DBMS > GBase vs. Google Cloud Firestore vs. Interbase vs. NSDb

System Properties Comparison GBase vs. Google Cloud Firestore vs. Interbase vs. NSDb

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Editorial information provided by DB-Engines

Name

Description

Widely used RDBMS in China, including analytical, transactional, distributed transactional, and cloud-native data warehousing.

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.

Light-weight proven RDBMS

originally from Borland

Scalable, High-performance Time Series DBMS designed for Real-time Analytics on top of Kubernetes

Primary database model

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

Score	1.05
Rank	#186	Overall
	#86	Relational DBMS

Score	7.36
Rank	#53	Overall
	#9	Document stores

Score	4.08
Rank	#75	Overall
	#41	Relational DBMS

Score	0.08
Rank	#369	Overall
	#40	Time Series DBMS

Website

www.gbase.cn

firebase.google.com/products/firestore

www.embarcadero.com/products/interbase

nsdb.io

Technical documentation

firebase.google.com/docs/firestore

docs.embarcadero.com/products/interbase

nsdb.io/Architecture

Developer

General Data Technology Co., Ltd.

Google

Embarcadero

Initial release

2004

2017

1984

2017

Current release

GBase 8a, GBase 8s, GBase 8c

InterBase 2020, December 2019

License

Commercial or Open Source

commercial

Open Source

Apache Version 2.0

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, Java, Python

Java, Scala

Server operating systems

Linux

hosted

Android
iOS
Linux
OS X
Windows

Linux
macOS

Data scheme

yes

schema-free

yes

Typing

predefined data types such as float or date

yes

yes: int, bigint, decimal, string

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

export as XML data possible

Secondary indexes

yes

all fields are automatically indexed

SQL

Support of SQL

Standard with numerous extensions

yes

SQL-like query language

APIs and other access methods

ADO.NET
C API
JDBC
ODBC

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

ADO.NET
JDBC
ODBC

gRPC
HTTP REST
WebSocket

Supported programming languages

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

.Net
C
C++
Delphi
Java
Object Pascal
PHP
Ruby

Java
Scala

Server-side scripts

Stored procedures

user defined functions

yes, Firebase Rules & Cloud Functions

yes

Interbase procedure and trigger language

Triggers

yes

yes, with Cloud Functions

yes

Partitioning methods

Methods for storing different data on different nodes

horizontal partitioning (by range, list and hash) and vertical partitioning

Sharding

none

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Multi-source replication

Interbase Change Views

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

Eventual Consistency

Foreign keys

Referential integrity

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

Multiversion concurreny control

yes

Durability

Support for making data persistent

yes

Using Apache Lucene

In-memory capabilities

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

yes

User concepts

Access control

yes

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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More resources

DB-Engines blog posts

Cloud-based DBMS's popularity grows at high rates
12 December 2019, Paul Andlinger

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