DBMS > Google Cloud Firestore vs. LeanXcale vs. Rockset vs. YottaDB

System Properties Comparison Google Cloud Firestore vs. LeanXcale vs. Rockset vs. YottaDB

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Editorial information provided by DB-Engines

Name

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 highly scalable full ACID SQL database with fast NoSQL data ingestion and GIS capabilities

A scalable, reliable search and analytics service in the cloud, built on RocksDB

A fast and solid embedded Key-value store

Primary database model

Document store

Key-value store
Relational DBMS

Document store

Key-value store

Secondary database models

Relational DBMS
Search engine

Relational DBMS

using the Octo plugin

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

Score	7.36
Rank	#53	Overall
	#9	Document stores

Score	0.36
Rank	#280	Overall
	#40	Key-value stores
	#129	Relational DBMS

Score	0.82
Rank	#212	Overall
	#36	Document stores

Score	0.28
Rank	#306	Overall
	#44	Key-value stores

Website

firebase.google.com/products/firestore

www.leanxcale.com

rockset.com

yottadb.com

Technical documentation

firebase.google.com/docs/firestore

docs.rockset.com

yottadb.com/resources/documentation

Developer

Google

LeanXcale

Rockset

YottaDB, LLC

Initial release

2017

2015

2019

2001

License

Commercial or Open Source

commercial

Open Source

AGPL 3.0

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++

Server operating systems

hosted

Docker
Linux

Data scheme

schema-free

yes

schema-free

Typing

predefined data types such as float or date

yes

dynamic typing

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.

ingestion from XML files supported

Secondary indexes

yes

all fields are automatically indexed

SQL

Support of SQL

yes

through Apache Derby

Read-only SQL queries, including JOINs

by using the Octo plugin

APIs and other access methods

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

JDBC
Kafka Connector
ODBC
proprietary key/value interface
Spark Connector

HTTP REST

PostgreSQL wire protocol

using the Octo plugin
Proprietary protocol

Supported programming languages

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

C
Java
Scala

Go
Java
JavaScript (Node.js)
Python

C
Go
JavaScript (Node.js)
Lua
M
Perl
Python
Rust

Server-side scripts

Stored procedures

yes, Firebase Rules & Cloud Functions

Triggers

yes, with Cloud Functions

Partitioning methods

Methods for storing different data on different nodes

Sharding

Automatic sharding

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication

yes

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

Foreign keys

Referential integrity

yes

Transaction concepts

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

yes

ACID

optimistic locking

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 and organizations can be defined via Rockset console

Users and groups based on OS-security mechanisms

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Related products and services

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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

Google's AI-First Strategy Brings Vector Support To Cloud Databases
1 March 2024, Forbes

Realtime vs Cloud Firestore: Which Firebase Database to go?
8 March 2024, Appinventiv

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

Google's Cloud-Native NoSQL Database Cloud Firestore Is Now Generally Available
8 February 2019, InfoQ.com

Firestore and Python | NoSQL on Google Cloud
7 August 2020, Towards Data Science

provided by Google News

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