DBMS > Databend vs. DataFS vs. Realm

System Properties Comparison Databend vs. DataFS vs. Realm

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Editorial information provided by DB-Engines

Name

Description

An open-source, elastic, and workload-aware cloud data warehouse designed to meet businesses' massive-scale analytics needs at low cost and with low complexity

All data is stored inside objects which are linked by so-called link attributes. Objects consist of classes which can be extended and de-extended at runtime. Graphs can be defined with a struct.

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

Primary database model

Relational DBMS

Object oriented DBMS

Document store

Secondary database models

Graph DBMS

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

Score	0.28
Rank	#287	Overall
	#131	Relational DBMS

Score	0.02
Rank	#369	Overall
	#18	Object oriented DBMS

Score	7.18
Rank	#52	Overall
	#8	Document stores

Website

github.com/datafuselabs/databend
www.databend.com

newdatabase.com

realm.io

Technical documentation

docs.databend.com

dev.mobiland.com/Overview.xsp

realm.io/docs

Developer

Databend Labs

Mobiland AG

Realm, acquired by MongoDB in May 2019

Initial release

2021

2018

2014

Current release

1.0.59, April 2023

1.1.263, October 2022

License

Commercial or Open Source

Open Source

Apache Version 2.0

commercial

Open Source

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

Rust

Server operating systems

hosted
Linux
macOS

Windows

Android
Backend: server-less
iOS
Windows

Data scheme

yes

Classes, Structs, and Lists are written in proprietary DataTypeDefinitionLanguage (.dtdl) and Objects consisting of those are written in proprietary DataAccessDefinitionLanguage (.dadl)

yes

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

yes

APIs and other access methods

CLI Client
JDBC
RESTful HTTP API

.NET Client API
Proprietary client DLL
WinRT client

Supported programming languages

Go
Java
JavaScript (Node.js)
Python
Rust

.Net
C
C#
C++
VB.Net

.Net
Java

with Android only
Objective-C
React Native
Swift

Server-side scripts

Stored procedures

runs within the applications so server-side scripts are unnecessary

Triggers

no, except callback-events from server when changes happened

yes

Change Listeners

Partitioning methods

Methods for storing different data on different nodes

none

Proprietary Sharding system

none

Replication methods

Methods for redundantly storing data on multiple nodes

none

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

yes

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

Users with fine-grained authorization concept, user roles

Windows-Profile

yes

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