DBMS > Google Cloud Firestore vs. H2 vs. LokiJS vs. Spark SQL vs. XTDB

System Properties Comparison Google Cloud Firestore vs. H2 vs. LokiJS vs. Spark SQL vs. XTDB

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.

Full-featured RDBMS with a small footprint, either embedded into a Java application or used as a database server.

In-memory JavaScript DBMS

Spark SQL is a component on top of 'Spark Core' for structured data processing

A general purpose database with bitemporal SQL and Datalog and graph queries

Primary database model

Secondary database models

Spatial DBMS

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

Score	7.36
Rank	#53	Overall
	#9	Document stores

Score	8.33
Rank	#46	Overall
	#30	Relational DBMS

Score	0.49
Rank	#260	Overall
	#42	Document stores

Score	18.04
Rank	#33	Overall
	#20	Relational DBMS

Score	0.18
Rank	#332	Overall
	#46	Document stores

Website

firebase.google.com/products/firestore

www.h2database.com

github.com/techfort/LokiJS

spark.apache.org/sql

github.com/xtdb/xtdb
www.xtdb.com

Technical documentation

firebase.google.com/docs/firestore

www.h2database.com/html/main.html

techfort.github.io/LokiJS

spark.apache.org/docs/latest/sql-programming-guide.html

www.xtdb.com/docs

Developer

Google

Thomas Mueller

Apache Software Foundation

Juxt Ltd.

Initial release

2017

2005

2014

2019

Current release

2.2.220, July 2023

3.5.0 ( 2.13), September 2023

1.19, September 2021

License

Commercial or Open Source

commercial

Open Source

dual-licence (Mozilla public license, Eclipse public license)

Open Source

Apache 2.0

Open Source

MIT License

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

Java

JavaScript

Scala

Clojure

Server operating systems

hosted

All OS with a Java VM

server-less, requires a JavaScript environment (browser, Node.js)

Linux
OS X
Windows

All OS with a Java 8 (and higher) VM
Linux

Data scheme

schema-free

yes

schema-free

yes

schema-free

Typing

predefined data types such as float or date

yes

yes, extensible-data-notation format

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.

Secondary indexes

yes

via views

yes

SQL

Support of SQL

yes

SQL-like DML and DDL statements

limited SQL, making use of Apache Calcite

APIs and other access methods

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

JDBC
ODBC

JavaScript API

JDBC
ODBC

HTTP REST
JDBC

Supported programming languages

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

Java

JavaScript

Java
Python
R
Scala

Clojure
Java

Server-side scripts

Stored procedures

yes, Firebase Rules & Cloud Functions

Java Stored Procedures and User-Defined Functions

View functions in JavaScript

Triggers

yes, with Cloud Functions

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

yes, utilizing Spark Core

none

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication

With clustering: 2 database servers on different computers operate on identical copies of a database

none

yes, each node contains all data

MapReduce

Offers an API for user-defined Map/Reduce methods

Using Cloud Dataflow

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

none

Foreign keys

Referential integrity

yes

Transaction concepts

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

yes

ACID

atomic operations within a single collection possible

ACID

Concurrency

Support for concurrent manipulation of data

yes

yes, multi-version concurrency control (MVCC)

yes

Durability

Support for making data persistent

yes

Serialization of a DB in a Node.JS/Cordova/PhoneGap environment. Usage of the IndexedDB-API in a browser.

yes

yes, flexibel persistency by using storage technologies like Apache Kafka, RocksDB or LMDB

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.

fine grained access rights according to SQL-standard

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More resources

DB-Engines blog posts

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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

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18 November 2014, iProgrammer

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