DBMS > GBase vs. Google Cloud Firestore vs. Ignite vs. JanusGraph

System Properties Comparison GBase vs. Google Cloud Firestore vs. Ignite vs. JanusGraph

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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.

Apache Ignite is a memory-centric distributed database, caching, and processing platform for transactional, analytical, and streaming workloads, delivering in-memory speeds at petabyte scale.

A Graph DBMS optimized for distributed clusters

It was forked from the latest code base of Titan in January 2017

Primary database model

Relational DBMS

Document store

Key-value store
Relational DBMS

Graph DBMS

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

Score	1.07
Rank	#185	Overall
	#86	Relational DBMS

Score	7.85
Rank	#51	Overall
	#8	Document stores

Score	3.16
Rank	#96	Overall
	#15	Key-value stores
	#49	Relational DBMS

Score	1.94
Rank	#129	Overall
	#12	Graph DBMS

Website

www.gbase.cn

firebase.google.com/products/firestore

ignite.apache.org

janusgraph.org

Technical documentation

firebase.google.com/docs/firestore

apacheignite.readme.io/docs

docs.janusgraph.org

Developer

General Data Technology Co., Ltd.

Google

Apache Software Foundation

Linux Foundation; originally developed as Titan by Aurelius

Initial release

2004

2017

2015

2017

Current release

GBase 8a, GBase 8s, GBase 8c

Apache Ignite 2.6

0.6.3, February 2023

License

Commercial or Open Source

commercial

Open Source

Apache 2.0

Open Source

Apache 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

C++, Java, .Net

Java

Server operating systems

Linux

hosted

Linux
OS X
Solaris
Windows

Linux
OS X
Unix
Windows

Data scheme

yes

schema-free

yes

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

SQL

Support of SQL

Standard with numerous extensions

ANSI-99 for query and DML statements, subset of DDL

APIs and other access methods

ADO.NET
C API
JDBC
ODBC

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

HDFS API
Hibernate
JCache
JDBC
ODBC
Proprietary protocol
RESTful HTTP API
Spring Data

Java API
TinkerPop Blueprints
TinkerPop Frames
TinkerPop Gremlin
TinkerPop Rexster

Supported programming languages

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

C#
C++
Java
PHP
Python
Ruby
Scala

Clojure
Java
Python

Server-side scripts

Stored procedures

user defined functions

yes, Firebase Rules & Cloud Functions

yes (compute grid and cache interceptors can be used instead)

yes

Triggers

yes

yes, with Cloud Functions

yes (cache interceptors and events)

yes

Partitioning methods

Methods for storing different data on different nodes

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

Sharding

yes

depending on the used storage backend (e.g. Cassandra, HBase, BerkeleyDB)

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Multi-source replication

yes (replicated cache)

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

Using Cloud Dataflow

yes (compute grid and hadoop accelerator)

yes

via Faunus, a graph analytics engine

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency
Immediate Consistency

Foreign keys

Referential integrity

yes

Relationships in graphs

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

Supports various storage backends: Cassandra, HBase, Berkeley DB, Akiban, Hazelcast

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.

Security Hooks for custom implementations

User authentification and security via Rexster Graph Server

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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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