DBMS > Google Cloud Bigtable vs. Google Cloud Firestore vs. InterSystems Caché

System Properties Comparison Google Cloud Bigtable vs. Google Cloud Firestore vs. InterSystems Caché

Please select another system to include it in the comparison.

Editorial information provided by DB-Engines

Name

Caché is a deprecated database engine which is substituted with InterSystems IRIS. It therefore is removed from the DB-Engines Ranking.

Description

Google's NoSQL Big Data database service. It's the same database that powers many core Google services, including Search, Analytics, Maps, and Gmail.

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 multi-model DBMS and application server

Primary database model

Key-value store
Wide column store

Document store

Key-value store
Object oriented DBMS
Relational DBMS

Secondary database models

Document store

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

Score	2.66
Rank	#92	Overall
	#15	Key-value stores
	#6	Wide column stores

Score	7.51
Rank	#43	Overall
	#7	Document stores

Website

cloud.google.com/bigtable

firebase.google.com/products/firestore

www.intersystems.com/products/cache

Technical documentation

cloud.google.com/bigtable/docs

firebase.google.com/docs/firestore

docs.intersystems.com

Developer

Google

InterSystems

Initial release

2015

2017

1997

Current release

2018.1.4, May 2020

License

Commercial or Open Source

commercial

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.

Server operating systems

hosted

AIX
HP Open VMS
HP-UX
Linux
OS X
Solaris
Windows

Data scheme

schema-free

depending on used data model

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

yes

APIs and other access methods

gRPC (using protocol buffers) API
HappyBase (Python library)
HBase compatible API (Java)

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

.NET Client API
JDBC
ODBC
RESTful HTTP API

Supported programming languages

C#
C++
Go
Java
JavaScript (Node.js)
Python

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

C#
C++
Java

Server-side scripts

Stored procedures

yes, Firebase Rules & Cloud Functions

yes

Triggers

yes, with Cloud Functions

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

Internal replication in Colossus, and regional replication between two clusters in different zones

Multi-source replication

Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Using Cloud Dataflow

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate consistency (for a single cluster), Eventual consistency (for two or more replicated clusters)

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

Atomic single-row operations

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

Access rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)

Access rights for users, groups and roles based on Google Cloud Identity and Access Management. Security Rules for 3rd party authentication using Firebase Auth.

Access rights for users, groups and roles

More information provided by the system vendor

We invite representatives of system vendors to contact us for updating and extending the system information,
and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.

Related products and services

We invite representatives of vendors of related products to contact us for presenting information about their offerings here.

More resources

DB-Engines blog posts

Cloud-based DBMS's popularity grows at high rates
12 December 2019, Paul Andlinger

show all

Recent citations in the news

What’s next for Google Cloud databases? AI inside SQL and more
9 April 2025, VentureBeat

Google Cloud adds graph processing to Spanner, SQL support to Bigtable
1 August 2024, InfoWorld

Google Bigtable
1 March 2022, TechTarget

Google Cloud expands its database portfolio with new AI capabilities
1 August 2024, TechCrunch

Google Introduces Autoscaling for Cloud Bigtable for Optimizing Costs
31 January 2022, infoq.com

provided by Google News

Google Cloud Announces Firestore with MongoDB Compatibility
26 April 2025, infoq.com

Google Cloud Enhances Databases with Firestore and MongoDB Features
28 April 2025, Security Boulevard

What’s next for Google Cloud databases? AI inside SQL and more
9 April 2025, VentureBeat

MWC: DT partners Google Cloud for better RANops using a network AI agent
25 February 2025, Mobile Europe

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

provided by Google News

Contracts for September 21, 2023
21 September 2023, U.S. Department of Defense (.gov)

Associative Data Modeling Demystified – Part1
9 July 2016, Data Science Central

Cast Your Vote for Best Overall Database in the DBTA Readers’ Choice Awards
23 April 2014, Database Trends and Applications

Announcing IBM Spectrum Sentinel: Building a Cyber Resilient Future
24 June 2022, IBM

provided by Google News

Share this page