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DBMS > FatDB vs. Spark SQL vs. SurrealDB vs. Typesense

System Properties Comparison FatDB vs. Spark SQL vs. SurrealDB vs. Typesense

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Editorial information provided by DB-Engines
NameFatDB  Xexclude from comparisonSpark SQL  Xexclude from comparisonSurrealDB  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 processingA fully ACID transactional, developer-friendly, multi-model DBMSA 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 DBMSDocument store
Graph DBMS
Search engine
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score18.04
Rank#33  Overall
#20  Relational DBMS
Score1.02
Rank#190  Overall
#33  Document stores
#18  Graph DBMS
Score0.76
Rank#219  Overall
#14  Search engines
Websitespark.apache.org/­sqlsurrealdb.comtypesense.org
Technical documentationspark.apache.org/­docs/­latest/­sql-programming-guide.htmlsurrealdb.com/­docstypesense.org/­docs
DeveloperFatCloudApache Software FoundationSurrealDB Ltd
Initial release2012201420222015
Current release3.5.0 ( 2.13), September 2023v1.5.0, May 2024
License infoCommercial or Open SourcecommercialOpen Source infoApache 2.0Open SourceOpen Source infoGPL V3
Cloud-based only infoOnly available as a cloud servicenononono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageC#ScalaRustC++
Server operating systemsWindowsLinux
OS X
Windows
Linux
macOS
Windows
Linux
Data schemeschema-freeyesschema-freeschema-free infopre-defined schema optional
Typing infopredefined data types such as float or dateyesyesyesyes
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.no
Secondary indexesyesnoyes
SQL infoSupport of SQLno infoVia inetgration in SQL ServerSQL-like DML and DDL statementsSQL-like query languageno
APIs and other access methods.NET Client API
LINQ
RESTful HTTP API
RPC
Windows WCF Bindings
JDBC
ODBC
GraphQL
RESTful HTTP API
WebSocket
RESTful HTTP API
Supported programming languagesC#Java
Python
R
Scala
Deno
Go
JavaScript (Node.js)
Rust
.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 applicationsnono
Triggersyes infovia applicationsno
Partitioning methods infoMethods for storing different data on different nodesShardingyes, utilizing Spark Core
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factornoneMulti-source replication using RAFT
MapReduce infoOffers an API for user-defined Map/Reduce methodsyesnono
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual Consistency
Immediate Consistency
Foreign keys infoReferential integritynonono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanonoACIDno
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
User concepts infoAccess controlno infoCan implement custom security layer via applicationsnoyes, based on authentication and database rules

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More resources
FatDBSpark SQLSurrealDBTypesense
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