DBMS > Amazon Neptune vs. Blueflood vs. Firebase Realtime Database vs. Infobright

System Properties Comparison Amazon Neptune vs. Blueflood vs. Firebase Realtime Database vs. Infobright

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Editorial information provided by DB-Engines

Name

Description

Fast, reliable graph database built for the cloud

Scalable TimeSeries DBMS based on Cassandra

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

High performant column-oriented DBMS for analytic workloads using MySQL or PostgreSQL as a frontend

Primary database model

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

Score	2.58
Rank	#112	Overall
	#9	Graph DBMS
	#5	RDF stores

Score	0.09
Rank	#353	Overall
	#33	Time Series DBMS

Score	15.00
Rank	#39	Overall
	#6	Document stores

Score	1.00
Rank	#193	Overall
	#90	Relational DBMS

Website

aws.amazon.com/neptune

blueflood.io

firebase.google.com/products/realtime-database

ignitetech.com/softwarelibrary/infobrightdb

Technical documentation

aws.amazon.com/neptune/developer-resources

github.com/rax-maas/blueflood/wiki

firebase.google.com/docs/database

Developer

Amazon

Rackspace

Google

acquired by Google 2014

Ignite Technologies Inc.; formerly InfoBright Inc.

Initial release

2017

2013

2012

2005

License

Commercial or Open Source

commercial

Open Source

Apache 2.0

commercial

The open source (GPLv2) version did not support inserts/updates/deletes and was discontinued with July 2016

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

Java

Server operating systems

hosted

Linux
OS X

hosted

Linux
Windows

Data scheme

schema-free

predefined 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

Knowledge Grid Technology used instead

SQL

Support of SQL

yes

APIs and other access methods

OpenCypher
RDF 1.1 / SPARQL 1.1
TinkerPop Gremlin

HTTP REST

Android
iOS
JavaScript API
RESTful HTTP API

ADO.NET
JDBC
ODBC

Supported programming languages

C#
Go
Java
JavaScript
PHP
Python
Ruby
Scala

Java
JavaScript
Objective-C

.Net
C
C#
C++
D
Eiffel
Erlang
Haskell
Java
Objective-C
OCaml
Perl
PHP
Python
Ruby
Scheme
Tcl

Server-side scripts

Stored procedures

limited functionality with using 'rules'

Triggers

Callbacks are triggered when data changes

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

based on Cassandra

none

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-availability zones high availability, asynchronous replication for up to 15 read replicas within a single region. Global database clusters consists of a primary write DB cluster in one region, and up to five secondary read DB clusters in different regions. Each secondary region can have up to 16 reader instances.

selectable replication factor

based on Cassandra

Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency

based on Cassandra
Immediate Consistency

based on Cassandra

Eventual Consistency

if the client is offline
Immediate Consistency

if the client is online

Immediate Consistency

Foreign keys

Referential integrity

yes

Relationships in graphs

Transaction concepts

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

ACID

yes

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

with encyption-at-rest

yes

In-memory capabilities

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

yes

User concepts

Access control

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

yes, based on authentication and database rules

fine grained access rights according to SQL-standard

exploiting MySQL or PostgreSQL frontend capabilities

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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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Recent citations in the news

Analyze large amounts of graph data to get insights and find trends with Amazon Neptune Analytics | Amazon Web ...
29 November 2023, AWS Blog

Create a Virtual Knowledge Graph with Amazon Neptune and an Amazon S3 data lake | Amazon Web Services
21 February 2024, AWS Blog

Visualize and explore knowledge graphs quickly by connecting metaphactory to Amazon Neptune | Amazon Web ...
22 January 2024, AWS Blog

Improve availability of Amazon Neptune during engine upgrade using blue/green deployment | Amazon Web Services
11 September 2023, AWS Blog

Generate suggestions for leisure activities in real time with Amazon Neptune | Amazon Web Services
6 June 2023, AWS Blog

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