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DBMS > Databricks vs. FatDB vs. Spark SQL vs. SQL.JS vs. TimescaleDB

System Properties Comparison Databricks vs. FatDB vs. Spark SQL vs. SQL.JS vs. TimescaleDB

Editorial information provided by DB-Engines
NameDatabricks  Xexclude from comparisonFatDB  Xexclude from comparisonSpark SQL  Xexclude from comparisonSQL.JS  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.Spark SQL is a component on top of 'Spark Core' for structured data processingPort of SQLite to JavaScriptA time series DBMS optimized for fast ingest and complex queries, based on PostgreSQL
Primary database modelDocument store
Relational DBMS
Document store
Key-value store
Relational DBMSRelational DBMSTime Series DBMS
Secondary database modelsRelational 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
Score18.04
Rank#33  Overall
#20  Relational DBMS
Score0.63
Rank#241  Overall
#112  Relational DBMS
Score4.46
Rank#71  Overall
#5  Time Series DBMS
Websitewww.databricks.comspark.apache.org/­sqlsql.js.orgwww.timescale.com
Technical documentationdocs.databricks.comspark.apache.org/­docs/­latest/­sql-programming-guide.htmlsql.js.org/­documentation/­index.htmldocs.timescale.com
DeveloperDatabricksFatCloudApache Software FoundationAlon Zakai infoenhancements implemented by othersTimescale
Initial release20132012201420122017
Current release3.5.0 ( 2.13), September 20232.15.0, May 2024
License infoCommercial or Open SourcecommercialcommercialOpen Source infoApache 2.0Open SourceOpen Source infoApache 2.0
Cloud-based only infoOnly available as a cloud serviceyesnononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC#ScalaJavaScriptC
Server operating systemshostedWindowsLinux
OS X
Windows
server-less, requires a JavaScript environment (browser, Node.js)Linux
OS X
Windows
Data schemeFlexible Schema (defined schema, partial schema, schema free)schema-freeyesyesyes
Typing infopredefined data types such as float or dateyesyesyesnumerics, 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.yesnonoyes
Secondary indexesyesyesnoyes
SQL infoSupport of SQLwith Databricks SQLno infoVia inetgration in SQL ServerSQL-like DML and DDL statementsyes infoSQL-92 is not fully supportedyes infofull PostgreSQL SQL syntax
APIs and other access methodsJDBC
ODBC
RESTful HTTP API
.NET Client API
LINQ
RESTful HTTP API
RPC
Windows WCF Bindings
JDBC
ODBC
JavaScript APIADO.NET
JDBC
native C library
ODBC
streaming API for large objects
Supported programming languagesPython
R
Scala
C#Java
Python
R
Scala
JavaScript.Net
C
C++
Delphi
Java infoJDBC
JavaScript
Perl
PHP
Python
R
Ruby
Scheme
Tcl
Server-side scripts infoStored proceduresuser defined functions and aggregatesyes infovia applicationsnonouser 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 applicationsnonoyes
Partitioning methods infoMethods for storing different data on different nodesShardingyes, utilizing Spark Corenoneyes, across time and space (hash partitioning) attributes
Replication methods infoMethods for redundantly storing data on multiple nodesyesselectable replication factornonenoneSource-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
noneImmediate Consistency
Foreign keys infoReferential integritynonoyesyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDnonoACIDACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyesyesno infoexcept by serializing a db to a fileyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.nonoyesno
User concepts infoAccess controlno infoCan implement custom security layer via applicationsnonofine grained access rights according to SQL-standard
More information provided by the system vendor
DatabricksFatDBSpark SQLSQL.JSTimescaleDB
Specific characteristicsSupported database models : In addition to the Document store and Relational DBMS...
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More resources
DatabricksFatDBSpark SQLSQL.JSTimescaleDB
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