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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.

  1. 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.

  2. 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.

  3. 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.

  4. 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.

  5. 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.

  6. 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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Pros of Amazon RDS
Pros of Snowflake
  • 165
    Reliable failovers
  • 156
    Automated backups
  • 130
    Backed by amazon
  • 92
    Db snapshots
  • 87
    Multi-availability
  • 30
    Control iops, fast restore to point of time
  • 28
    Security
  • 24
    Elastic
  • 20
    Push-button scaling
  • 20
    Automatic software patching
  • 4
    Replication
  • 3
    Reliable
  • 2
    Isolation
  • 7
    Public and Private Data Sharing
  • 4
    Multicloud
  • 4
    Good Performance
  • 4
    User Friendly
  • 3
    Great Documentation
  • 2
    Serverless
  • 1
    Economical
  • 1
    Usage based billing
  • 1
    Innovative

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What is Amazon RDS?

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.

What is Snowflake?

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.

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Jul 2 2019 at 9:34PM

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What are some alternatives to Amazon RDS and Snowflake?
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.
Apache Aurora
Apache Aurora is a service scheduler that runs on top of Mesos, enabling you to run long-running services that take advantage of Mesos' scalability, fault-tolerance, and resource isolation.
MySQL
The MySQL software delivers a very fast, multi-threaded, multi-user, and robust SQL (Structured Query Language) database server. MySQL Server is intended for mission-critical, heavy-load production systems as well as for embedding into mass-deployed software.
Oracle
Oracle Database is an RDBMS. An RDBMS that implements object-oriented features such as user-defined types, inheritance, and polymorphism is called an object-relational database management system (ORDBMS). Oracle Database has extended the relational model to an object-relational model, making it possible to store complex business models in a relational database.
Heroku Postgres
Heroku Postgres provides a SQL database-as-a-service that lets you focus on building your application instead of messing around with database management.
See all alternatives