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DBMS > Apache Spark (SQL) vs. TimesTen

System Properties Comparison Apache Spark (SQL) vs. TimesTen

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Editorial information provided by DB-Engines
NameApache Spark (SQL)  Xexclude from comparisonTimesTen  Xexclude from comparison
DescriptionApache Spark SQL is a component on top of 'Spark Core' for structured data processingAn in-memory SQL relational database that delivers microsecond response and high throughput for OLTP applications. TimesTen can be deployed as a standalone database or as a cache to a backend Oracle database.
Primary database modelRelational DBMSRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score18.45
Rank#31  Overall
#19  Relational DBMS
Score1.17
Rank#167  Overall
#76  Relational DBMS
Websitespark.apache.org/­sqlwww.oracle.com/­database/­technologies/­related/­timesten.html
Technical documentationspark.apache.org/­docs/­latest/­sql-programming-guide.htmldocs.oracle.com/­en/­database/­other-databases/­timesten/­index.html
DeveloperApache Software FoundationOracle infooriginally founded in HP Labs it was acquired by Oracle in 2005
Initial release20141998
Current release3.5.0 ( 2.13), September 2023Release 22.1
License infoCommercial or Open SourceOpen Source infoApache 2.0commercial
Cloud-based only infoOnly available as a cloud servicenono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageScala
Server operating systemsLinux
OS X
Windows
IBM AIX Power PC 64-bit
Linux arm64
Linux x86-64
Solaris SPARC 64
Solaris SPARC/x86
Solaris x86-64
Data schemeyesyes
Typing infopredefined data types such as float or dateyesyes
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.nono
Secondary indexesnoyes
SQL infoSupport of SQLSQL-like DML and DDL statementsyes
APIs and other access methodsJDBC
ODBC
ODBC
ODP.NET
Oracle Call Interface (OCI)
Pro*C/C++ programming interfaces
SQL and PL/SQL via JDBC
Supported programming languagesJava
Python
R
Scala
C
C++
Java
Node.js
PL/SQL
Python
Server-side scripts infoStored proceduresnoPL/SQL
Triggersnono
Partitioning methods infoMethods for storing different data on different nodesyes, utilizing Spark Corenone
Replication methods infoMethods for redundantly storing data on multiple nodesnoneMulti-source replication
Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate Consistency or Eventual Consistency depending on configuration
Foreign keys infoReferential integritynoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACID
Concurrency infoSupport for concurrent manipulation of datayesyes
Durability infoSupport for making data persistentyesyes infoby means of logfiles and checkpoints
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyes
User concepts infoAccess controlnofine grained access rights according to SQL-standard

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More resources
Apache Spark (SQL)TimesTen
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