DBMS > Amazon DynamoDB vs. Bangdb vs. Google Cloud Firestore vs. searchxml

System Properties Comparison Amazon DynamoDB vs. Bangdb vs. Google Cloud Firestore vs. searchxml

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Editorial information provided by DB-Engines

Name

Description

Hosted, scalable database service by Amazon with the data stored in Amazons cloud

Converged and high performance database for device data, events, time series, document and graph

Cloud Firestore is an auto-scaling document database for storing, syncing, and querying data for mobile and web apps. It offers seamless integration with other Firebase and Google Cloud Platform products.

DBMS for structured and unstructured content wrapped with an application server

Primary database model

Document store
Key-value store

Document store
Graph DBMS
Time Series DBMS

Document store

Native XML DBMS
Search engine

Secondary database models

Spatial DBMS

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

Score	74.07
Rank	#17	Overall
	#3	Document stores
	#2	Key-value stores

Score	0.08
Rank	#347	Overall
	#47	Document stores
	#34	Graph DBMS
	#31	Time Series DBMS

Score	7.85
Rank	#51	Overall
	#8	Document stores

Score	0.00
Rank	#383	Overall
	#7	Native XML DBMS
	#25	Search engines

Website

aws.amazon.com/dynamodb

bangdb.com

firebase.google.com/products/firestore

www.searchxml.net/category/products

Technical documentation

docs.aws.amazon.com/dynamodb

docs.bangdb.com

firebase.google.com/docs/firestore

www.searchxml.net/support/handouts

Developer

Amazon

Sachin Sinha, BangDB

Google

informationpartners gmbh

Initial release

2012

2017

2015

Current release

BangDB 2.0, October 2021

1.0

License

Commercial or Open Source

commercial

free tier for a limited amount of database operations

Open Source

BSD 3

commercial

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

C, C++

C++

Server operating systems

hosted

Linux

hosted

Windows

Data scheme

schema-free

Typing

predefined data types such as float or date

yes

yes: string, long, double, int, geospatial, stream, events

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

secondary, composite, nested, reverse, geospatial

yes

SQL

Support of SQL

SQL like support with command line tool

APIs and other access methods

RESTful HTTP API

Proprietary protocol
RESTful HTTP API

Android
gRPC (using protocol buffers) API
iOS
JavaScript API
RESTful HTTP API

RESTful HTTP API
WebDAV
XQuery
XSLT

Supported programming languages

.Net
ColdFusion
Erlang
Groovy
Java
JavaScript
Perl
PHP
Python
Ruby

C
C#
C++
Java
Python

Go
Java
JavaScript
JavaScript (Node.js)
Objective-C
Python

C++

most other programming languages supported via APIs

Server-side scripts

Stored procedures

yes, Firebase Rules & Cloud Functions

yes

on the application server

Triggers

yes

by integration with AWS Lambda

yes, Notifications (with Streaming only)

yes, with Cloud Functions

Partitioning methods

Methods for storing different data on different nodes

Sharding

Sharding (enterprise version only). P2P based virtual network overlay with consistent hashing and chord algorithm

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

yes

selectable replication factor, Knob for CAP (enterprise version only)

Multi-source replication

yes

sychronisation to multiple collections

MapReduce

Offers an API for user-defined Map/Reduce methods

may be implemented via Amazon Elastic MapReduce (Amazon EMR)

Using Cloud Dataflow

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency
Immediate Consistency

can be specified for read operations

Tunable consistency, set CAP knob accordingly

Immediate Consistency

Foreign keys

Referential integrity

Transaction concepts

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

ACID

ACID across one or more tables within a single AWS account and region

ACID

yes

multiple readers, single writer

Concurrency

Support for concurrent manipulation of data

yes

yes, optimistic concurrency control

yes

Durability

Support for making data persistent

yes

yes, implements WAL (Write ahead log) as well

yes

In-memory capabilities

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

yes, run db with in-memory only mode

User concepts

Access control

Access rights for users and roles can be defined via the AWS Identity and Access Management (IAM)

yes (enterprise version only)

Access rights for users, groups and roles based on Google Cloud Identity and Access Management. Security Rules for 3rd party authentication using Firebase Auth.

Domain, group and role-based access control at the document level and for application services

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