DBMS > EDB Postgres vs. Google Cloud Firestore vs. Stardog vs. Yaacomo

System Properties Comparison EDB Postgres vs. Google Cloud Firestore vs. Stardog 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

The EDB Postgres Platform is an enterprise-class data management platform based on the open source database PostgreSQL with flexible deployment options and Oracle compatibility features, complemented by tool kits for management, integration, and migration.

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.

Enterprise Knowledge Graph platform and graph DBMS with high availability, high performance reasoning, and virtualization

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

Primary database model

Secondary database models

Document store
Spatial DBMS

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

Score	1.90
Rank	#135	Overall
	#63	Relational DBMS

Score	7.85
Rank	#51	Overall
	#8	Document stores

Score	2.02
Rank	#123	Overall
	#11	Graph DBMS
	#6	RDF stores

Website

www.enterprisedb.com

firebase.google.com/products/firestore

www.stardog.com

yaacomo.com

Technical documentation

www.enterprisedb.com/docs

firebase.google.com/docs/firestore

docs.stardog.com

Developer

EnterpriseDB

Google

Stardog-Union

Q2WEB GmbH

Initial release

2005

2017

2010

2009

Current release

14, December 2021

7.3.0, May 2020

License

Commercial or Open Source

commercial

BSD for PostgreSQL-components

commercial

60-day fully-featured trial license; 1-year fully-featured non-commercial use license for academics/students

commercial

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
Windows

hosted

Linux
macOS
Windows

Android
Linux
Windows

Data scheme

yes

schema-free

schema-free and OWL/RDFS-schema support

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.

yes

specific XML-type available, but no XML query functionality.

Import/export of XML data possible

Secondary indexes

yes

supports real-time indexing in full-text and geospatial

yes

SQL

Support of SQL

yes

standard with numerous extensions

Yes, compatible with all major SQL variants through dedicated BI/SQL Server

yes

APIs and other access methods

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

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

GraphQL query language
HTTP API
Jena RDF API
OWL
RDF4J API
Sesame REST HTTP Protocol
SNARL
SPARQL
Spring Data
Stardog Studio
TinkerPop 3

JDBC
ODBC

Supported programming languages

.Net
C
C++
Delphi
Java
Perl
PHP
Python
Tcl

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

.Net
Clojure
Groovy
Java
JavaScript
Python
Ruby

Server-side scripts

Stored procedures

user defined functions

realized in proprietary language PL/pgSQL or with common languages like Perl, Python, Tcl etc.

yes, Firebase Rules & Cloud Functions

user defined functions and aggregates, HTTP Server extensions in Java

Triggers

yes

yes, with Cloud Functions

yes

via event handlers

yes

Partitioning methods

Methods for storing different data on different nodes

horizontal partitioning

by hash, list or range

Sharding

none

horizontal partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication

Multi-source replication in HA-Cluster

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

Immediate Consistency in HA-Cluster

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, multi-version concurrency control (MVCC)

yes

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

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

Access rights for users and roles

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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