DBMS > EJDB vs. Google Cloud Firestore vs. Ingres vs. Microsoft SQL Server vs. PouchDB

System Properties Comparison EJDB vs. Google Cloud Firestore vs. Ingres vs. Microsoft SQL Server vs. PouchDB

Editorial information provided by DB-Engines

Name

Description

Embeddable document-store database library with JSON representation of queries (in MongoDB style)

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.

Well established RDBMS

Microsofts flagship relational DBMS

JavaScript DBMS with an API inspired by CouchDB

Primary database model

Document store

Relational DBMS

Document store

Secondary database models

Document store
Graph DBMS
Spatial DBMS

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

Score	0.31
Rank	#296	Overall
	#44	Document stores

Score	7.36
Rank	#53	Overall
	#9	Document stores

Score	3.80
Rank	#82	Overall
	#44	Relational DBMS

Score	821.56
Rank	#3	Overall
	#3	Relational DBMS

Score	2.34
Rank	#112	Overall
	#21	Document stores

Website

github.com/Softmotions/ejdb

firebase.google.com/products/firestore

www.actian.com/databases/ingres

www.microsoft.com/en-us/sql-server

pouchdb.com

Technical documentation

github.com/Softmotions/ejdb/blob/master/README.md

firebase.google.com/docs/firestore

docs.actian.com/ingres

learn.microsoft.com/en-US/sql/sql-server

pouchdb.com/guides

Developer

Softmotions

Google

Actian Corporation

Microsoft

Apache Software Foundation

Initial release

2012

2017

1974

originally developed at University Berkely in early 1970s

1989

2012

Current release

11.2, May 2022

SQL Server 2022, November 2022

7.1.1, June 2019

License

Commercial or Open Source

Open Source

GPLv2

commercial

restricted free version is available

Open Source

Cloud-based only

Only available as a cloud service

yes

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Implementation language

C++

JavaScript

Server operating systems

server-less

hosted

AIX
HP Open VMS
HP-UX
Linux
Solaris
Windows

Linux
Windows

server-less, requires a JavaScript environment (browser, Node.js)

Data scheme

schema-free

yes

schema-free

Typing

predefined data types such as float or date

yes

string, integer, double, bool, date, object_id

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.

but tools for importing/exporting data from/to XML-files available

yes

Secondary indexes

yes

via views

SQL

Support of SQL

yes

APIs and other access methods

in-process shared library

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

.NET Client API
JDBC
ODBC
proprietary protocol (OpenAPI)

ADO.NET
JDBC
ODBC
OLE DB
Tabular Data Stream (TDS)

HTTP REST

only for PouchDB Server
JavaScript API

Supported programming languages

Actionscript
C
C#
C++
Go
Java
JavaScript (Node.js)
Lua
Objective-C
Pike
Python
Ruby

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

C#
C++
Delphi
Go
Java
JavaScript (Node.js)
PHP
Python
R
Ruby
Visual Basic

JavaScript

Server-side scripts

Stored procedures

yes, Firebase Rules & Cloud Functions

yes

Transact SQL, .NET languages, R, Python and (with SQL Server 2019) Java

View functions in JavaScript

Triggers

yes, with Cloud Functions

yes

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

horizontal partitioning

Ingres Star to access multiple databases simultaneously

tables can be distributed across several files (horizontal partitioning); sharding through federation

Sharding

with a proxy-based framework, named couchdb-lounge

Replication methods

Methods for redundantly storing data on multiple nodes

none

Multi-source replication

Ingres Replicator

yes, but depending on the SQL-Server Edition

Multi-source replication

also with CouchDB databases
Source-replica replication

also with CouchDB databases

MapReduce

Offers an API for user-defined Map/Reduce methods

Using Cloud Dataflow

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency

Foreign keys

Referential integrity

typically not needed, however similar functionality with collection joins possible

yes

Transaction concepts

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

yes

ACID

Concurrency

Support for concurrent manipulation of data

yes

Read/Write Locking

yes

MVCC

yes

Durability

Support for making data persistent

yes

by using IndexedDB, WebSQL or LevelDB as backend

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.

fine grained access rights according to SQL-standard

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