DBMS > Amazon Neptune vs. EsgynDB vs. Google Cloud Firestore vs. Yaacomo

System Properties Comparison Amazon Neptune vs. EsgynDB vs. Google Cloud Firestore vs. Yaacomo

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Editorial information provided by DB-Engines

Name

Yaacomo seems to be discontinued and is removed from the DB-Engines ranking

Description

Fast, reliable graph database built for the cloud

Enterprise-class SQL-on-Hadoop solution, powered by Apache Trafodion

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.

OpenCL based in-memory RDBMS, designed for efficiently utilizing the hardware via parallel computing

Primary database model

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

Score	2.29
Rank	#113	Overall
	#9	Graph DBMS
	#5	RDF stores

Score	0.25
Rank	#312	Overall
	#138	Relational DBMS

Score	7.36
Rank	#53	Overall
	#9	Document stores

Website

aws.amazon.com/neptune

www.esgyn.cn

firebase.google.com/products/firestore

yaacomo.com

Technical documentation

aws.amazon.com/neptune/developer-resources

firebase.google.com/docs/firestore

Developer

Amazon

Esgyn

Google

Q2WEB GmbH

Initial release

2017

2015

2017

2009

License

Commercial or 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

C++, Java

Server operating systems

hosted

Linux

hosted

Android
Linux
Windows

Data scheme

schema-free

yes

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

SQL

Support of SQL

yes

APIs and other access methods

OpenCypher
RDF 1.1 / SPARQL 1.1
TinkerPop Gremlin

ADO.NET
JDBC
ODBC

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

JDBC
ODBC

Supported programming languages

C#
Go
Java
JavaScript
PHP
Python
Ruby
Scala

All languages supporting JDBC/ODBC/ADO.Net

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

Server-side scripts

Stored procedures

Java Stored Procedures

yes, Firebase Rules & Cloud Functions

Triggers

yes, with Cloud Functions

yes

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

horizontal partitioning

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.

Multi-source replication between multi datacenters

Multi-source replication

Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Using Cloud Dataflow

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Foreign keys

Referential integrity

yes

Relationships in graphs

yes

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)

fine grained access rights according to SQL-standard

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

fine grained access rights according to SQL-standard

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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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