DBMS > Amazon DynamoDB vs. Coveo vs. Firebase Realtime Database vs. H2 vs. XTDB

System Properties Comparison Amazon DynamoDB vs. Coveo vs. Firebase Realtime Database vs. H2 vs. XTDB

Editorial information provided by DB-Engines

Name

Description

Hosted, scalable database service by Amazon with the data stored in Amazons cloud

AI-powered hosted search, recommendation and personalization platform providing tools for both low-code and full-code development

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
Key-value store

Secondary database models

Spatial DBMS

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

Score	74.07
Rank	#17	Overall
	#3	Document stores
	#2	Key-value stores

Score	2.28
Rank	#114	Overall
	#11	Search engines

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/dynamodb

www.coveo.com

firebase.google.com/products/realtime-database

www.h2database.com

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

Technical documentation

docs.aws.amazon.com/dynamodb

docs.coveo.com

firebase.google.com/docs/database

www.h2database.com/html/main.html

www.xtdb.com/docs

Developer

Amazon

Coveo

Google

acquired by Google 2014

Thomas Mueller

Juxt Ltd.

Initial release

2012

2005

2019

Current release

2.2.220, July 2023

1.19, September 2021

License

Commercial or Open Source

commercial

free tier for a limited amount of database operations

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

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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

hybrid - fields need to be configured prior to indexing, but relationships can be exploited at query time without pre-configuration

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

RESTful HTTP API

Android
iOS
JavaScript API
RESTful HTTP API

JDBC
ODBC

HTTP REST
JDBC

Supported programming languages

.Net
ColdFusion
Erlang
Groovy
Java
JavaScript
Perl
PHP
Python
Ruby

C#
Java
JavaScript
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

yes

by integration with AWS Lambda

yes

Callbacks are triggered when data changes

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

yes

none

Replication methods

Methods for redundantly storing data on multiple nodes

yes

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

Eventual Consistency
Immediate Consistency

can be specified for read operations

Immediate Consistency

Eventual Consistency

if the client is offline
Immediate Consistency

if the client is online

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

ACID across one or more tables within a single AWS account and region

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 can be defined via the AWS Identity and Access Management (IAM)

granular access controls, API key management, content filters

yes, based on authentication and database rules

fine grained access rights according to SQL-standard

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