DBMS > Amazon DynamoDB vs. Cloudflare Workers KV vs. Galaxybase vs. Google BigQuery vs. HEAVY.AI

System Properties Comparison Amazon DynamoDB vs. Cloudflare Workers KV vs. Galaxybase vs. Google BigQuery vs. HEAVY.AI

Editorial information provided by DB-Engines

Name

Description

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

A global, low-latency, key-value store for applications on Cloudflare with exceptionally high read volumes and low-latency.

Scalable, ACID-compliant native distributed parallel graph platform

Large scale data warehouse service with append-only tables

A high performance, column-oriented RDBMS, specifically developed to harness the massive parallelism of modern CPU and GPU hardware

Primary database model

Document store
Key-value store

Key-value store

Graph DBMS

Relational DBMS

Secondary database models

Spatial DBMS

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	0.39
Rank	#274	Overall
	#39	Key-value stores

Score	0.07
Rank	#377	Overall
	#40	Graph DBMS

Score	58.10
Rank	#19	Overall
	#13	Relational DBMS

Score	1.64
Rank	#145	Overall
	#67	Relational DBMS

Website

aws.amazon.com/dynamodb

www.cloudflare.com/developer-platform/workers-kv

galaxybase.com

cloud.google.com/bigquery

github.com/heavyai/heavydb
www.heavy.ai

Technical documentation

docs.aws.amazon.com/dynamodb

developers.cloudflare.com/kv/api

cloud.google.com/bigquery/docs

docs.heavy.ai

Developer

Amazon

Cloudflare

Chuanglin(Createlink) Technology Co., Ltd 浙江创邻科技有限公司

Google

HEAVY.AI, Inc.

Initial release

2012

2018

2017

2010

2016

Current release

Nov 20, November 2021

5.10, January 2022

License

Commercial or Open Source

commercial

free tier for a limited amount of database operations

commercial

Open Source

Apache Version 2; enterprise edition available

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

C and Java

C++ and CUDA

Server operating systems

hosted

Linux

hosted

Linux

Data scheme

schema-free

Strong typed schema

yes

Typing

predefined data types such as float or date

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.

Secondary indexes

yes

SQL

Support of SQL

yes

APIs and other access methods

RESTful HTTP API

HTTP REST
Proprietary protocol

Browser interface
console (shell)
Graph API (Gremlin)
OpenCypher
Proprietary native API

RESTful HTTP/JSON API

JDBC
ODBC
Thrift
Vega

Supported programming languages

.Net
ColdFusion
Erlang
Groovy
Java
JavaScript
Perl
PHP
Python
Ruby

C
C++
Dart
JavaScript
Kotlin
Python
Rust
Scala

Go
Java
Python

.Net
Java
JavaScript
Objective-C
PHP
Python
Ruby

All languages supporting JDBC/ODBC/Thrift
Python

Server-side scripts

Stored procedures

user defined procedures and functions

user defined functions

in JavaScript

Triggers

yes

by integration with AWS Lambda

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

Sharding

Round robin

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Multi-source replication

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

Eventual Consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

Relationships in graphs

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

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)

Role-based access control

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

Google Cloud Identity & Access Management (IAM)

fine grained access rights according to SQL-standard

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