript
Perl
PHP
Python
Ruby
Visual Basic
Server-side scripts infoStored proceduresnoyes infoUDFs, stored procedures, table functions in parallelyes infoVirtuoso PL
Triggersnoyesyes
Partitioning methods infoMethods for storing different data on different nodesyes, utilizing Spark CoreSharding infoHashingyes
Replication methods infoMethods for redundantly storing data on multiple nodesnoneMulti-source replication
Source-replica replication
Chain, star, and bi-directional replication
Multi-source replication
Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyes
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.noyesyes
User concepts infoAccess controlnofine grained access rights according to SQL-standardFine-grained Attribute-Based Access Control (ABAC) in addition to typical coarse-grained Role-Based Access Control (RBAC) according to SQL-standard. Pluggable authentication with supported standards (LDAP, Active Directory, Kerberos)
More information provided by the system vendor
Spark SQLTeradataVirtuoso
Specific characteristicsVirtuoso is a modern multi-model RDBMS for managing data represented as tabular relations...
» more
Competitive advantagesPerformance & Scale โ€” as exemplified by DBpedia and the LOD Cloud it spawned, i.e.,...
» more
Typical application scenariosUsed for โ€” Analytics/BI Conceptual Data Virtualization Enterprise Knowledge Graphs...
» more
Key customersBroad use across enterprises and governments including โ€” European Union (EU) US Government...
» more
Market metricsLargest installed-base โ€‹of Multi-Model RDBMS for AI-friendly Knowledge Graphs Platform...
» more
Licensing and pricing modelsAvailable in both Commercial Enterprise and Open Source (GPL v2) Editions Feature...
» more

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More resources
Spark SQLTeradataVirtuoso
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