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Mentat vs Microsoft SQL Server: What are the differences?
## Introduction
Key differences between Mentat and Microsoft SQL Server are outlined below:
1. **Database structure**: Mentat uses a hierarchical database structure, primarily based on nodes and connections, while Microsoft SQL Server follows a relational database model with tables and rows. This fundamental difference affects how data is stored, queried, and managed in each system.
2. **Query language**: Mentat uses MQL (Mentat Query Language) as its query language, specifically designed to navigate through the hierarchical database structure, while Microsoft SQL Server employs T-SQL (Transact-SQL) for interacting with its relational database. The syntax and capabilities of these query languages differ significantly.
3. **Scalability**: Mentat is designed for small to medium-scale applications with a focus on flexibility and ease of use, whereas Microsoft SQL Server is known for its scalability and performance in handling large enterprise-level datasets. The choice between the two systems often depends on the size and growth potential of the organization.
4. **Support for transaction management**: Microsoft SQL Server has robust support for transaction management, ensuring ACID (Atomicity, Consistency, Isolation, Durability) properties, while Mentat provides more lightweight transaction capabilities suitable for simpler applications. This can impact the reliability and integrity of data operations in each system.
5. **Vendor and licensing**: Mentat is an open-source project, offering its database system freely without licensing fees, whereas Microsoft SQL Server is a commercial product that requires licensing for enterprise usage. The decision on which system to adopt can hinge on budget considerations and the level of support required.
6. **Ecosystem and integration**: Microsoft SQL Server has a well-established ecosystem with numerous tools, libraries, and third-party integrations available, making it easier to work with in a diverse technology landscape. In contrast, Mentat may have limitations in terms of ecosystem support and compatibility with other systems, impacting the overall development environment.
## Summary
In summary, the key differences between Mentat and Microsoft SQL Server lie in their database structure, query language, scalability, transaction management, vendor and licensing models, as well as ecosystem and integration capabilities.
I am a Microsoft SQL Server programmer who is a bit out of practice. I have been asked to assist on a new project. The overall purpose is to organize a large number of recordings so that they can be searched. I have an enormous music library but my songs are several hours long. I need to include things like time, date and location of the recording. I don't have a problem with the general database design. I have two primary questions:
- I need to use either MySQL or PostgreSQL on a Linux based OS. Which would be better for this application?
- I have not dealt with a sound based data type before. How do I store that and put it in a table? Thank you.
Hi Erin,
Honestly both databases will do the job just fine. I personally prefer Postgres.
Much more important is how you store the audio. While you could technically use a blob type column, it's really not ideal to be storing audio files which are "several hours long" in a database row. Instead consider storing the audio files in an object store (hosted options include backblaze b2 or aws s3) and persisting the key (which references that object) in your database column.
Hi Erin, Chances are you would want to store the files in a blob type. Both MySQL and Postgres support this. Can you explain a little more about your need to store the files in the database? I may be more effective to store the files on a file system or something like S3. To answer your qustion based on what you are descibing I would slighly lean towards PostgreSQL since it tends to be a little better on the data warehousing side.
Hey Erin! I would recommend checking out Directus before you start work on building your own app for them. I just stumbled upon it, and so far extremely happy with the functionalities. If your client is just looking for a simple web app for their own data, then Directus may be a great option. It offers "database mirroring", so that you can connect it to any database and set up functionality around it!
Hi Erin! First of all, you'd probably want to go with a managed service. Don't spin up your own MySQL installation on your own Linux box. If you are on AWS, thet have different offerings for database services. Standard RDS vs. Aurora. Aurora would be my preferred choice given the benefits it offers, storage optimizations it comes with... etc. Such managed services easily allow you to apply new security patches and upgrades, set up backups, replication... etc. Doing this on your own would either be risky, inefficient, or you might just give up. As far as which database to chose, you'll have the choice between Postgresql, MySQL, Maria DB, SQL Server... etc. I personally would recommend MySQL (latest version available), as the official tooling for it (MySQL Workbench) is great, stable, and moreover free. Other database services exist, I'd recommend you also explore Dynamo DB.
Regardless, you'd certainly only keep high-level records, meta data in Database, and the actual files, most-likely in S3, so that you can keep all options open in terms of what you'll do with them.
Hi Erin,
- Coming from "Big" DB engines, such as Oracle or MSSQL, go for PostgreSQL. You'll get all the features you need with PostgreSQL.
- Your case seems to point to a "NoSQL" or Document Database use case. Since you get covered on this with PostgreSQL which achieves excellent performances on JSON based objects, this is a second reason to choose PostgreSQL. MongoDB might be an excellent option as well if you need "sharding" and excellent map-reduce mechanisms for very massive data sets. You really should investigate the NoSQL option for your use case.
- Starting with AWS Aurora is an excellent advise. since "vendor lock-in" is limited, but I did not check for JSON based object / NoSQL features.
- If you stick to Linux server, the PostgreSQL or MySQL provided with your distribution are straightforward to install (i.e. apt install postgresql). For PostgreSQL, make sure you're comfortable with the pg_hba.conf, especially for IP restrictions & accesses.
Regards,
I recommend Postgres as well. Superior performance overall and a more robust architecture.
Pros of Mentat
Pros of Microsoft SQL Server
- Reliable and easy to use139
- High performance102
- Great with .net95
- Works well with .net65
- Easy to maintain56
- Azure support21
- Full Index Support17
- Always on17
- Enterprise manager is fantastic10
- In-Memory OLTP Engine9
- Easy to setup and configure2
- Security is forefront2
- Faster Than Oracle1
- Decent management tools1
- Great documentation1
- Docker Delivery1
- Columnstore indexes1
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Cons of Mentat
Cons of Microsoft SQL Server
- Expensive Licensing4
- Microsoft2
