Amazon RDS vs Snowflake

Overview

Amazon RDS

Stacks16.2K

Followers10.8K

Votes761

Snowflake

Stacks1.2K

Followers1.2K

Votes27

Amazon RDS vs Snowflake: What are the differences?

Introduction

In this article, we will discuss the key differences between Amazon RDS and Snowflake. Amazon RDS (Relational Database Service) is a managed database service provided by Amazon Web Services (AWS) that makes it easy to set up, operate, and scale a relational database in the cloud. Snowflake, on the other hand, is a cloud-based data warehouse solution that provides a powerful and flexible platform for data analytics.

Database types: While Amazon RDS supports various relational database engines like MySQL, PostgreSQL, Oracle, and SQL Server, Snowflake is specifically designed for data warehousing and does not support other database types. Snowflake's architecture is optimized for handling large-scale data analytics workloads.
Scalability: Amazon RDS allows you to scale your database vertically by increasing the instance size or horizontally by adding read replicas. However, Snowflake offers automatic and elastic scalability without the need for manual intervention. Snowflake automatically scales storage and compute resources based on your workload needs.
Pricing: Amazon RDS follows a pay-as-you-go pricing model, where you pay for the resources you consume. The pricing is based on the database engine, instance type, and storage size. On the other hand, Snowflake follows a usage-based pricing model, where you are billed based on the amount of data stored and the amount of compute resources used for query processing.
Data sharing: Snowflake provides built-in functionality for secure data sharing across different organizations, allowing you to easily share data sets with external parties without the need for data movement. Amazon RDS does not have native data sharing capabilities and requires manual data export and import for sharing data.
Concurrency: Snowflake is designed to support a high level of concurrency, allowing multiple users to query and analyze data concurrently without performance degradation. Amazon RDS also supports concurrency, but the performance may be impacted as the number of concurrent connections increases.
Data processing capabilities: Snowflake provides advanced data processing capabilities, such as support for semi-structured data (JSON, Avro, XML), data masking, data encryption, and automated data optimization. Amazon RDS offers more traditional database functionalities without these advanced features.

In summary, the key differences between Amazon RDS and Snowflake lie in the database types supported, scalability options, pricing models, data sharing capabilities, concurrency support, and data processing capabilities.

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Detailed Comparison

Amazon RDS	Snowflake
Amazon RDS gives you access to the capabilities of a familiar MySQL, Oracle or Microsoft SQL Server database engine. This means that the code, applications, and tools you already use today with your existing databases can be used with Amazon RDS. Amazon RDS automatically patches the database software and backs up your database, storing the backups for a user-defined retention period and enabling point-in-time recovery. You benefit from the flexibility of being able to scale the compute resources or storage capacity associated with your Database Instance (DB Instance) via a single API call.	Snowflake eliminates the administration and management demands of traditional data warehouses and big data platforms. Snowflake is a true data warehouse as a service running on Amazon Web Services (AWS)—no infrastructure to manage and no knobs to turn.
Pre-configured Parameters;Monitoring and Metrics;Automatic Software Patching;Automated Backups;DB Snapshots;DB Event Notifications;Multi-Availability Zone (Multi-AZ) Deployments;Provisioned IOPS;Push-Button Scaling;Automatic Host Replacement;Replication;Isolation and Security	-
Statistics
Stacks 16.2K	Stacks 1.2K
Followers 10.8K	Followers 1.2K
Votes 761	Votes 27
Pros & Cons
Pros 165 Reliable failovers 156 Automated backups 130 Backed by amazon 92 Db snapshots 87 Multi-availability	Pros 7 Public and Private Data Sharing 4 Multicloud 4 User Friendly 4 Good Performance 3 Great Documentation
Integrations
No integrations available	Python Apache Spark Node.js Looker Periscope Mode

What are some alternatives to Amazon RDS, Snowflake?

Google BigQuery

Run super-fast, SQL-like queries against terabytes of data in seconds, using the processing power of Google's infrastructure. Load data with ease. Bulk load your data using Google Cloud Storage or stream it in. Easy access. Access BigQuery by using a browser tool, a command-line tool, or by making calls to the BigQuery REST API with client libraries such as Java, PHP or Python.

Amazon Redshift

It is optimized for data sets ranging from a few hundred gigabytes to a petabyte or more and costs less than $1,000 per terabyte per year, a tenth the cost of most traditional data warehousing solutions.

Qubole

Qubole is a cloud based service that makes big data easy for analysts and data engineers.

Amazon Aurora

Amazon Aurora is a MySQL-compatible, relational database engine that combines the speed and availability of high-end commercial databases with the simplicity and cost-effectiveness of open source databases. Amazon Aurora provides up to five times better performance than MySQL at a price point one tenth that of a commercial database while delivering similar performance and availability.

Amazon EMR

It is used in a variety of applications, including log analysis, data warehousing, machine learning, financial analysis, scientific simulation, and bioinformatics.

Google Cloud SQL

Run the same relational databases you know with their rich extension collections, configuration flags and developer ecosystem, but without the hassle of self management.

ClearDB

ClearDB uses a combination of advanced replication techniques, advanced cluster technology, and layered web services to provide you with a MySQL database that is "smarter" than usual.

Altiscale

we run Apache Hadoop for you. We not only deploy Hadoop, we monitor, manage, fix, and update it for you. Then we take it a step further: We monitor your jobs, notify you when something’s wrong with them, and can help with tuning.

Azure SQL Database

It is the intelligent, scalable, cloud database service that provides the broadest SQL Server engine compatibility and up to a 212% return on investment. It is a database service that can quickly and efficiently scale to meet demand, is automatically highly available, and supports a variety of third party software.

Stitch

Stitch is a simple, powerful ETL service built for software developers. Stitch evolved out of RJMetrics, a widely used business intelligence platform. When RJMetrics was acquired by Magento in 2016, Stitch was launched as its own company.

Related Comparisons

Amazon RDS vs Snowflake: What are the differences?

Introduction

Database types: While Amazon RDS supports various relational database engines like MySQL, PostgreSQL, Oracle, and SQL Server, Snowflake is specifically designed for data warehousing and does not support other database types. Snowflake's architecture is optimized for handling large-scale data analytics workloads.
Scalability: Amazon RDS allows you to scale your database vertically by increasing the instance size or horizontally by adding read replicas. However, Snowflake offers automatic and elastic scalability without the need for manual intervention. Snowflake automatically scales storage and compute resources based on your workload needs.
Pricing: Amazon RDS follows a pay-as-you-go pricing model, where you pay for the resources you consume. The pricing is based on the database engine, instance type, and storage size. On the other hand, Snowflake follows a usage-based pricing model, where you are billed based on the amount of data stored and the amount of compute resources used for query processing.
Data sharing: Snowflake provides built-in functionality for secure data sharing across different organizations, allowing you to easily share data sets with external parties without the need for data movement. Amazon RDS does not have native data sharing capabilities and requires manual data export and import for sharing data.
Concurrency: Snowflake is designed to support a high level of concurrency, allowing multiple users to query and analyze data concurrently without performance degradation. Amazon RDS also supports concurrency, but the performance may be impacted as the number of concurrent connections increases.
Data processing capabilities: Snowflake provides advanced data processing capabilities, such as support for semi-structured data (JSON, Avro, XML), data masking, data encryption, and automated data optimization. Amazon RDS offers more traditional database functionalities without these advanced features.

Amazon RDS vs Snowflake

Overview