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

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

Editorial information provided by DB-Engines
NameFatDB  Xexclude from comparisonSpark SQL  Xexclude from comparisonSQL.JS  Xexclude from comparisonTimescaleDB  Xexclude from comparisonTypesense  Xexclude from comparison
FatDB/FatCloud has ceased operations as a company with February 2014. FatDB is discontinued and excluded from the ranking.
DescriptionA .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 PostgreSQLA typo-tolerant, in-memory search engine optimized for instant search-as-you-type experiences and developer productivity
Primary database modelDocument store
Key-value store
Relational DBMSRelational DBMSTime Series DBMSSearch engine
Secondary database modelsRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
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
Score0.76
Rank#219  Overall
#14  Search engines
Websitespark.apache.org/­sqlsql.js.orgwww.timescale.comtypesense.org
Technical documentationspark.apache.org/­docs/­latest/­sql-programming-guide.htmlsql.js.org/­documentation/­index.htmldocs.timescale.comtypesense.org/­docs
DeveloperFatCloudApache Software FoundationAlon Zakai infoenhancements implemented by othersTimescale
Initial release20122014201220172015
Current release3.5.0 ( 2.13), September 20232.15.0, May 2024
License infoCommercial or Open SourcecommercialOpen Source infoApache 2.0Open SourceOpen Source infoApache 2.0Open Source infoGPL V3
Cloud-based only infoOnly available as a cloud servicenonononono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageC#ScalaJavaScriptCC++
Server operating systemsWindowsLinux
OS X
Windows
server-less, requires a JavaScript environment (browser, Node.js)Linux
OS X
Windows
Linux
Data schemeschema-freeyesyesyesschema-free infopre-defined schema optional
Typing infopredefined data types such as float or dateyesyesyesnumerics, strings, booleans, arrays, JSON blobs, geospatial dimensions, currencies, binary data, other complex data typesyes
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.nonoyes
Secondary indexesyesnoyesyes
SQL infoSupport of SQLno infoVia inetgration in SQL ServerSQL-like DML and DDL statementsyes infoSQL-92 is not fully supportedyes infofull PostgreSQL SQL syntaxno
APIs and other access methods.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
RESTful HTTP API
Supported programming languagesC#Java
Python
R
Scala
JavaScript.Net
C
C++
Delphi
Java infoJDBC
JavaScript
Perl
PHP
Python
R
Ruby
Scheme
Tcl
.Net infocommunity maintained
Clojure infocommunity maintained
Dart infocommunity maintained
Go infocommunity maintained
Java infocommunity maintained
JavaScript
Perl infocommunity maintained
PHP
Python
Ruby
Rust infocommunity maintained
Swift infocommunity maintained
Server-side scripts infoStored proceduresyes infovia applicationsnonouser defined functions, PL/pgSQL, PL/Tcl, PL/Perl, PL/Python, PL/Java, PL/PHP, PL/R, PL/Ruby, PL/Scheme, PL/Unix shellno
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 nodesselectable replication factornonenoneSource-replica replication with hot standby and reads on replicas infoMulti-source replication using RAFT
MapReduce infoOffers an API for user-defined Map/Reduce methodsyesnonono
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual Consistency
Immediate Consistency
noneImmediate Consistency
Foreign keys infoReferential integritynonoyesyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanonoACIDACIDno
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyesno infoexcept by serializing a db to a fileyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyesnoyes
User concepts infoAccess controlno infoCan implement custom security layer via applicationsnonofine grained access rights according to SQL-standard

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More resources
FatDBSpark SQLSQL.JSTimescaleDBTypesense
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