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DBMS > Databricks vs. FatDB vs. InfluxDB vs. TimescaleDB

System Properties Comparison Databricks vs. FatDB vs. InfluxDB vs. TimescaleDB

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Editorial information provided by DB-Engines
NameDatabricks  Xexclude from comparisonFatDB  Xexclude from comparisonInfluxDB  Xexclude from comparisonTimescaleDB  Xexclude from comparison
FatDB/FatCloud has ceased operations as a company with February 2014. FatDB is discontinued and excluded from the ranking.
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 .NET NoSQL DBMS that can integrate with and extend SQL Server.DBMS for storing time series, events and metricsA time series DBMS optimized for fast ingest and complex queries, based on PostgreSQL
Primary database modelDocument store
Relational DBMS
Document store
Key-value store
Time Series DBMSTime Series DBMS
Secondary database modelsSpatial DBMS infowith GEO packageRelational 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
Score25.83
Rank#28  Overall
#1  Time Series DBMS
Score4.64
Rank#71  Overall
#4  Time Series DBMS
Websitewww.databricks.comwww.influxdata.com/­products/­influxdb-overviewwww.timescale.com
Technical documentationdocs.databricks.comdocs.influxdata.com/­influxdbdocs.timescale.com
DeveloperDatabricksFatCloudTimescale
Initial release2013201220132017
Current release2.7.6, April 20242.13.0, November 2023
License infoCommercial or Open SourcecommercialcommercialOpen Source infoMIT-License; commercial enterprise version availableOpen Source infoApache 2.0
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 languageC#GoC
Server operating systemshostedWindowsLinux
OS X infothrough Homebrew
Linux
OS X
Windows
Data schemeFlexible Schema (defined schema, partial schema, schema free)schema-freeschema-freeyes
Typing infopredefined data types such as float or dateyesNumeric data and Stringsnumerics, strings, booleans, arrays, JSON blobs, geospatial dimensions, currencies, binary data, other complex data types
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.yesnoyes
Secondary indexesyesyesnoyes
SQL infoSupport of SQLwith Databricks SQLno infoVia inetgration in SQL ServerSQL-like query languageyes infofull PostgreSQL SQL syntax
APIs and other access methodsJDBC
ODBC
RESTful HTTP API
.NET Client API
LINQ
RESTful HTTP API
RPC
Windows WCF Bindings
HTTP API
JSON over UDP
ADO.NET
JDBC
native C library
ODBC
streaming API for large objects
Supported programming languagesPython
R
Scala
C#.Net
Clojure
Erlang
Go
Haskell
Java
JavaScript
JavaScript (Node.js)
Lisp
Perl
PHP
Python
R
Ruby
Rust
Scala
.Net
C
C++
Delphi
Java infoJDBC
JavaScript
Perl
PHP
Python
R
Ruby
Scheme
Tcl
Server-side scripts infoStored proceduresuser defined functions and aggregatesyes infovia applicationsnouser defined functions, PL/pgSQL, PL/Tcl, PL/Perl, PL/Python, PL/Java, PL/PHP, PL/R, PL/Ruby, PL/Scheme, PL/Unix shell
Triggersyes infovia applicationsnoyes
Partitioning methods infoMethods for storing different data on different nodesShardingSharding infoin enterprise version onlyyes, across time and space (hash partitioning) attributes
Replication methods infoMethods for redundantly storing data on multiple nodesyesselectable replication factorselectable replication factor infoin enterprise version onlySource-replica replication with hot standby and reads on replicas info
MapReduce infoOffers an API for user-defined Map/Reduce methodsyesnono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyEventual Consistency
Immediate Consistency
Immediate Consistency
Foreign keys infoReferential integritynonoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDnonoACID
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.noyes infoDepending on used storage engineno
User concepts infoAccess controlno infoCan implement custom security layer via applicationssimple rights management via user accountsfine grained access rights according to SQL-standard
More information provided by the system vendor
DatabricksFatDBInfluxDBTimescaleDB
Specific characteristicsSupported database models : In addition to the Document store and Relational DBMS...
» more
InfluxData is the creator of InfluxDB , the open source time series database. It...
» more
Competitive advantagesTime to Value InfluxDB is available in all the popular languages and frameworks,...
» more
Typical application scenariosIoT & Sensor Monitoring Developers are witnessing the instrumentation of every available...
» more
Key customersInfluxData has more than 1,900 paying customers, including customers include MuleSoft,...
» more
Market metricsFastest-growing database to drive 27,500 GitHub stars Over 750,000 daily active instances
» more
Licensing and pricing modelsOpen source core with closed source clustering available either on-premise or on...
» more
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