Azure Databricks is a service available on Microsoft's Azure platform and suite of products. It provides the latest versions of Apache Spark so users can integrate with open source libraries, or spin up clusters and build in a fully managed Apache Spark environment with the global scale and availability of Azure. Clusters are set up, configured, and fine-tuned to ensure reliability and performance without the need for monitoring. The solution includes autoscaling and auto-termination to improve…
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MySQL
Score 8.3 out of 10
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MySQL is a popular open-source relational and embedded database, now owned by Oracle.
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Pricing
Azure Databricks
MySQL
Editions & Modules
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Pricing Offerings
Azure Databricks
MySQL
Free Trial
No
No
Free/Freemium Version
No
No
Premium Consulting/Integration Services
No
No
Entry-level Setup Fee
No setup fee
No setup fee
Additional Details
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More Pricing Information
Community Pulse
Azure Databricks
MySQL
Features
Azure Databricks
MySQL
Platform Connectivity
Comparison of Platform Connectivity features of Product A and Product B
Azure Databricks
7.3
4 Ratings
13% below category average
MySQL
-
Ratings
Connect to Multiple Data Sources
6.14 Ratings
00 Ratings
Extend Existing Data Sources
7.84 Ratings
00 Ratings
Automatic Data Format Detection
7.44 Ratings
00 Ratings
MDM Integration
8.03 Ratings
00 Ratings
Data Exploration
Comparison of Data Exploration features of Product A and Product B
Azure Databricks
6.8
4 Ratings
22% below category average
MySQL
-
Ratings
Visualization
6.04 Ratings
00 Ratings
Interactive Data Analysis
7.63 Ratings
00 Ratings
Data Preparation
Comparison of Data Preparation features of Product A and Product B
Azure Databricks
8.6
4 Ratings
5% above category average
MySQL
-
Ratings
Interactive Data Cleaning and Enrichment
8.24 Ratings
00 Ratings
Data Transformations
9.04 Ratings
00 Ratings
Data Encryption
9.44 Ratings
00 Ratings
Built-in Processors
7.84 Ratings
00 Ratings
Platform Data Modeling
Comparison of Platform Data Modeling features of Product A and Product B
Azure Databricks
8.0
4 Ratings
5% below category average
MySQL
-
Ratings
Multiple Model Development Languages and Tools
6.54 Ratings
00 Ratings
Automated Machine Learning
8.64 Ratings
00 Ratings
Single platform for multiple model development
8.44 Ratings
00 Ratings
Self-Service Model Delivery
8.44 Ratings
00 Ratings
Model Deployment
Comparison of Model Deployment features of Product A and Product B
Centralised notebooks are out directly into production. This can lead to poorly engineered code. It is very good for fast queries and our data team are always able to provide what we ask for. It is a big cost to our business so it is important it runs efficiently and returns on our investment.
MySQL is best suited for applications on platform like high-traffic content-driven websites, small-scale web apps, data warehouses which regards light analytical workloads. However its less suited for areas like enterprise data warehouse, OLAP cubes, large-scale reporting, applications requiring flexible or semi-structured data like event logging systems, product configurations, dynamic forms.
Learning curve: is big. Newbies will face problems in understanding the platform initially. However, with plenty of online resources, one can easily find solutions to problems and learn on the go.
Backup and restore: MySQL is not very seamless. Although the data is never ruptured or missed, the process involved is not very much user-friendly. Maybe, a new command-line interface for only the backup-restore functionality shall be set up again to make this very important step much easier to perform and maintain.
For teaching Databases and SQL, I would definitely continue to use MySQL. It provides a good, solid foundation to learn about databases. Also to learn about the SQL language and how it works with the creation, insertion, deletion, updating, and manipulation of data, tables, and databases. This SQL language is a foundation and can be used to learn many other database related concepts.
The developers are able to switch between Python and SQL in the Notebook which allows the collaboration of SQL analyst and Data scientist. The integration of Mosaic AI allows users to write complex codes in natural languages. Unity catalog has centralized the security and governance features and simplified the process of maintaining it
I give MySQL a 9/10 overall because I really like it but I feel like there are a lot of tech people who would hate it if I gave it a 10/10. I've never had any problems with it or reached any of its limitations but I know a few people who have so I can't give it a 10/10 based on those complaints.
We have never contacted MySQL enterprise support team for any issues related to MySQL. This is because we have been using primarily the MySQL Server community edition and have been using the MySQL support forums for any questions and practical guidance that we needed before and during the technical implementations. Overall, the support community has been very helpful and allowed us to make the most out of the community edition.
I have found Azure Databricks to be much better than Snowflake for handling bigger, diverse data types. Snowflake is much simpler and better for smaller warehousing. The real time processing is much better in Azure Databricks and we have much more language options. Snowflake is more expensive but simpler to use. Both are great for different needs.
MongoDB has a dynamic schema for how data is stored in 'documents' whereas MySQL is more structured with tables, columns, and rows. MongoDB was built for high availability whereas MySQL can be a challenge when it comes to replication of the data and making everything redundant in the event of a DR or outage.