DBMS > AgensGraph vs. Google Cloud Firestore vs. mSQL vs. NSDb vs. OrigoDB

System Properties Comparison AgensGraph vs. Google Cloud Firestore vs. mSQL vs. NSDb vs. OrigoDB

Editorial information provided by DB-Engines

Name

Description

Multi-model database supporting relational and graph data models and built upon PostgreSQL

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.

mSQL (Mini SQL) is a simple and lightweight RDBMS

Scalable, High-performance Time Series DBMS designed for Real-time Analytics on top of Kubernetes

A fully ACID in-memory object graph database

Primary database model

Graph DBMS
Relational DBMS

Document store

Relational DBMS

Time Series DBMS

Document store
Object oriented DBMS

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

Score	0.20
Rank	#321	Overall
	#27	Graph DBMS
	#143	Relational DBMS

Score	7.85
Rank	#51	Overall
	#8	Document stores

Score	1.27
Rank	#167	Overall
	#77	Relational DBMS

Score	0.00
Rank	#383	Overall
	#41	Time Series DBMS

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

Website

bitnine.net/agensgraph

firebase.google.com/products/firestore

hughestech.com.au/products/msql

nsdb.io

origodb.com

Technical documentation

bitnine.net/documentation

firebase.google.com/docs/firestore

nsdb.io/Architecture

origodb.com/docs

Developer

Bitnine Global Inc.

Google

Hughes Technologies

Robert Friberg et al

Initial release

2016

2017

1994

2017

2009

under the name LiveDB

Current release

2.1, December 2018

4.4, October 2021

License

Commercial or Open Source

Open Source

Apache License 2.0

commercial

free licenses can be provided

Open Source

Apache Version 2.0

Open Source

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, Scala

Server operating systems

Linux
OS X
Windows

hosted

AIX
HP-UX
Linux
OS X
Solaris SPARC/x86
Windows

Linux
macOS

Linux
Windows

Data scheme

depending on used data model

schema-free

yes

Typing

predefined data types such as float or date

yes

yes: int, bigint, decimal, string

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

all fields are automatically indexed

yes

SQL

Support of SQL

yes

A subset of ANSI SQL is implemented

no subqueries, aggregate functions, views, foreign keys, triggers

SQL-like query language

APIs and other access methods

Cypher Query Language
JDBC

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

JDBC
ODBC

gRPC
HTTP REST
WebSocket

.NET Client API
HTTP API
LINQ

Supported programming languages

C
Java
JavaScript
Python

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

C
C++
Delphi
Java
Perl
PHP
Tcl

Java
Scala

.Net

Server-side scripts

Stored procedures

yes

yes, Firebase Rules & Cloud Functions

yes

Triggers

yes, with Cloud Functions

yes

Domain Events

Partitioning methods

Methods for storing different data on different nodes

no, but can be realized using table inheritance

Sharding

none

Sharding

horizontal partitioning

client side managed; servers are not synchronized

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

Multi-source replication

none

Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

Using Cloud Dataflow

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

none

Eventual Consistency

Foreign keys

Referential integrity

yes

depending on model

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

Using Apache Lucene

yes

Write ahead log

In-memory capabilities

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

yes

User concepts

Access control

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.

Role based authorization

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More resources

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