DBMS > Google Cloud Firestore vs. InterSystems Caché vs. JaguarDB vs. Stardog

System Properties Comparison Google Cloud Firestore vs. InterSystems Caché vs. JaguarDB vs. Stardog

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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

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

Performant, highly scalable DBMS for AI and IoT applications

Enterprise Knowledge Graph platform and graph DBMS with high availability, high performance reasoning, and virtualization

Primary database model

Document store

Key-value store
Object oriented DBMS
Relational DBMS

Key-value store
Vector DBMS

Graph DBMS
RDF store

Secondary database models

Document store

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

Score	7.85
Rank	#51	Overall
	#8	Document stores

Score	0.00
Rank	#383	Overall
	#60	Key-value stores
	#13	Vector DBMS

Score	2.02
Rank	#123	Overall
	#11	Graph DBMS
	#6	RDF stores

Website

firebase.google.com/products/firestore

www.intersystems.com/products/cache

www.jaguardb.com

www.stardog.com

Technical documentation

firebase.google.com/docs/firestore

docs.intersystems.com

www.jaguardb.com/support.html

docs.stardog.com

Developer

Google

InterSystems

DataJaguar, Inc.

Stardog-Union

Initial release

2017

1997

2015

2010

Current release

2018.1.4, May 2020

3.3 July 2023

7.3.0, May 2020

License

Commercial or Open Source

commercial

Open Source

GPL V3.0

commercial

60-day fully-featured trial license; 1-year fully-featured non-commercial use license for academics/students

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++

the server part. Clients available in other languages

Java

Server operating systems

hosted

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

Linux

Linux
macOS
Windows

Data scheme

schema-free

depending on used data model

yes

schema-free and OWL/RDFS-schema support

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

Import/export of XML data possible

Secondary indexes

yes

supports real-time indexing in full-text and geospatial

SQL

Support of SQL

yes

A subset of ANSI SQL is implemented

but no views, foreign keys, triggers

Yes, compatible with all major SQL variants through dedicated BI/SQL Server

APIs and other access methods

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

.NET Client API
JDBC
ODBC
RESTful HTTP API

JDBC
ODBC

GraphQL query language
HTTP API
Jena RDF API
OWL
RDF4J API
Sesame REST HTTP Protocol
SNARL
SPARQL
Spring Data
Stardog Studio
TinkerPop 3

Supported programming languages

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

C#
C++
Java

C
C++
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
Scala

.Net
Clojure
Groovy
Java
JavaScript
Python
Ruby

Server-side scripts

Stored procedures

yes, Firebase Rules & Cloud Functions

yes

user defined functions and aggregates, HTTP Server extensions in Java

Triggers

yes, with Cloud Functions

yes

via event handlers

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication

Source-replica replication

Multi-source replication

Multi-source replication in HA-Cluster

MapReduce

Offers an API for user-defined Map/Reduce methods

Using Cloud Dataflow

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency

Immediate Consistency in HA-Cluster

Foreign keys

Referential integrity

yes

relationships in graphs

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

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

rights management via user accounts

Access rights for users and roles

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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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