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Microsoft SQL Server vs Mongoose: What are the differences?
Introduction
In this markdown code, I will provide the key differences between Microsoft SQL Server and Mongoose. Microsoft SQL Server is a relational database management system developed by Microsoft, while Mongoose is an object data modeling (ODM) library for MongoDB and Node.js.
Data Structure: Microsoft SQL Server uses a structured data model, where data is organized in tables with predefined schema and relationships between tables. On the other hand, Mongoose is built for NoSQL databases like MongoDB, which use a flexible, document-based data model where data is stored in collections without a fixed schema.
Query Language: Microsoft SQL Server uses SQL (Structured Query Language) for querying and manipulating data. It provides a rich set of SQL features for data retrieval, filtering, sorting, and aggregation. In contrast, Mongoose uses JavaScript-based queries to interact with MongoDB, allowing developers to use the flexibility and power of JavaScript to query and manipulate data.
Transaction Support: Microsoft SQL Server provides full transaction support, allowing multiple operations to be grouped together in a transaction, ensuring that either all operations are successful or none are committed. Mongoose, on the other hand, does not natively support transactions in MongoDB. Although MongoDB supports transactions, Mongoose does not provide an abstraction layer for handling transactions.
Scalability: Microsoft SQL Server is designed for scaling vertically, which means adding more resources (CPU, memory) to a single server to handle increased workload. It supports clustering to increase the performance and availability of the database. In contrast, MongoDB (and therefore Mongoose) is designed for horizontal scalability, which means adding more servers to distribute the workload. It provides sharding mechanisms to scale horizontally by partitioning data across multiple servers.
Schema Flexibility: Microsoft SQL Server uses a rigid schema, where the structure of the database and tables are defined upfront. Any modifications to the schema require altering the database structure. In contrast, Mongoose allows flexible schema design and schema-less data storage in MongoDB. A document in a MongoDB collection can have varying fields and structures, making it easier to accommodate changing requirements.
Compatibility: Microsoft SQL Server is primarily designed for Windows-based systems and has excellent integration with other Microsoft technologies. It supports Windows authentication and Active Directory integration. On the other hand, Mongoose is a library for Node.js, which is cross-platform and can be used on various operating systems. MongoDB, the database used by Mongoose, is also cross-platform and can run on Linux, macOS, and Windows platforms.
In summary, Microsoft SQL Server is a relational database management system with a structured data model, SQL query language, transaction support, vertical scalability, rigid schema, and compatibility with Windows systems. Mongoose, on the other hand, is an ODM library for MongoDB, which uses a flexible document-based data model, JavaScript-based queries, no transaction support in Mongoose itself, horizontal scalability, flexible schema, and compatibility with Node.js and multiple operating systems.
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 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
Pros of Mongoose
- Several bad ideas mixed together17
- Well documented17
- JSON10
- Actually terrible documentation8
- Recommended and used by Valve. See steamworks docs2
- Can be used with passportjs for oauth1
- Yeah1
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Cons of Microsoft SQL Server
- Expensive Licensing4
- Microsoft2
Cons of Mongoose
- Model middleware/hooks are not user friendly3