DBMS > Amazon DynamoDB vs. Google BigQuery vs. RisingWave vs. SQream DB

System Properties Comparison Amazon DynamoDB vs. Google BigQuery vs. RisingWave vs. SQream DB

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Editorial information provided by DB-Engines

Name

Description

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

Large scale data warehouse service with append-only tables

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

a GPU-based, columnar RDBMS for big data analytics workloads

Primary database model

Document store
Key-value store

Relational 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	58.10
Rank	#19	Overall
	#13	Relational DBMS

Score	0.64
Rank	#238	Overall
	#110	Relational DBMS

Score	0.74
Rank	#224	Overall
	#103	Relational DBMS

Website

aws.amazon.com/dynamodb

cloud.google.com/bigquery

www.risingwave.com/database

sqream.com

Technical documentation

docs.aws.amazon.com/dynamodb

cloud.google.com/bigquery/docs

docs.risingwave.com/docs/current/intro

docs.sqream.com

Developer

Amazon

Google

RisingWave Labs

SQream Technologies

Initial release

2012

2010

2022

2017

Current release

1.2, September 2023

2022.1.6, December 2022

License

Commercial or Open Source

commercial

free tier for a limited amount of database operations

commercial

Open Source

Apache Version 2.0

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

Rust

C++, CUDA, Haskell, Java, Scala

Server operating systems

hosted

Docker
Linux
macOS

Linux

Data scheme

schema-free

yes

Typing

predefined data types such as float or date

yes

Standard SQL-types and JSON

yes, ANSI Standard SQL Types

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

RESTful HTTP/JSON API

JDBC
PostgreSQL wire protocol

.Net
JDBC
ODBC

Supported programming languages

.Net
ColdFusion
Erlang
Groovy
Java
JavaScript
Perl
PHP
Python
Ruby

.Net
Java
JavaScript
Objective-C
PHP
Python
Ruby

Go
Java
JavaScript (Node.js)
Python

C++
Java
JavaScript (Node.js)
Python

Server-side scripts

Stored procedures

user defined functions

in JavaScript

UDFs in Python or Java

user defined functions in Python

Triggers

yes

by integration with AWS Lambda

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

horizontal and vertical partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

yes

none

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

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

Since BigQuery is designed for querying data

ACID

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)

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

Google Cloud Identity & Access Management (IAM)

Users and Roles

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