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DBMS > Databend vs. Spark SQL vs. TimesTen

System Properties Comparison Databend vs. Spark SQL vs. TimesTen

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Editorial information provided by DB-Engines
NameDatabend  Xexclude from comparisonSpark SQL  Xexclude from comparisonTimesTen  Xexclude from comparison
DescriptionAn open-source, elastic, and workload-aware cloud data warehouse designed to meet businesses' massive-scale analytics needs at low cost and with low complexitySpark SQL is a component on top of 'Spark Core' for structured data processingIn-Memory RDBMS compatible to Oracle
Primary database modelRelational DBMSRelational DBMSRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.30
Rank#287  Overall
#130  Relational DBMS
Score18.96
Rank#33  Overall
#20  Relational DBMS
Score1.31
Rank#163  Overall
#74  Relational DBMS
Websitegithub.com/­datafuselabs/­databend
www.databend.com
spark.apache.org/­sqlwww.oracle.com/­database/­technologies/­related/­timesten.html
Technical documentationdocs.databend.comspark.apache.org/­docs/­latest/­sql-programming-guide.htmldocs.oracle.com/­database/­timesten-18.1
DeveloperDatabend LabsApache Software FoundationOracle, TimesTen Performance Software, HP infooriginally founded in HP Labs it was acquired by Oracle in 2005
Initial release202120141998
Current release1.0.59, April 20233.5.0 ( 2.13), September 202311 Release 2 (11.2.2.8.0)
License infoCommercial or Open SourceOpen Source infoApache Version 2.0Open Source infoApache 2.0commercial
Cloud-based only infoOnly available as a cloud servicenonono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageRustScala
Server operating systemshosted
Linux
macOS
Linux
OS X
Windows
AIX
HP-UX
Linux
OS X
Solaris SPARC/x86
Windows
Data schemeyesyesyes
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.nonono
Secondary indexesnonoyes
SQL infoSupport of SQLyesSQL-like DML and DDL statementsyes
APIs and other access methodsCLI Client
JDBC
RESTful HTTP API
JDBC
ODBC
JDBC
ODBC
ODP.NET
Oracle Call Interface (OCI)
Supported programming languagesGo
Java
JavaScript (Node.js)
Python
Rust
Java
Python
R
Scala
C
C++
Java
PL/SQL
Server-side scripts infoStored proceduresnonoPL/SQL
Triggersnonono
Partitioning methods infoMethods for storing different data on different nodesnoneyes, utilizing Spark Corenone
Replication methods infoMethods for redundantly storing data on multiple nodesnonenoneMulti-source replication
Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate Consistency or Eventual Consistency depending on configuration
Foreign keys infoReferential integritynonoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datayesnoACID
Concurrency infoSupport for concurrent manipulation of datayesyesyes
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.noyes
User concepts infoAccess controlUsers with fine-grained authorization concept, user rolesnofine grained access rights according to SQL-standard

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DatabendSpark SQLTimesTen
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