DBMS > Badger vs. GBase vs. Google Cloud Firestore vs. HugeGraph vs. OpenQM

System Properties Comparison Badger vs. GBase vs. Google Cloud Firestore vs. HugeGraph vs. OpenQM

Editorial information provided by DB-Engines

Name

Description

An embeddable, persistent, simple and fast Key-Value Store, written purely in Go.

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 fast-speed and highly-scalable Graph DBMS

QpenQM is a high-performance, self-tuning, multi-value DBMS

Primary database model

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

Score	0.22
Rank	#320	Overall
	#47	Key-value stores

Score	1.05
Rank	#186	Overall
	#86	Relational DBMS

Score	7.36
Rank	#53	Overall
	#9	Document stores

Score	0.17
Rank	#335	Overall
	#31	Graph DBMS

Score	0.34
Rank	#284	Overall
	#10	Multivalue DBMS

Website

github.com/dgraph-io/badger

www.gbase.cn

firebase.google.com/products/firestore

github.com/hugegraph
hugegraph.apache.org

www.rocketsoftware.com/products/rocket-multivalue-application-development-platform/rocket-open-qm

Technical documentation

godoc.org/github.com/dgraph-io/badger

firebase.google.com/docs/firestore

hugegraph.apache.org/docs

Developer

DGraph Labs

General Data Technology Co., Ltd.

Google

Baidu

Rocket Software, originally Martin Phillips

Initial release

2017

2004

2017

2018

1993

Current release

GBase 8a, GBase 8s, GBase 8c

0.9

3.4-12

License

Commercial or Open Source

Open Source

Apache 2.0

commercial

Open Source

Apache Version 2.0

Open Source

GPLv2, extended commercial license available

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

Server operating systems

BSD
Linux
OS X
Solaris
Windows

Linux

hosted

Linux
macOS
Unix

AIX
FreeBSD
Linux
macOS
Raspberry Pi
Solaris
Windows

Data scheme

schema-free

yes

schema-free

yes

with some exceptions

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.

yes

Secondary indexes

yes

also supports composite index and range index

yes

SQL

Support of SQL

Standard with numerous extensions

APIs and other access methods

ADO.NET
C API
JDBC
ODBC

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

Java API
RESTful HTTP API
TinkerPop Gremlin

Supported programming languages

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

Groovy
Java
Python

.Net
Basic
C
Java
Objective C
PHP
Python

Server-side scripts

Stored procedures

user defined functions

yes, Firebase Rules & Cloud Functions

asynchronous Gremlin script jobs

yes

Triggers

yes

yes, with Cloud Functions

yes

Partitioning methods

Methods for storing different data on different nodes

none

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

Sharding

yes

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

yes

Replication methods

Methods for redundantly storing data on multiple nodes

none

yes

Multi-source replication

yes

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

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

Using Cloud Dataflow

via hugegraph-spark

Consistency concepts

Methods to ensure consistency in a distributed system

none

Immediate Consistency

Eventual Consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

edges in graph

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

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.

Users, roles and permissions

Access rights can be defined down to the item level

More information provided by the system vendor

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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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Recent citations in the news

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Google launches Cloud Firestore, a new document database for app developers
3 October 2017, TechCrunch

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8 February 2019, InfoQ.com

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provided by Google News

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