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DBMS > Databricks vs. TimescaleDB vs. TimesTen vs. Vitess

System Properties Comparison Databricks vs. TimescaleDB vs. TimesTen vs. Vitess

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Editorial information provided by DB-Engines
NameDatabricks  Xexclude from comparisonTimescaleDB  Xexclude from comparisonTimesTen  Xexclude from comparisonVitess  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.A time series DBMS optimized for fast ingest and complex queries, based on PostgreSQLIn-Memory RDBMS compatible to OracleScalable, distributed, cloud-native DBMS, extending MySQL
Primary database modelDocument store
Relational DBMS
Time Series DBMSRelational DBMSRelational DBMS
Secondary database modelsRelational DBMSDocument store
Spatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score81.08
Rank#15  Overall
#2  Document stores
#10  Relational DBMS
Score4.46
Rank#71  Overall
#5  Time Series DBMS
Score1.36
Rank#161  Overall
#75  Relational DBMS
Score0.88
Rank#203  Overall
#95  Relational DBMS
Websitewww.databricks.comwww.timescale.comwww.oracle.com/­database/­technologies/­related/­timesten.htmlvitess.io
Technical documentationdocs.databricks.comdocs.timescale.comdocs.oracle.com/­database/­timesten-18.1vitess.io/­docs
DeveloperDatabricksTimescaleOracle, TimesTen Performance Software, HP infooriginally founded in HP Labs it was acquired by Oracle in 2005The Linux Foundation, PlanetScale
Initial release2013201719982013
Current release2.15.0, May 202411 Release 2 (11.2.2.8.0)15.0.2, December 2022
License infoCommercial or Open SourcecommercialOpen Source infoApache 2.0commercialOpen Source infoApache Version 2.0, commercial licenses available
Cloud-based only infoOnly available as a cloud serviceyesnonono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageCGo
Server operating systemshostedLinux
OS X
Windows
AIX
HP-UX
Linux
OS X
Solaris SPARC/x86
Windows
Docker
Linux
macOS
Data schemeFlexible Schema (defined schema, partial schema, schema free)yesyesyes
Typing infopredefined data types such as float or datenumerics, strings, booleans, arrays, JSON blobs, geospatial dimensions, currencies, binary data, other complex data typesyesyes
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.yesyesno
Secondary indexesyesyesyesyes
SQL infoSupport of SQLwith Databricks SQLyes infofull PostgreSQL SQL syntaxyesyes infowith proprietary extensions
APIs and other access methodsJDBC
ODBC
RESTful HTTP API
ADO.NET
JDBC
native C library
ODBC
streaming API for large objects
JDBC
ODBC
ODP.NET
Oracle Call Interface (OCI)
ADO.NET
JDBC
MySQL protocol
ODBC
Supported programming languagesPython
R
Scala
.Net
C
C++
Delphi
Java infoJDBC
JavaScript
Perl
PHP
Python
R
Ruby
Scheme
Tcl
C
C++
Java
PL/SQL
Ada
C
C#
C++
D
Delphi
Eiffel
Erlang
Haskell
Java
JavaScript (Node.js)
Objective-C
OCaml
Perl
PHP
Python
Ruby
Scheme
Tcl
Server-side scripts infoStored proceduresuser defined functions and aggregatesuser defined functions, PL/pgSQL, PL/Tcl, PL/Perl, PL/Python, PL/Java, PL/PHP, PL/R, PL/Ruby, PL/Scheme, PL/Unix shellPL/SQLyes infoproprietary syntax
Triggersyesnoyes
Partitioning methods infoMethods for storing different data on different nodesyes, across time and space (hash partitioning) attributesnoneSharding
Replication methods infoMethods for redundantly storing data on multiple nodesyesSource-replica replication with hot standby and reads on replicas infoMulti-source replication
Source-replica replication
Multi-source replication
Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyImmediate Consistency or Eventual Consistency depending on configurationEventual Consistency across shards
Immediate Consistency within a shard
Foreign keys infoReferential integrityyesyesyes infonot for MyISAM storage engine
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACIDACIDACID at shard level
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes infotable locks or row locks depending on storage engine
Durability infoSupport for making data persistentyesyesyes infoby means of logfiles and checkpointsyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.nonoyesyes
User concepts infoAccess controlfine grained access rights according to SQL-standardfine grained access rights according to SQL-standardUsers with fine-grained authorization concept infono user groups or roles
More information provided by the system vendor
DatabricksTimescaleDBTimesTenVitess
Specific characteristicsSupported database models : In addition to the Document store and Relational DBMS...
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More resources
DatabricksTimescaleDBTimesTenVitess
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