DBMS > Amazon DynamoDB vs. Fauna vs. Google BigQuery vs. HarperDB vs. Snowflake

System Properties Comparison Amazon DynamoDB vs. Fauna vs. Google BigQuery vs. HarperDB vs. Snowflake

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

HarperDB takes the "stack" out of "tech stack" by combining an ultra-fast document-style data store, in-memory cache, real-time message broker, and your application components into a single distributed technology.

Cloud-based data warehousing service for structured and semi-structured data

Primary database model

Document store
Key-value store

Document store
Graph DBMS
Relational DBMS
Time Series DBMS

Relational DBMS

Document store

Relational DBMS

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

Score	70.06
Rank	#17	Overall
	#3	Document stores
	#2	Key-value stores

Score	1.55
Rank	#143	Overall
	#26	Document stores
	#13	Graph DBMS
	#66	Relational DBMS
	#13	Time Series DBMS

Score	52.67
Rank	#19	Overall
	#13	Relational DBMS

Score	0.55
Rank	#243	Overall
	#38	Document stores

Score	133.72
Rank	#7	Overall
	#5	Relational DBMS

Website

aws.amazon.com/dynamodb

fauna.com

cloud.google.com/bigquery

www.harperdb.io

www.snowflake.com

Technical documentation

docs.aws.amazon.com/dynamodb

docs.fauna.com

cloud.google.com/bigquery/docs

docs.harperdb.io/docs

docs.snowflake.net/manuals/index.html

Developer

Amazon

Fauna, Inc.

Google

HarperDB

Snowflake Computing Inc.

Initial release

2012

2014

2010

2017

2014

Current release

3.1, August 2021

License

Commercial or Open Source

commercial

free tier for a limited amount of database operations

commercial

free community edition available

commercial

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

Node.js

Server operating systems

hosted

Linux
OS X

hosted

Data scheme

schema-free

yes

dynamic schema

yes

support of semi-structured data formats (JSON, XML, Avro)

Typing

predefined data types such as float or date

yes

JSON data types

yes

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.

yes

Secondary indexes

yes

SQL

Support of SQL

yes

SQL-like data manipulation statements

yes

APIs and other access methods

RESTful HTTP API

RESTful HTTP/JSON API

JDBC
ODBC
React Hooks
RESTful HTTP/JSON API
WebSocket

CLI Client
JDBC
ODBC

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

.Net
C
C#
C++
ColdFusion
D
Dart
Delphi
Erlang
Go
Haskell
Java
JavaScript (Node.js)
Lisp
MatLab
Objective C
Perl
PHP
PowerShell
Prolog
Python
R
Ruby
Rust
Scala
Swift

JavaScript (Node.js)
Python

Server-side scripts

Stored procedures

user defined functions

in JavaScript

Custom Functions

since release 3.1

user defined functions

Triggers

yes

by integration with AWS Lambda

similar concept for controling cloud resources

Partitioning methods

Methods for storing different data on different nodes

Sharding

horizontal partitioning

consistent hashing

none

A table resides as a whole on one (or more) nodes in a cluster

yes

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Multi-source replication

yes

the nodes on which a table resides can be defined

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

Atomic execution of specific operations

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

yes, using LMDB

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)

Access rights for users and roles

Users with fine-grained authorization concept, user roles and pluggable authentication

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