DBMS > Badger vs. Firebase Realtime Database vs. Firebolt vs. Microsoft Azure Synapse Analytics

System Properties Comparison Badger vs. Firebase Realtime Database vs. Firebolt vs. Microsoft Azure Synapse Analytics

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Editorial information provided by DB-Engines

Name

Description

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

Cloud-hosted realtime document store. iOS, Android, and JavaScript clients share one Realtime Database instance and automatically receive updates with the newest data.

Highly scalable cloud data warehouse and analytics product

Forked from Clickhouse

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

Primary database model

Key-value store

Document store

Relational DBMS

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

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

Score	13.64
Rank	#39	Overall
	#6	Document stores

Score	1.73
Rank	#140	Overall
	#63	Relational DBMS

Score	19.93
Rank	#31	Overall
	#19	Relational DBMS

Website

github.com/dgraph-io/badger

firebase.google.com/products/realtime-database

www.firebolt.io

azure.microsoft.com/services/synapse-analytics

Technical documentation

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

firebase.google.com/docs/database

docs.firebolt.io

docs.microsoft.com/azure/synapse-analytics

Developer

DGraph Labs

Google

acquired by Google 2014

Firebolt Analytics Inc.

Microsoft

Initial release

2017

2012

2020

2016

License

Commercial or Open Source

Open Source

Apache 2.0

commercial

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

hosted

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

yes

APIs and other access methods

Android
iOS
JavaScript API
RESTful HTTP API

.Net
ODBC
RESTful HTTP API

ADO.NET
JDBC
ODBC

Supported programming languages

Java
JavaScript
Objective-C

Go
JavaScript (Node.js)
Python

C#
Java
PHP

Server-side scripts

Stored procedures

limited functionality with using 'rules'

Transact SQL

Triggers

Callbacks are triggered when data changes

Partitioning methods

Methods for storing different data on different nodes

none

Sharding, horizontal partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

none

depending on storage layer

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

none

Eventual Consistency

if the client is offline
Immediate Consistency

if the client is online

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

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.

User concepts

Access control

yes, based on authentication and database rules

yes

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More resources

DB-Engines blog posts

Cloud-based DBMS's popularity grows at high rates
12 December 2019, Paul Andlinger

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