DBMS > Firebase Realtime Database vs. HugeGraph vs. ObjectBox vs. openGauss vs. Yanza

System Properties Comparison Firebase Realtime Database vs. HugeGraph vs. ObjectBox vs. openGauss vs. Yanza

Editorial information provided by DB-Engines

Name

Yanza seems to be discontinued. Therefore it is excluded from the DB-Engines Ranking.

Description

Cloud-hosted realtime document store. iOS, Android, and JavaScript clients share one Realtime Database instance and automatically receive updates with the newest data.

A fast-speed and highly-scalable Graph DBMS

Extremely fast embedded database for small devices, IoT and Mobile

An enterprise-class RDBMS compatible with high-performance, high-availability and high-performance originally developed by Huawei

Time Series DBMS for IoT Applications

Primary database model

Secondary database models

Time Series DBMS

Document store
Spatial DBMS

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

Score	14.29
Rank	#39	Overall
	#6	Document stores

Score	0.13
Rank	#336	Overall
	#32	Graph DBMS

Score	1.20
Rank	#170	Overall
	#5	Object oriented DBMS

Score	1.08
Rank	#183	Overall
	#84	Relational DBMS

Website

firebase.google.com/products/realtime-database

github.com/hugegraph
hugegraph.apache.org

objectbox.io

gitee.com/opengauss
opengauss.org

yanza.com

Technical documentation

firebase.google.com/docs/database

hugegraph.apache.org/docs

docs.objectbox.io

docs.opengauss.org/en
gitee.com/opengauss/docs

Developer

Google

acquired by Google 2014

Baidu

ObjectBox Limited

Huawei and openGauss community

Yanza

Initial release

2012

2018

2017

2019

2015

Current release

0.9

3.0, March 2022

License

Commercial or Open Source

commercial

Open Source

Apache Version 2.0

Open Source

Apache License 2.0

Open Source

commercial

free version available

Cloud-based only

Only available as a cloud service

yes

but mainly used as a service provided by Yanza

DBaaS offerings (sponsored links)

Database as a Service

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

Implementation language

Java

C and C++

C, C++, Java

Server operating systems

hosted

Linux
macOS
Unix

Android
iOS
Linux
macOS
Windows

Linux

Windows

Data scheme

schema-free

yes

schema-free

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.

Secondary indexes

yes

also supports composite index and range index

yes

SQL

Support of SQL

ANSI SQL 2011

APIs and other access methods

Android
iOS
JavaScript API
RESTful HTTP API

Java API
RESTful HTTP API
TinkerPop Gremlin

Proprietary native API

JDBC
ODBC

HTTP API

Supported programming languages

Java
JavaScript
Objective-C

Groovy
Java
Python

C
C++
Dart
Go
Java
JavaScript

planned (as of Jan 2019)
Kotlin
Python

planned (as of Jan 2019)
Swift

C
C++
Java

any language that supports HTTP calls

Server-side scripts

Stored procedures

limited functionality with using 'rules'

asynchronous Gremlin script jobs

yes

Triggers

Callbacks are triggered when data changes

yes

Timer and event based

Partitioning methods

Methods for storing different data on different nodes

yes

depending on used storage backend, e.g. Cassandra and HBase

none

horizontal partitioning (by range, list and hash)

none

Replication methods

Methods for redundantly storing data on multiple nodes

yes

depending on used storage backend, e.g. Cassandra and HBase

online/offline synchronization between client and server

Source-replica replication

none

MapReduce

Offers an API for user-defined Map/Reduce methods

via hugegraph-spark

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency

if the client is offline
Immediate Consistency

if the client is online

Eventual Consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

edges in graph

yes

Transaction concepts

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

yes

ACID

Concurrency

Support for concurrent manipulation of data

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

yes, based on authentication and database rules

Users, roles and permissions

yes

Access rights for users, groups and roles according to SQL-standard

More information provided by the system vendor

News

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23 May 2024

On-device Vector Database for Dart/Flutter
21 May 2024

The first On-Device Vector Database: ObjectBox 4.0
16 May 2024

SQLite and SQLite alternatives – a comprehensive overview
7 May 2024

Edge AI: The era of on-device AI
23 April 2024

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More resources

DB-Engines blog posts

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12 December 2019, Paul Andlinger

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