DBMS > BigchainDB vs. Firebase Realtime Database vs. Google Cloud Datastore vs. Realm vs. Snowflake

System Properties Comparison BigchainDB vs. Firebase Realtime Database vs. Google Cloud Datastore vs. Realm vs. Snowflake

Editorial information provided by DB-Engines

Name

Description

BigchainDB is scalable blockchain database offering decentralization, immutability and native assets

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

Automatically scaling NoSQL Database as a Service (DBaaS) on the Google Cloud Platform

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

Cloud-based data warehousing service for structured and semi-structured data

Primary database model

Document store

Relational DBMS

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

Score	0.76
Rank	#216	Overall
	#36	Document stores

Score	13.60
Rank	#39	Overall
	#6	Document stores

Score	4.13
Rank	#71	Overall
	#12	Document stores

Score	7.18
Rank	#52	Overall
	#8	Document stores

Score	133.72
Rank	#7	Overall
	#5	Relational DBMS

Website

www.bigchaindb.com

firebase.google.com/products/realtime-database

cloud.google.com/datastore

realm.io

www.snowflake.com

Technical documentation

bigchaindb.readthedocs.io/en/latest

firebase.google.com/docs/database

cloud.google.com/datastore/docs

realm.io/docs

docs.snowflake.net/manuals/index.html

Developer

Google

acquired by Google 2014

Google

Realm, acquired by MongoDB in May 2019

Snowflake Computing Inc.

Initial release

2016

2012

2008

2014

License

Commercial or Open Source

Open Source

AGPL v3

commercial

Open Source

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

Python

Server operating systems

Linux

hosted

Android
Backend: server-less
iOS
Windows

hosted

Data scheme

schema-free

yes

support of semi-structured data formats (JSON, XML, Avro)

Typing

predefined data types such as float or date

yes

yes, details here

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.

yes

Secondary indexes

yes

SQL

Support of SQL

SQL-like query language (GQL)

yes

APIs and other access methods

CLI Client
RESTful HTTP API

Android
iOS
JavaScript API
RESTful HTTP API

gRPC (using protocol buffers) API
RESTful HTTP/JSON API

CLI Client
JDBC
ODBC

Supported programming languages

Go
Haskell
Java
JavaScript
Python
Ruby

Java
JavaScript
Objective-C

.Net
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby

.Net
Java

with Android only
Objective-C
React Native
Swift

JavaScript (Node.js)
Python

Server-side scripts

Stored procedures

limited functionality with using 'rules'

using Google App Engine

runs within the applications so server-side scripts are unnecessary

user defined functions

Triggers

Callbacks are triggered when data changes

Callbacks using the Google Apps Engine

yes

Change Listeners

similar concept for controling cloud resources

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

yes

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor

Multi-source replication using Paxos

none

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

using Google Cloud Dataflow

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency

if the client is offline
Immediate Consistency

if the client is online

Immediate Consistency or Eventual Consistency depending on type of query and configuration

Strong Consistency is default for entity lookups and queries within an Entity Group (but can instead be made eventually consistent). Other queries are always eventual consistent.

Immediate Consistency

Foreign keys

Referential integrity

yes

via ReferenceProperties or Ancestor paths

yes

Transaction concepts

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

yes

ACID

Serializable Isolation within Transactions, Read Committed outside of Transactions

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes,with MongoDB ord RethinkDB

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

yes

yes, based on authentication and database rules

Access rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)

yes

Users with fine-grained authorization concept, user roles and pluggable authentication

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