DBMS > Amazon Neptune vs. Coveo vs. Firebase Realtime Database vs. OrigoDB vs. Riak KV

System Properties Comparison Amazon Neptune vs. Coveo vs. Firebase Realtime Database vs. OrigoDB vs. Riak KV

Editorial information provided by DB-Engines

Name

Description

Fast, reliable graph database built for the cloud

AI-powered hosted search, recommendation and personalization platform providing tools for both low-code and full-code development

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

A fully ACID in-memory object graph database

Distributed, fault tolerant key-value store

Primary database model

Graph DBMS
RDF store

Search engine

Document store

Document store
Object oriented DBMS

Key-value store

with links between data sets and object tags for the creation of secondary indexes

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

Score	2.20
Rank	#119	Overall
	#9	Graph DBMS
	#5	RDF stores

Score	2.28
Rank	#114	Overall
	#11	Search engines

Score	14.29
Rank	#39	Overall
	#6	Document stores

Score	0.00
Rank	#383	Overall
	#53	Document stores
	#20	Object oriented DBMS

Score	4.10
Rank	#82	Overall
	#9	Key-value stores

Website

aws.amazon.com/neptune

www.coveo.com

firebase.google.com/products/realtime-database

origodb.com

Technical documentation

aws.amazon.com/neptune/developer-resources

docs.coveo.com

firebase.google.com/docs/database

origodb.com/docs

www.tiot.jp/riak-docs/riak/kv/latest

Developer

Amazon

Coveo

Google

acquired by Google 2014

Robert Friberg et al

OpenSource, formerly Basho Technologies

Initial release

2017

2012

2009

under the name LiveDB

2009

Current release

3.2.0, December 2022

License

Commercial or Open Source

commercial

Open Source

Apache version 2, commercial enterprise edition

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

Erlang

Server operating systems

hosted

Linux
Windows

Linux
OS X

Data scheme

schema-free

hybrid - fields need to be configured prior to indexing, but relationships can be exploited at query time without pre-configuration

schema-free

yes

schema-free

Typing

predefined data types such as float or date

yes

User defined using .NET types and collections

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.

can be achieved using .NET

Secondary indexes

yes

restricted

SQL

Support of SQL

APIs and other access methods

OpenCypher
RDF 1.1 / SPARQL 1.1
TinkerPop Gremlin

RESTful HTTP API

Android
iOS
JavaScript API
RESTful HTTP API

.NET Client API
HTTP API
LINQ

HTTP API
Native Erlang Interface

Supported programming languages

C#
Go
Java
JavaScript
PHP
Python
Ruby
Scala

C#
Java
JavaScript
Python

Java
JavaScript
Objective-C

.Net

unofficial client library
C#
C++

unofficial client library
Clojure

unofficial client library
Dart

unofficial client library
Erlang
Go

unofficial client library
Groovy

unofficial client library
Haskell

unofficial client library
Java
JavaScript

unofficial client library
Lisp

unofficial client library
Perl

unofficial client library
PHP
Python
Ruby
Scala

unofficial client library
Smalltalk

unofficial client library

Server-side scripts

Stored procedures

limited functionality with using 'rules'

yes

Erlang

Triggers

yes

Callbacks are triggered when data changes

yes

Domain Events

yes

pre-commit hooks and post-commit hooks

Partitioning methods

Methods for storing different data on different nodes

none

yes

horizontal partitioning

client side managed; servers are not synchronized

Sharding

no "single point of failure"

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.

yes

Source-replica replication

selectable replication factor

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency

if the client is offline
Immediate Consistency

if the client is online

Eventual Consistency

Foreign keys

Referential integrity

yes

Relationships in graphs

yes

depending on model

links between data sets can be stored

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

Write ahead log

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)

granular access controls, API key management, content filters

yes, based on authentication and database rules

Role based authorization

yes, using Riak Security

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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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