MySQL vs Snowflake

Overview

MySQL

Stacks129.6K

Followers108.6K

Votes3.8K

GitHub Stars11.8K

Forks4.1K

Snowflake

Stacks1.2K

Followers1.2K

Votes27

MySQL vs Snowflake: What are the differences?

MySQL is a scalable open-source RDBMS known for its ease of use. Snowflake is a cloud-based data warehousing platform with advanced features for handling large volumes of data. Here are the key differences between MySQL and Snowflake:

Architecture: MySQL is a traditional relational database management system (RDBMS) designed for handling structured data. It follows a client-server architecture and is typically installed and managed on-premises or on cloud-based virtual machines. Snowflake, on the other hand, is a cloud-based data warehouse platform built for handling large volumes of data and performing complex analytics. It uses a distributed architecture that enables scalable and parallel processing by separating compute and storage components.
Scalability and Performance: MySQL is known for its scalability, but it requires manual configuration and management for scaling resources as the data and workload grow. It can handle moderate to large datasets efficiently, but performance may degrade with highly concurrent workloads. Snowflake, being a cloud-based data warehouse, offers built-in scalability and elasticity. It automatically scales resources based on demand to handle massive amounts of data and support high concurrency for complex analytics queries.
Data Storage and Management: MySQL is a database system that stores and manages data in one place. It's flexible and offers different ways to store data. On the other hand, Snowflake separates where data is stored from where it is processed. It can handle big amounts of data quickly and efficiently, making it great for large projects.
Query Language and Analytics Capabilities: MySQL uses SQL (Structured Query Language) as its primary query language. It provides a wide range of SQL functions and supports complex joins, aggregations, and subqueries. However, MySQL may require additional tools or extensions for advanced analytics and data processing. Snowflake also uses SQL for querying data but offers extended support for analytical queries. It provides built-in functions for handling semi-structured data, time-series analysis, and machine learning integration, making it well-suited for advanced analytics and data exploration.
Pricing: MySQL is open-source and free, with optional enterprise support. Snowflake is a subscription-based cloud service with costs based on storage and compute usage.

In summary, MySQL is a reliable and widely-used RDBMS suitable for traditional database applications, while Snowflake is a cloud-based data warehouse platform designed for handling large-scale data analytics and complex queries.

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Advice on MySQL, Snowflake

Kyle

Web Application Developer at Redacted DevWorks

Dec 3, 2019

Decidedon

PostGIS

While there's been some very clever techniques that has allowed non-natively supported geo querying to be performed, it is incredibly slow in the long game and error prone at best.

MySQL finally introduced it's own GEO functions and special indexing operations for GIS type data. I prototyped with this, as MySQL is the most familiar database to me. But no matter what I did with it, how much tuning i'd give it, how much I played with it, the results would come back inconsistent.

It was very disappointing.

I figured, at this point, that SQL Server, being an enterprise solution authored by one of the biggest worldwide software developers in the world, Microsoft, might contain some decent GIS in it.

I was very disappointed.

Postgres is a Database solution i'm still getting familiar with, but I noticed it had no built in support for GIS. So I hilariously didn't pay it too much attention. That was until I stumbled upon PostGIS and my world changed forever.

449k views449k

Comments

Ido

Mar 6, 2020

Decided

My data was inherently hierarchical, but there was not enough content in each level of the hierarchy to justify a relational DB (SQL) with a one-to-many approach. It was also far easier to share data between the frontend (Angular), backend (Node.js) and DB (MongoDB) as they all pass around JSON natively. This allowed me to skip the translation layer from relational to hierarchical. You do need to think about correct indexes in MongoDB, and make sure the objects have finite size. For instance, an object in your DB shouldn't have a property which is an array that grows over time, without limit. In addition, I did use MySQL for other types of data, such as a catalog of products which (a) has a lot of data, (b) flat and not hierarchical, (c) needed very fast queries.

575k views575k

Comments

Navraj

CEO at SuPragma

Apr 16, 2020

Needs adviceon

MySQL

PostgreSQL

I asked my last question incorrectly. Rephrasing it here.

I am looking for the most secure open source database for my project I'm starting: https://github.com/SuPragma/SuPragma/wiki

Which database is more secure? MySQL or PostgreSQL? Are there others I should be considering? Is it possible to change the encryption keys dynamically?

