DBMS > Badger vs. FatDB vs. Microsoft Azure Synapse Analytics vs. Realm

System Properties Comparison Badger vs. FatDB vs. Microsoft Azure Synapse Analytics vs. Realm

Please select another system to include it in the comparison.

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

An embeddable, persistent, simple and fast Key-Value Store, written purely in Go.

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

Elastic, large scale data warehouse service leveraging the broad eco-system of SQL Server

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

Primary database model

Key-value store

Document store
Key-value store

Relational DBMS

Document store

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

Score	0.22
Rank	#320	Overall
	#47	Key-value stores

Score	19.93
Rank	#31	Overall
	#19	Relational DBMS

Score	7.41
Rank	#52	Overall
	#8	Document stores

Website

github.com/dgraph-io/badger

azure.microsoft.com/services/synapse-analytics

realm.io

Technical documentation

godoc.org/github.com/dgraph-io/badger

docs.microsoft.com/azure/synapse-analytics

realm.io/docs

Developer

DGraph Labs

FatCloud

Microsoft

Realm, acquired by MongoDB in May 2019

Initial release

2017

2012

2016

2014

License

Commercial or Open Source

Open Source

Apache 2.0

commercial

Open Source

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

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

Implementation language

C++

Server operating systems

BSD
Linux
OS X
Solaris
Windows

Windows

hosted

Android
Backend: server-less
iOS
Windows

Data scheme

schema-free

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

Via inetgration in SQL Server

yes

APIs and other access methods

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

ADO.NET
JDBC
ODBC

Supported programming languages

C#
Java
PHP

.Net
Java

with Android only
Objective-C
React Native
Swift

Server-side scripts

Stored procedures

yes

via applications

Transact SQL

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

none

Sharding

Sharding, horizontal partitioning

none

Replication methods

Methods for redundantly storing data on multiple nodes

none

selectable replication factor

yes

none

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

none

Eventual Consistency
Immediate Consistency

Immediate Consistency

Foreign keys

Referential integrity

docs.microsoft.com/en-us/azure/synapse-analytics/sql-data-warehouse/sql-data-warehouse-table-constraints

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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