DBMS > Couchbase vs. Google Cloud Firestore vs. GridGain vs. ObjectBox

System Properties Comparison Couchbase vs. Google Cloud Firestore vs. GridGain vs. ObjectBox

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Editorial information provided by DB-Engines

Name

Description

A distributed document store with integrated cache, a powerful search engine, in-built operational and analytical capabilities, and an embedded mobile database

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.

GridGain is an in-memory computing platform, built on Apache Ignite

Lightweight, fast on-device database for IoT, Mobile and Embedded devices, persisting and synchronising objects and vectors

Primary database model

Document store

Key-value store
Relational DBMS

Object oriented DBMS
Vector DBMS

Secondary database models

Key-value store

originating from the former Membase product and supporting the Memcached protocol
Spatial DBMS

using the Geocouch extension
Search engine
Time Series DBMS
Vector DBMS

Time Series DBMS

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

Score	16.59
Rank	#36	Overall
	#5	Document stores

Score	7.36
Rank	#53	Overall
	#9	Document stores

Score	1.55
Rank	#150	Overall
	#26	Key-value stores
	#70	Relational DBMS

Score	1.29
Rank	#166	Overall
	#5	Object oriented DBMS
	#7	Vector DBMS

Website

www.couchbase.com

firebase.google.com/products/firestore

www.gridgain.com

github.com/objectbox
objectbox.io

Technical documentation

docs.couchbase.com

firebase.google.com/docs/firestore

www.gridgain.com/docs/index.html

docs.objectbox.io

Developer

Couchbase, Inc.

Google

GridGain Systems, Inc.

ObjectBox Limited

Initial release

2011

2017

2007

2017

Current release

Server: 7.2, June 2023; Mobile: 3.1, March 2022; Couchbase Capella (DBaaS), June 2023

GridGain 8.5.1

4.0 (May 2024)

License

Commercial or Open Source

Open Source

Business Source License (BSL 1.1); Commercial licenses also available

commercial

Bindings are released under Apache 2.0

Apache License 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, C++, Go and Erlang

Java, C++, .Net

C and C++

Server operating systems

Linux
OS X
Windows

hosted

Linux
OS X
Solaris
Windows

Android
Any POSIX system
Docker
iOS
Linux
macOS
QNX
Windows

Data scheme

schema-free

yes

Typing

predefined data types such as float or date

yes

yes, plus "flex" map-like types

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

SQL++, extends ANSI SQL to JSON for operational, transactional, and analytic use cases

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

APIs and other access methods

CLI Client
HTTP REST
Kafka Connector
Native language bindings for CRUD, Query, Search and Analytics APIs
Spark Connector
Spring Data

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

Proprietary native API

Supported programming languages

.Net
C
Go
Java
JavaScript

Node.js
Kotlin
PHP
Python
Ruby
Scala

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

C#
C++
Java
PHP
Python
Ruby
Scala

C
C++
Dart (Flutter)
Go
Java
Kotlin
Python
Swift

Server-side scripts

Stored procedures

Functions and timers in JavaScript and UDFs in Java, Python, SQL++

yes, Firebase Rules & Cloud Functions

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

Triggers

yes

via the TAP protocol

yes, with Cloud Functions

yes (cache interceptors and events)

Partitioning methods

Methods for storing different data on different nodes

Automatic Sharding

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication

including cross data center replication
Source-replica replication

Multi-source replication

yes (replicated cache)

Data sync between devices allowing occasional connected databases to work completely offline

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Using Cloud Dataflow

yes (compute grid and hadoop accelerator)

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency
Immediate Consistency

selectable on a per-operation basis

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

In-memory capabilities

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

yes

Ephemeral buckets

yes

User concepts

Access control

User and Administrator separation with password-based and LDAP integrated Authentication. Role-base access control.

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

yes

More information provided by the system vendor

News

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29 May 2024

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28 May 2024

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23 May 2024

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

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