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DBMS > Databricks vs. Spark SQL vs. TDengine vs. Transbase

System Properties Comparison Databricks vs. Spark SQL vs. TDengine vs. Transbase

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Editorial information provided by DB-Engines
NameDatabricks  Xexclude from comparisonSpark SQL  Xexclude from comparisonTDengine  Xexclude from comparisonTransbase  Xexclude from comparison
DescriptionThe 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.Spark SQL is a component on top of 'Spark Core' for structured data processingTime Series DBMS and big data platformA resource-optimized, high-performance, universally applicable RDBMS
Primary database modelDocument store
Relational DBMS
Relational DBMSTime Series DBMSRelational DBMS
Secondary database modelsRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score78.61
Rank#15  Overall
#2  Document stores
#10  Relational DBMS
Score18.96
Rank#33  Overall
#20  Relational DBMS
Score2.60
Rank#107  Overall
#8  Time Series DBMS
Score0.11
Rank#341  Overall
#150  Relational DBMS
Websitewww.databricks.comspark.apache.org/­sqlgithub.com/­taosdata/­TDengine
tdengine.com
www.transaction.de/­en/­products/­transbase.html
Technical documentationdocs.databricks.comspark.apache.org/­docs/­latest/­sql-programming-guide.htmldocs.tdengine.comwww.transaction.de/­en/­products/­transbase/­features.html
DeveloperDatabricksApache Software FoundationTDEngine, previously Taos DataTransaction Software GmbH
Initial release2013201420191987
Current release3.5.0 ( 2.13), September 20233.0, August 2022Transbase 8.3, 2022
License infoCommercial or Open SourcecommercialOpen Source infoApache 2.0Open Source infoAGPL V3, also commercial editions availablecommercial infofree development license
Cloud-based only infoOnly available as a cloud serviceyesnonono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageScalaCC and C++
Server operating systemshostedLinux
OS X
Windows
Linux
Windows
FreeBSD
Linux
macOS
Solaris
Windows
Data schemeFlexible Schema (defined schema, partial schema, schema free)yesyesyes
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.yesnonono
Secondary indexesyesnonoyes
SQL infoSupport of SQLwith Databricks SQLSQL-like DML and DDL statementsStandard SQL with extensions for time-series applicationsyes
APIs and other access methodsJDBC
ODBC
RESTful HTTP API
JDBC
ODBC
JDBC
RESTful HTTP API
ADO.NET
JDBC
ODBC
Proprietary native API
Supported programming languagesPython
R
Scala
Java
Python
R
Scala
C
C#
C++
Go
Java
JavaScript (Node.js)
PHP
Python
Rust
C
C#
C++
Java
JavaScript
Kotlin
Objective-C
PHP
Python
Server-side scripts infoStored proceduresuser defined functions and aggregatesnonoyes
Triggersnoyes, via alarm monitoringyes
Partitioning methods infoMethods for storing different data on different nodesyes, utilizing Spark CoreSharding
Replication methods infoMethods for redundantly storing data on multiple nodesyesnoneyesSource-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynonoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDnoyes
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.nonono
User concepts infoAccess controlnoyesfine grained access rights according to SQL-standard
More information provided by the system vendor
DatabricksSpark SQLTDengineTransbase
Specific characteristicsSupported database models : In addition to the Document store and Relational DBMS...
» more
TDengine™ is a next generation data historian purpose-built for Industry 4.0 and...
» more
Competitive advantagesHigh Performance at any Scale: TDengine is purpose-built for handling massive industrial...
» more
Typical application scenariosTDengine is designed for Industrial IoT scenarios, including: Manufacturing Connected...
» more
Market metricsTDengine has garnered over 22,500 stars on GitHub and is used in over 50 countries...
» more
Licensing and pricing modelsTDengine OSS is an open source, cloud native time series database. It includes built-in...
» more
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8 May 2024

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7 May 2024

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