Thanks,

Raj

401k views401k

Comments

Detailed Comparison

MySQL	Snowflake
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.	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.
Statistics
GitHub Stars 11.8K	GitHub Stars -
GitHub Forks 4.1K	GitHub Forks -
Stacks 129.6K	Stacks 1.2K
Followers 108.6K	Followers 1.2K
Votes 3.8K	Votes 27
Pros & Cons
Pros 800 Sql 679 Free 562 Easy 528 Widely used 490 Open source Cons 16 Owned by a company with their own agenda 3 Can't roll back schema changes	Pros 7 Public and Private Data Sharing 4 Multicloud 4 Good Performance 4 User Friendly 3 Great Documentation
Integrations
No integrations available	Python Apache Spark Node.js Looker Periscope Mode

What are some alternatives to MySQL, Snowflake?

MongoDB

MongoDB stores data in JSON-like documents that can vary in structure, offering a dynamic, flexible schema. MongoDB was also designed for high availability and scalability, with built-in replication and auto-sharding.

PostgreSQL

PostgreSQL is an advanced object-relational database management system that supports an extended subset of the SQL standard, including transactions, foreign keys, subqueries, triggers, user-defined types and functions.

Microsoft SQL Server

Microsoft® SQL Server is a database management and analysis system for e-commerce, line-of-business, and data warehousing solutions.

SQLite

SQLite is an embedded SQL database engine. Unlike most other SQL databases, SQLite does not have a separate server process. SQLite reads and writes directly to ordinary disk files. A complete SQL database with multiple tables, indices, triggers, and views, is contained in a single disk file.

Cassandra

Partitioning means that Cassandra can distribute your data across multiple machines in an application-transparent matter. Cassandra will automatically repartition as machines are added and removed from the cluster. Row store means that like relational databases, Cassandra organizes data by rows and columns. The Cassandra Query Language (CQL) is a close relative of SQL.

Memcached

Memcached is an in-memory key-value store for small chunks of arbitrary data (strings, objects) from results of database calls, API calls, or page rendering.

MariaDB

Started by core members of the original MySQL team, MariaDB actively works with outside developers to deliver the most featureful, stable, and sanely licensed open SQL server in the industry. MariaDB is designed as a drop-in replacement of MySQL(R) with more features, new storage engines, fewer bugs, and better performance.

RethinkDB

RethinkDB is built to store JSON documents, and scale to multiple machines with very little effort. It has a pleasant query language that supports really useful queries like table joins and group by, and is easy to setup and learn.

ArangoDB

A distributed free and open-source database with a flexible data model for documents, graphs, and key-values. Build high performance applications using a convenient SQL-like query language or JavaScript extensions.

InfluxDB

InfluxDB is a scalable datastore for metrics, events, and real-time analytics. It has a built-in HTTP API so you don't have to write any server side code to get up and running. InfluxDB is designed to be scalable, simple to install and manage, and fast to get data in and out.

Related Comparisons

Architecture: MySQL is a traditional relational database management system (RDBMS) designed for handling structured data. It follows a client-server architecture and is typically installed and managed on-premises or on cloud-based virtual machines. Snowflake, on the other hand, is a cloud-based data warehouse platform built for handling large volumes of data and performing complex analytics. It uses a distributed architecture that enables scalable and parallel processing by separating compute and storage components.
Scalability and Performance: MySQL is known for its scalability, but it requires manual configuration and management for scaling resources as the data and workload grow. It can handle moderate to large datasets efficiently, but performance may degrade with highly concurrent workloads. Snowflake, being a cloud-based data warehouse, offers built-in scalability and elasticity. It automatically scales resources based on demand to handle massive amounts of data and support high concurrency for complex analytics queries.
Data Storage and Management: MySQL is a database system that stores and manages data in one place. It's flexible and offers different ways to store data. On the other hand, Snowflake separates where data is stored from where it is processed. It can handle big amounts of data quickly and efficiently, making it great for large projects.
Query Language and Analytics Capabilities: MySQL uses SQL (Structured Query Language) as its primary query language. It provides a wide range of SQL functions and supports complex joins, aggregations, and subqueries. However, MySQL may require additional tools or extensions for advanced analytics and data processing. Snowflake also uses SQL for querying data but offers extended support for analytical queries. It provides built-in functions for handling semi-structured data, time-series analysis, and machine learning integration, making it well-suited for advanced analytics and data exploration.
Pricing: MySQL is open-source and free, with optional enterprise support. Snowflake is a subscription-based cloud service with costs based on storage and compute usage.

MySQL vs Snowflake