DBMS > FatDB vs. Realm vs. Spark SQL vs. SWC-DB

System Properties Comparison FatDB vs. Realm vs. Spark SQL vs. SWC-DB

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Editorial information provided by DB-Engines

Name

FatDB/FatCloud has ceased operations as a company with February 2014. FatDB is discontinued and excluded from the ranking.

Description

A .NET NoSQL DBMS that can integrate with and extend SQL Server.

A DBMS built for use on mobile devices that’s a fast, easy to use alternative to SQLite and Core Data

Spark SQL is a component on top of 'Spark Core' for structured data processing

A high performance, scalable Wide Column DBMS

Primary database model

Document store
Key-value store

Document store

Relational DBMS

Wide column store

Secondary database models

Time Series DBMS

DB-Engines Ranking measures the popularity of database management systems
Trend Chart

Score	7.60
Rank	#52	Overall
	#9	Document stores

Score	18.96
Rank	#33	Overall
	#20	Relational DBMS

Score	0.01
Rank	#376	Overall
	#13	Wide column stores

Website

realm.io

spark.apache.org/sql

github.com/kashirin-alex/swc-db
www.swcdb.org

Technical documentation

realm.io/docs

spark.apache.org/docs/latest/sql-programming-guide.html

Developer

FatCloud

Realm, acquired by MongoDB in May 2019

Apache Software Foundation

Alex Kashirin

Initial release

2012

2014

2020

Current release

3.5.0 ( 2.13), September 2023

0.5, April 2021

License

Commercial or Open Source

commercial

Open Source

Apache 2.0

Open Source

GPL V3

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

Providers of DBaaS offerings, please contact us to be listed.

Implementation language

Scala

C++

Server operating systems

Windows

Android
Backend: server-less
iOS
Windows

Linux
OS X
Windows

Linux

Data scheme

schema-free

yes

schema-free

Typing

predefined data types such as float or date

yes

XML support

Some form of processing data in XML format, e.g. support for XML data structures, and/or support for XPath, XQuery or XSLT.

Secondary indexes

yes

SQL

Support of SQL

Via inetgration in SQL Server

SQL-like DML and DDL statements

SQL-like query language

APIs and other access methods

.NET Client API
LINQ
RESTful HTTP API
RPC
Windows WCF Bindings

JDBC
ODBC

Proprietary protocol
Thrift

Supported programming languages

.Net
Java

with Android only
Objective-C
React Native
Swift

Java
Python
R
Scala

C++

Server-side scripts

Stored procedures

yes

via applications

runs within the applications so server-side scripts are unnecessary

Triggers

yes

via applications

yes

Change Listeners

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

yes, utilizing Spark Core

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor

none

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency
Immediate Consistency

Immediate Consistency

Foreign keys

Referential integrity

Transaction concepts

Support to ensure data integrity after non-atomic manipulations of data

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

In-memory capabilities

Is there an option to define some or all structures to be held in-memory only.

yes

In-Memory realm

User concepts

Access control

Can implement custom security layer via applications

yes

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