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DBMS > Apache Spark (SQL) vs. Hyprcubd vs. TimesTen

System Properties Comparison Apache Spark (SQL) vs. Hyprcubd vs. TimesTen

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Editorial information provided by DB-Engines
NameApache Spark (SQL)  Xexclude from comparisonHyprcubd  Xexclude from comparisonTimesTen  Xexclude from comparison
Hyprcubd seems to be discontinued. Therefore it is excluded from the DB-Engines ranking.
DescriptionApache Spark SQL is a component on top of 'Spark Core' for structured data processingServerless Time Series DBMSAn 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 DBMSTime Series DBMSRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score17.80
Rank#31  Overall
#19  Relational DBMS
Score1.19
Rank#167  Overall
#76  Relational DBMS
Websitespark.apache.org/­sqlhyprcubd.com (offline)www.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 FoundationHyprcubd, Inc.Oracle 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 2.0commercialcommercial
Cloud-based only infoOnly available as a cloud servicenoyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageScalaGo
Server operating systemsLinux
OS X
Windows
hostedIBM AIX Power PC 64-bit
Linux arm64
Linux x86-64
Solaris SPARC 64
Solaris SPARC/x86
Solaris x86-64
Data schemeyesyesyes
Typing infopredefined data types such as float or dateyesyes infotime, int, uint, float, stringyes
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.nonono
Secondary indexesnonoyes
SQL infoSupport of SQLSQL-like DML and DDL statementsSQL-like query languageyes
APIs and other access methodsJDBC
ODBC
gRPC (https)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 proceduresnonoPL/SQL
Triggersnonono
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 methodsnono
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual ConsistencyImmediate Consistency or Eventual Consistency depending on configuration
Foreign keys infoReferential integritynonoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanonoACID
Concurrency infoSupport for concurrent manipulation of datayesnoyes
Durability infoSupport for making data persistentyesyesyes 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.nonoyes
User concepts infoAccess controlnotoken accessfine grained access rights according to SQL-standard

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More resources
Apache Spark (SQL)HyprcubdTimesTen
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