DBMS > Amazon DynamoDB vs. Faircom EDGE vs. Firebase Realtime Database vs. InfluxDB vs. Memgraph

System Properties Comparison Amazon DynamoDB vs. Faircom EDGE vs. Firebase Realtime Database vs. InfluxDB vs. Memgraph

Editorial information provided by DB-Engines

Name

Description

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

FairCom EDGE is an Industry 4.0 solution built to integrate, collect, aggregate and synchronize mission-critical data in edge computing environments

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

DBMS for storing time series, events and metrics

An open source graph database built for real-time streaming and compatible with Neo4j

Primary database model

Document store
Key-value store

Key-value store
Relational DBMS

Document store

Time Series DBMS

Graph DBMS

Secondary database models

Spatial DBMS

with GEO package

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

Score	74.45
Rank	#17	Overall
	#3	Document stores
	#2	Key-value stores

Score	0.09
Rank	#362	Overall
	#53	Key-value stores
	#155	Relational DBMS

Score	13.64
Rank	#39	Overall
	#6	Document stores

Score	24.39
Rank	#28	Overall
	#1	Time Series DBMS

Score	3.19
Rank	#94	Overall
	#8	Graph DBMS

Website

aws.amazon.com/dynamodb

www.faircom.com/products/faircom-edge

firebase.google.com/products/realtime-database

www.influxdata.com/products/influxdb-overview

memgraph.com

Technical documentation

docs.aws.amazon.com/dynamodb

docs.faircom.com/docs/en/UUID-23d4f1fd-d213-f6d5-b92e-9b7475baa14e.html

firebase.google.com/docs/database

docs.influxdata.com/influxdb

memgraph.com/docs

Social network pages

Developer

Amazon

FairCom Corporation

Google

acquired by Google 2014

Memgraph Ltd

Initial release

2012

1979

2012

2013

2017

Current release

V3, October 2020

2.7.6, April 2024

License

Commercial or Open Source

commercial

free tier for a limited amount of database operations

commercial

Restricted, free version available

commercial

Open Source

MIT-License; commercial enterprise version available

Open Source

BSL 1.1; commercial license for enterprise edition available

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

ANSI C, C++

C and C++

Server operating systems

hosted

Android
Linux

ARM, x86
Raspbian
Windows

hosted

Linux
OS X

through Homebrew

Linux

Data scheme

schema-free

Flexible Schema (defined schema, partial schema, schema free)

schema-free

schema-free and schema-optional

Typing

predefined data types such as float or date

yes

yes, ANSI Standard SQL Types

yes

Numeric data and Strings

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

yes

ANSI SQL queries

SQL-like query language

APIs and other access methods

RESTful HTTP API

ADO.NET
Direct SQL
IoT Microservice layer
JDBC
MQTT (Message Queue Telemetry Transport)
ODBC
RESTful HTTP API

Android
iOS
JavaScript API
RESTful HTTP API

HTTP API
JSON over UDP

Bolt protocol
Cypher query language

Supported programming languages

.Net
ColdFusion
Erlang
Groovy
Java
JavaScript
Perl
PHP
Python
Ruby

C
C#
C++
Java
JavaScript
PHP
Python
VB.Net

Java
JavaScript
Objective-C

.Net
Clojure
Erlang
Go
Haskell
Java
JavaScript
JavaScript (Node.js)
Lisp
Perl
PHP
Python
R
Ruby
Rust
Scala

.Net
C
C++
Elixir
Go
Haskell
Java
JavaScript
PHP
Python
Ruby
Scala

Server-side scripts

Stored procedures

yes

.Net, JavaScript, C/C++

limited functionality with using 'rules'

Triggers

yes

by integration with AWS Lambda

yes

Callbacks are triggered when data changes

Partitioning methods

Methods for storing different data on different nodes

Sharding

File partitioning

Customizable business rules for partitioning

Sharding

in enterprise version only

Sharding

dynamic graph partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Synchronous and asynchronous realtime replication based on transaction logs

selectable replication factor

in enterprise version only

Multi-source replication using RAFT

MapReduce

Offers an API for user-defined Map/Reduce methods

may be implemented via Amazon Elastic MapReduce (Amazon EMR)

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency
Immediate Consistency

can be specified for read operations

Immediate Consistency
Tunable Consistency

Eventual Consistency

if the client is offline
Immediate Consistency

if the client is online

Immediate Consistency

Foreign keys

Referential integrity

yes

when using SQL

yes

relationships in graphs

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

ACID

with snapshot isolation

Concurrency

Support for concurrent manipulation of data

yes

across SQL and NoSQL

yes

yes, multi-version concurrency control (MVCC)

Durability

Support for making data persistent

yes

with periodic snapshot and write-ahead logging (WAL) of changes

In-memory capabilities

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

yes

Depending on used storage engine

yes

User concepts

Access control

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

Fine grained user, group and file access rights managed across SQL (per ANSI standard) and NoSQL.

yes, based on authentication and database rules

simple rights management via user accounts

Users, roles and permissions

More information provided by the system vendor

Specific characteristics

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Competitive advantages

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Typical application scenarios

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Key customers

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Market metrics

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Licensing and pricing models

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