DBMS > AgensGraph vs. Google Cloud Firestore vs. Postgres-XL vs. Quasardb

System Properties Comparison AgensGraph vs. Google Cloud Firestore vs. Postgres-XL vs. Quasardb

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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.

Based on PostgreSQL enhanced with MPP and write-scale-out cluster features

Distributed, high-performance timeseries database

Primary database model

Graph DBMS
Relational DBMS

Document store

Relational DBMS

Time Series DBMS

Secondary database models

Document store
Spatial 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	0.49
Rank	#256	Overall
	#117	Relational DBMS

Score	0.14
Rank	#332	Overall
	#29	Time Series DBMS

Website

bitnine.net/agensgraph

firebase.google.com/products/firestore

www.postgres-xl.org

quasar.ai

Technical documentation

bitnine.net/documentation

firebase.google.com/docs/firestore

www.postgres-xl.org/documentation

doc.quasar.ai/master

Developer

Bitnine Global Inc.

Google

quasardb

Initial release

2016

2017

2014

since 2012, originally named StormDB

2009

Current release

2.1, December 2018

10 R1, October 2018

3.14.1, January 2024

License

Commercial or Open Source

Open Source

Apache License 2.0

commercial

Open Source

Mozilla public license

commercial

Free community edition, Non-profit organizations and non-commercial usage are eligible for free licenses

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++

Server operating systems

Linux
OS X
Windows

hosted

Linux
macOS

BSD
Linux
OS X
Windows

Data scheme

depending on used data model

schema-free

yes

schema-free

Typing

predefined data types such as float or date

yes

integer and binary

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

XML type, but no XML query functionality

Secondary indexes

yes

with tags

SQL

Support of SQL

yes

distributed, parallel query execution

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

ADO.NET
JDBC
native C library
ODBC
streaming API for large objects

HTTP API

Supported programming languages

C
Java
JavaScript
Python

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

.Net
C
C++
Delphi
Erlang
Java
JavaScript (Node.js)
Perl
PHP
Python
Tcl

.Net
C
C#
C++
Go
Java
JavaScript (Node.js)
PHP
Python
R

Server-side scripts

Stored procedures

yes

yes, Firebase Rules & Cloud Functions

user defined functions

Triggers

yes, with Cloud Functions

yes

Partitioning methods

Methods for storing different data on different nodes

no, but can be realized using table inheritance

Sharding

horizontal partitioning

Sharding

consistent hashing

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

Multi-source replication

Source-replica replication with selectable replication factor

MapReduce

Offers an API for user-defined Map/Reduce methods

Using Cloud Dataflow

with Hadoop integration

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

yes

ACID

MVCC

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

by using LevelDB

In-memory capabilities

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

yes

Transient mode

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.

fine grained access rights according to SQL-standard

Cryptographically strong user authentication and audit trail

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More resources

DB-Engines blog posts

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12 December 2019, Paul Andlinger

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