DBMS > DataFS vs. GBase vs. Google Cloud Firestore vs. Tkrzw vs. XTDB

System Properties Comparison DataFS vs. GBase vs. Google Cloud Firestore vs. Tkrzw vs. XTDB

Editorial information provided by DB-Engines

Name

Description

All data is stored inside objects which are linked by so-called link attributes. Objects consist of classes which can be extended and de-extended at runtime. Graphs can be defined with a struct.

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.

A concept of libraries, allowing an application program to store and query key-value pairs in a file. Successor of Tokyo Cabinet and Kyoto Cabinet

A general purpose database with bitemporal SQL and Datalog and graph queries

Primary database model

Secondary database models

Graph DBMS

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

Score	0.06
Rank	#354	Overall
	#15	Object oriented DBMS

Score	1.07
Rank	#185	Overall
	#86	Relational DBMS

Score	7.85
Rank	#51	Overall
	#8	Document stores

Score	0.00
Rank	#383	Overall
	#60	Key-value stores

Score	0.11
Rank	#343	Overall
	#46	Document stores

Website

newdatabase.com

www.gbase.cn

firebase.google.com/products/firestore

dbmx.net/tkrzw

github.com/xtdb/xtdb
www.xtdb.com

Technical documentation

dev.mobiland.com/Overview.xsp

firebase.google.com/docs/firestore

www.xtdb.com/docs

Developer

Mobiland AG

General Data Technology Co., Ltd.

Google

Mikio Hirabayashi

Juxt Ltd.

Initial release

2018

2004

2017

2020

2019

Current release

1.1.263, October 2022

GBase 8a, GBase 8s, GBase 8c

0.9.3, August 2020

1.19, September 2021

License

Commercial or Open Source

commercial

Open Source

Apache Version 2.0

Open Source

MIT License

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

C++

Clojure

Server operating systems

Windows

Linux

hosted

Linux
macOS

All OS with a Java 8 (and higher) VM
Linux

Data scheme

Classes, Structs, and Lists are written in proprietary DataTypeDefinitionLanguage (.dtdl) and Objects consisting of those are written in proprietary DataAccessDefinitionLanguage (.dadl)

yes

schema-free

Typing

predefined data types such as float or date

yes

yes, extensible-data-notation format

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

Secondary indexes

yes

SQL

Support of SQL

Standard with numerous extensions

limited SQL, making use of Apache Calcite

APIs and other access methods

.NET Client API
Proprietary client DLL
WinRT client

ADO.NET
C API
JDBC
ODBC

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

HTTP REST
JDBC

Supported programming languages

.Net
C
C#
C++
VB.Net

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

C++
Java
Python
Ruby

Clojure
Java

Server-side scripts

Stored procedures

user defined functions

yes, Firebase Rules & Cloud Functions

Triggers

no, except callback-events from server when changes happened

yes

yes, with Cloud Functions

Partitioning methods

Methods for storing different data on different nodes

Proprietary Sharding system

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

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Multi-source replication

none

yes, each node contains all data

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

Transaction concepts

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

ACID

yes

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

yes, flexibel persistency by using storage technologies like Apache Kafka, RocksDB or LMDB

In-memory capabilities

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

yes

using specific database classes

User concepts

Access control

Windows-Profile

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.

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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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provided by Google News

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