DBMS > AgensGraph vs. Blazegraph vs. Google Cloud Firestore vs. SQLite

System Properties Comparison AgensGraph vs. Blazegraph vs. Google Cloud Firestore vs. SQLite

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Editorial information provided by DB-Engines

Name

Amazon has acquired Blazegraph's domain and (probably) product. It is said that Amazon Neptune is based on Blazegraph.

Description

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

High-performance graph database supporting Semantic Web (RDF/SPARQL) and Graph Database (tinkerpop3, blueprints, vertex-centric) APIs with scale-out and High Availability.

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.

Widely used embeddable, in-process RDBMS

Primary database model

Graph DBMS
Relational DBMS

Graph DBMS
RDF store

Document store

Relational DBMS

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

Score	0.23
Rank	#315	Overall
	#26	Graph DBMS
	#140	Relational DBMS

Score	0.81
Rank	#213	Overall
	#19	Graph DBMS
	#8	RDF stores

Score	7.36
Rank	#53	Overall
	#9	Document stores

Score	111.41
Rank	#10	Overall
	#7	Relational DBMS

Website

bitnine.net/agensgraph

blazegraph.com

firebase.google.com/products/firestore

www.sqlite.org

Technical documentation

bitnine.net/documentation

wiki.blazegraph.com

firebase.google.com/docs/firestore

www.sqlite.org/docs.html

Developer

Bitnine Global Inc.

Blazegraph

Google

Dwayne Richard Hipp

Initial release

2016

2006

2017

2000

Current release

2.1, December 2018

2.1.5, March 2019

3.46.0 (23 May 2024), May 2024

License

Commercial or Open Source

Open Source

Apache License 2.0

Open Source

extended commercial license available

commercial

Open Source

Public Domain

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

Java

Server operating systems

Linux
OS X
Windows

hosted

server-less

Data scheme

depending on used data model

schema-free

yes

dynamic column types

Typing

predefined data types such as float or date

yes

RDF literal types

yes

not rigid because of 'dynamic typing' concept.

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

SPARQL is used as query language

yes

SQL-92 is not fully supported

APIs and other access methods

Cypher Query Language
JDBC

Java API
RESTful HTTP API
SPARQL QUERY
SPARQL UPDATE
TinkerPop 3

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

ADO.NET

inofficial driver
JDBC

inofficial driver
ODBC

inofficial driver

Supported programming languages

C
Java
JavaScript
Python

.Net
C
C++
Java
JavaScript
PHP
Python
Ruby

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

Actionscript
Ada
Basic
C
C#
C++
D
Delphi
Forth
Fortran
Haskell
Java
JavaScript
Lisp
Lua
MatLab
Objective-C
OCaml
Perl
PHP
PL/SQL
Python
R
Ruby
Scala
Scheme
Smalltalk
Tcl

Server-side scripts

Stored procedures

yes

yes, Firebase Rules & Cloud 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

none

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

yes

Multi-source replication

none

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

Immediate Consistency or Eventual Consistency depending on configuration

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

via file-system locks

Durability

Support for making data persistent

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

fine grained access rights according to SQL-standard

Security and Authentication via Web Application Container (Tomcat, Jetty)

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

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