DBMS > Amazon DocumentDB vs. Firebase Realtime Database vs. H2 vs. XTDB

System Properties Comparison Amazon DocumentDB vs. Firebase Realtime Database vs. H2 vs. XTDB

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Editorial information provided by DB-Engines

Name

Description

Fast, scalable, highly available, and fully managed MongoDB-compatible database service

Cloud-hosted realtime document store. iOS, Android, and JavaScript clients share one Realtime Database instance and automatically receive updates with the newest data.

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

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

Primary database model

Document store

Relational DBMS

Document store

Secondary database models

Spatial DBMS

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

Score	1.91
Rank	#132	Overall
	#24	Document stores

Score	14.29
Rank	#39	Overall
	#6	Document stores

Score	8.13
Rank	#49	Overall
	#31	Relational DBMS

Score	0.11
Rank	#343	Overall
	#46	Document stores

Website

aws.amazon.com/documentdb

firebase.google.com/products/realtime-database

www.h2database.com

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

Technical documentation

aws.amazon.com/documentdb/resources

firebase.google.com/docs/database

www.h2database.com/html/main.html

www.xtdb.com/docs

Developer

Google

acquired by Google 2014

Thomas Mueller

Juxt Ltd.

Initial release

2019

2012

2005

2019

Current release

2.2.220, July 2023

1.19, September 2021

License

Commercial or Open Source

commercial

Open Source

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

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

Clojure

Server operating systems

hosted

All OS with a Java VM

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

Data scheme

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

SQL

Support of SQL

yes

limited SQL, making use of Apache Calcite

APIs and other access methods

proprietary protocol using JSON (MongoDB compatible)

Android
iOS
JavaScript API
RESTful HTTP API

JDBC
ODBC

HTTP REST
JDBC

Supported programming languages

Go
Java
JavaScript (Node.js)
PHP
Python

Java
JavaScript
Objective-C

Java

Clojure
Java

Server-side scripts

Stored procedures

limited functionality with using 'rules'

Java Stored Procedures and User-Defined Functions

Triggers

Callbacks are triggered when data changes

yes

Partitioning methods

Methods for storing different data on different nodes

none

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-availability zones for high availability, asynchronous replication for up to 15 read replicas

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

yes, each node contains all data

MapReduce

Offers an API for user-defined Map/Reduce methods

may be implemented via Amazon Elastic MapReduce (Amazon EMR)

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency

if the client is offline
Immediate Consistency

if the client is online

Immediate Consistency

Foreign keys

Referential integrity

typically not used, however similar functionality with DBRef possible

yes

Transaction concepts

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

Atomic single-document operations

yes

ACID

Concurrency

Support for concurrent manipulation of data

yes

yes, multi-version concurrency control (MVCC)

yes

Durability

Support for making data persistent

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 and roles

yes, based on authentication and database rules

fine grained access rights according to SQL-standard

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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

Vector search for Amazon DocumentDB (with MongoDB compatibility) is now generally available | Amazon Web Services
29 November 2023, AWS Blog

Reduce cost and improve performance by migrating to Amazon DocumentDB 5.0 | Amazon Web Services
15 April 2024, AWS Blog

AWS announces Amazon DocumentDB I/O-Optimized
21 November 2023, AWS Blog

AWS announces vector search for Amazon DocumentDB
29 November 2023, AWS Blog

Mask sensitive Amazon DocumentDB log data with Amazon CloudWatch Logs data protection | Amazon Web Services
16 April 2024, AWS Blog

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8 March 2024, Appinventiv

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18 March 2024, The Register

Atos cybersecurity blog: Misconfigured Firebase: A real-time cyber threat
18 January 2024, Atos

Hundreds of sites misconfigured Firebase security rules, exposing a total of 125 million pieces of sensitive information
4 May 2024, GIGAZINE（ギガジン）

Google Firebase may have exposed 125M records from misconfigurations
19 March 2024, SC Media

provided by Google News

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