DBMS > Amazon DynamoDB vs. Fauna vs. Google BigQuery vs. RisingWave vs. YottaDB

System Properties Comparison Amazon DynamoDB vs. Fauna vs. Google BigQuery vs. RisingWave vs. YottaDB

Editorial information provided by DB-Engines

Name

Description

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

Fauna provides a web-native interface, with support for GraphQL and custom business logic that integrates seamlessly with the rest of the serverless ecosystem. The underlying globally distributed storage and compute platform is fast, consistent, and reliable, with a modern security infrastructure.

Large scale data warehouse service with append-only tables

A distributed RDBMS for stream processing, wire-compatible with PostgreSQL

A fast and solid embedded Key-value store

Primary database model

Document store
Key-value store

Document store
Graph DBMS
Relational DBMS
Time Series DBMS

Relational DBMS

Key-value store

Secondary database models

Relational DBMS

using the Octo plugin

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

Score	74.45
Rank	#17	Overall
	#3	Document stores
	#2	Key-value stores

Score	1.55
Rank	#151	Overall
	#26	Document stores
	#14	Graph DBMS
	#71	Relational DBMS
	#13	Time Series DBMS

Score	58.10
Rank	#19	Overall
	#13	Relational DBMS

Score	0.64
Rank	#238	Overall
	#110	Relational DBMS

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

Website

aws.amazon.com/dynamodb

fauna.com

cloud.google.com/bigquery

www.risingwave.com/database

yottadb.com

Technical documentation

docs.aws.amazon.com/dynamodb

docs.fauna.com

cloud.google.com/bigquery/docs

docs.risingwave.com/docs/current/intro

yottadb.com/resources/documentation

Developer

Amazon

Fauna, Inc.

Google

RisingWave Labs

YottaDB, LLC

Initial release

2012

2014

2010

2022

2001

Current release

1.2, September 2023

License

Commercial or Open Source

commercial

free tier for a limited amount of database operations

commercial

Open Source

Apache Version 2.0

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

Scala

Rust

Server operating systems

hosted

Docker
Linux
macOS

Docker
Linux

Data scheme

schema-free

yes

schema-free

Typing

predefined data types such as float or date

yes

Standard SQL-types and JSON

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

by using the Octo plugin

APIs and other access methods

RESTful HTTP API

RESTful HTTP/JSON API

JDBC
PostgreSQL wire protocol

PostgreSQL wire protocol

using the Octo plugin
Proprietary protocol

Supported programming languages

.Net
ColdFusion
Erlang
Groovy
Java
JavaScript
Perl
PHP
Python
Ruby

C#
Go
Java
JavaScript
Python
Ruby
Scala
Swift

.Net
Java
JavaScript
Objective-C
PHP
Python
Ruby

Go
Java
JavaScript (Node.js)
Python

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

Server-side scripts

Stored procedures

user defined functions

in JavaScript

UDFs in Python or Java

Triggers

yes

by integration with AWS Lambda

Partitioning methods

Methods for storing different data on different nodes

Sharding

horizontal partitioning

consistent hashing

none

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Multi-source replication

yes

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

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

ACID

Since BigQuery is designed for querying data

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

Identity management, authentication, and access control

Access privileges (owner, writer, reader) on dataset, table or view level

Google Cloud Identity & Access Management (IAM)

Users and Roles

Users and groups based on OS-security mechanisms

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