DBMS > Google Cloud Firestore vs. Microsoft Azure Table Storage vs. OpenEdge vs. OrigoDB vs. SAP HANA

System Properties Comparison Google Cloud Firestore vs. Microsoft Azure Table Storage vs. OpenEdge vs. OrigoDB vs. SAP HANA

Editorial information provided by DB-Engines

Name

Description

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.

A Wide Column Store for rapid development using massive semi-structured datasets

Application development environment with integrated database management system

A fully ACID in-memory object graph database

In-memory, column based data store. Available as appliance or cloud service

Primary database model

Document store

Wide column store

Relational DBMS

Document store
Object oriented DBMS

Relational DBMS

Secondary database models

Document store
Graph DBMS

with SAP Hana, Enterprise Edition
Spatial DBMS

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

Score	7.85
Rank	#51	Overall
	#8	Document stores

Score	4.48
Rank	#75	Overall
	#6	Wide column stores

Score	3.51
Rank	#86	Overall
	#46	Relational DBMS

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

Score	44.69
Rank	#22	Overall
	#16	Relational DBMS

Website

firebase.google.com/products/firestore

azure.microsoft.com/en-us/services/storage/tables

www.progress.com/openedge

origodb.com

www.sap.com/products/hana.html

Technical documentation

firebase.google.com/docs/firestore

documentation.progress.com/output/ua/OpenEdge_latest

origodb.com/docs

help.sap.com/hana

Developer

Google

Microsoft

Progress Software Corporation

Robert Friberg et al

SAP

Initial release

2017

2012

1984

2009

under the name LiveDB

2010

Current release

OpenEdge 12.2, March 2020

2.0 SPS07 (April 4, 2023), April 2023

License

Commercial or Open Source

commercial

Open Source

commercial

Cloud-based only

Only available as a cloud service

yes

also available as a cloud based service

DBaaS offerings (sponsored links)

Database as a Service

Providers of DBaaS offerings, please contact us to be listed.

Implementation language

Server operating systems

hosted

AIX
HP-UX
Linux
Solaris
Windows

Linux
Windows

Appliance or cloud-service

Data scheme

schema-free

yes

Typing

predefined data types such as float or date

yes

User defined using .NET types and collections

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

can be achieved using .NET

Secondary indexes

yes

SQL

Support of SQL

yes

close to SQL 92

yes

APIs and other access methods

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

RESTful HTTP API

JDBC
ODBC

.NET Client API
HTTP API
LINQ

JDBC
ODBC

Supported programming languages

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

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

Progress proprietary ABL (Advanced Business Language)

.Net

Server-side scripts

Stored procedures

yes, Firebase Rules & Cloud Functions

yes

SQLScript, R

Triggers

yes, with Cloud Functions

yes

Domain Events

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

Implicit feature of the cloud service

horizontal partitioning

since Version 11.4

horizontal partitioning

client side managed; servers are not synchronized

yes

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication

yes

implicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.

Source-replica replication

yes

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

Foreign keys

Referential integrity

yes

depending on model

yes

Transaction concepts

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

yes

optimistic locking

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

Write ahead log

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

Access rights based on private key authentication or shared access signatures

Users and groups

Role based authorization

yes

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