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DBMS > Apache Kylin vs. Databricks vs. TimesTen

System Properties Comparison Apache Kylin vs. Databricks vs. TimesTen

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Editorial information provided by DB-Engines
NameApache Kylin  Xexclude from comparisonDatabricks  Xexclude from comparisonTimesTen  Xexclude from comparison
DescriptionA distributed analytics engine for big data, providing a SQL interface and multi-dimensional analysis (OLAP) and leveraging the Hadoop stackThe Databricks Lakehouse Platform combines elements of data lakes and data warehouses to provide a unified view onto structured and unstructured data. It is based on Apache Spark.An 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 DBMSDocument store
Relational DBMS
Relational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.14
Rank#171  Overall
#78  Relational DBMS
Score83.29
Rank#15  Overall
#2  Document stores
#10  Relational DBMS
Score1.26
Rank#164  Overall
#76  Relational DBMS
Websitekylin.apache.orgwww.databricks.comwww.oracle.com/­database/­technologies/­related/­timesten.html
Technical documentationkylin.apache.org/­docsdocs.databricks.comdocs.oracle.com/­en/­database/­other-databases/­timesten/­index.html
DeveloperApache Software Foundation, originally contributed from eBay IncDatabricksOracle infooriginally founded in HP Labs it was acquired by Oracle in 2005
Initial release201520131998
Current release3.1.0, July 2020Release 22.1
License infoCommercial or Open SourceOpen Source infoApache Version 2.0commercialcommercial
Cloud-based only infoOnly available as a cloud servicenoyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJava
Server operating systemsLinuxhostedIBM AIX Power PC 64-bit
Linux arm64
Linux x86-64
Solaris SPARC 64
Solaris SPARC/x86
Solaris x86-64
Data schemeyesFlexible Schema (defined schema, partial schema, schema free)yes
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.noyesno
Secondary indexesyesyesyes
SQL infoSupport of SQLANSI SQL for queries (using Apache Calcite)with Databricks SQLyes
APIs and other access methodsJDBC
ODBC
RESTful HTTP API
JDBC
ODBC
RESTful HTTP API
ODBC
ODP.NET
Oracle Call Interface (OCI)
Pro*C/C++ programming interfaces
SQL and PL/SQL via JDBC
Supported programming languagesPython
R
Scala
C
C++
Java
Node.js
PL/SQL
Python
Server-side scripts infoStored proceduresuser defined functions and aggregatesPL/SQL
Triggersno
Partitioning methods infoMethods for storing different data on different nodesnone
Replication methods infoMethods for redundantly storing data on multiple nodesyesMulti-source replication
Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsyesno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyImmediate Consistency or Eventual Consistency depending on configuration
Foreign keys infoReferential integrityyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACID
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.nonoyes
User concepts infoAccess controlfine grained access rights according to SQL-standard
More information provided by the system vendor
Apache KylinDatabricksTimesTen
Specific characteristicsSupported database models : In addition to the Document store and Relational DBMS...
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Apache KylinDatabricksTimesTen
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