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DBMS > Spark SQL vs. Teradata vs. TigerGraph vs. Transbase

System Properties Comparison Spark SQL vs. Teradata vs. TigerGraph vs. Transbase

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Editorial information provided by DB-Engines
NameSpark SQL  Xexclude from comparisonTeradata  Xexclude from comparisonTigerGraph  Xexclude from comparisonTransbase  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 complete, distributed, parallel graph computing platform supporting web-scale data analytics in real-timeA resource-optimized, high-performance, universally applicable RDBMS
Primary database modelRelational DBMSRelational DBMSGraph DBMSRelational DBMS
Secondary database modelsDocument store
Graph DBMS
Spatial DBMS
Time Series 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
Score1.83
Rank#139  Overall
#13  Graph DBMS
Score0.11
Rank#341  Overall
#150  Relational DBMS
Websitespark.apache.org/­sqlwww.teradata.comwww.tigergraph.comwww.transaction.de/­en/­products/­transbase.html
Technical documentationspark.apache.org/­docs/­latest/­sql-programming-guide.htmldocs.teradata.comdocs.tigergraph.comwww.transaction.de/­en/­products/­transbase/­features.html
DeveloperApache Software FoundationTeradataTransaction Software GmbH
Initial release2014198420171987
Current release3.5.0 ( 2.13), September 2023Teradata Vantage 1.0 MU2, January 2019Transbase 8.3, 2022
License infoCommercial or Open SourceOpen Source infoApache 2.0commercialcommercialcommercial infofree development license
Cloud-based only infoOnly available as a cloud servicenononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageScalaC++C and C++
Server operating systemsLinux
OS X
Windows
hosted
Linux
LinuxFreeBSD
Linux
macOS
Solaris
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.noyesnono
Secondary indexesnoyes infoJoin-index to prejoin tables, aggregate index, sparse index, hash indexyes
SQL infoSupport of SQLSQL-like DML and DDL statementsyes infoSQL 2016 + extensionsSQL-like query language (GSQL)yes
APIs and other access methodsJDBC
ODBC
.NET Client API
HTTP REST
JDBC
JMS Adapter
ODBC
OLE DB
GSQL (TigerGraph Query Language)
Kafka
RESTful HTTP/JSON API
ADO.NET
JDBC
ODBC
Proprietary native API
Supported programming languagesJava
Python
R
Scala
C
C++
Cobol
Java (JDBC-ODBC)
Perl
PL/1
Python
R
Ruby
C++
Java
C
C#
C++
Java
JavaScript
Kotlin
Objective-C
PHP
Python
Server-side scripts infoStored proceduresnoyes infoUDFs, stored procedures, table functions in parallelyesyes
Triggersnoyesnoyes
Partitioning methods infoMethods for storing different data on different nodesyes, utilizing Spark CoreSharding infoHashing
Replication methods infoMethods for redundantly storing data on multiple nodesnoneMulti-source replication
Source-replica replication
Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyesno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynoyesyes infoRelationships in graphsyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDACIDyes
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.noyesnono
User concepts infoAccess controlnofine grained access rights according to SQL-standardRole-based access controlfine grained access rights according to SQL-standard

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More resources
Spark SQLTeradataTigerGraphTransbase
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