I have previously used and evaluated MongoDB and MySQL for various projects before choosing AstraDB for my chatbot application. While MongoDB and MySQL are both powerful and popular database solutions, AstraDB stood out for specific reasons in the context of my project.MongoDB, …
We've been super happy with Astra DB. It's been extremely well-suited for our vector search needs as described in previous responses. With Astra DB’s high-performance vector search, Maester’s AI dynamically optimizes responses in real-time, adapting to new user interactions without requiring costly retraining cycles.
From my own perspective and the tasks that I perform on a daily basis, MySQL is perfect. It has a reasonable footprint, is fast enough and offers the security and flexibility I need. Everyone has their preferred applications and, no doubt, for larger data warehouses or more intensive applications, MySQL may have its limits, but for the area that I operate in, it's a great match.
Security: is embedded at each level in MySQL. Authentication mechanisms are in place for configuring user access and even service account access to applications. MySQL is secure enough under the hood to store your sensitive information. Also, additional plugins are available that sit on top of MySQL for even tighter security.
Widely adopted: MySQL is used across the industry and is trusted the most. Therefore, if you face any problems, simply Google it and you shall land in plenty of forums. This is a great relief as when you are in a need of help, you can find it right in your browser.
Lightweight application: MySQL is not a heavy application. However, the data you store in the database can get heavy with time, but as in the configuration and MySql application files, those are not very heavy and can easily be installed on legacy systems as well.
The support team sometimes requires the escalate button pressed on tickets, to get timely responses. I will say, once the ticket is escalated, action is taken.
They require better documentation on the migration of data. The three primary methods for migrating large data volumes are bulk, Cassandra Data Migrator, and ZDM (Zero Downtime Migration Utility). Over time I have become very familiar will all three of these methods; however, through working with the Services team and the support team, it seemed like we were breaking new ground. I feel if the utilities were better documented and included some examples and/or use cases from large data migrations; this process would have been easier. One lesson learned is you likely need to migrate your application servers to the same cloud provider you host Astra on; otherwise, the latency is too large for latency-sensitive applications.
Although you can add the data you require as more and more data is added, the fixity of it becomes more critical.
As the demand, size, and use of the system increase, you may also need to change or acquire more equipment on your servers, although this is an internal inconvenience for the company.
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.
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.
Their response time is fast, in case you do not contact them during business hours, they give a very good follow-up to your case. They also facilitate video calls if necessary for debugging.
The support staff is friendly, knowledgeable, and efficient. I only had to get part way through my explanations before they had a solution. They will walk you through a fix or actually connect in and fix the problem for you--or would if you can allow it. I've done it both ways with them. They are always forthcoming with 'how to do this if it happens again' information. I love working with MySQL support.
Graph, search, analytics, administration, developer tooling, and monitoring are all incorporated into a single platform by Astra DB. Mongo Db is a self-managed infrastructure. Astra DB has Wide column store and Mongo DB has Document store. The best thing is that Astra DB operates on Java while Mongo DB operates on C++
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.
We are well aware of the Cassandra architecture and familiar with the open source tooling that Datastax provides the industry (K8sSandra / Stargate) to scale Cassandra on Kubernetes.
Having prior knowledge of Cassandra / Kubernetes means we know that under the hood Astra is built on infinitely scalable technologies. We trust that the foundations that Astra is built on will scale so we know Astra will scale.
The high availability capabilities of Astra DB can assist in reducing downtime, which is crucial for revenue-generating applications.
The developer-friendly features of Astra DB, as well as support for known query languages, can help expedite development, save development time, and minimize labor costs. This can result in a shorter time to market and a higher ROI.
