Knex.js vs Microsoft SQL Server

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Knex.js

184
406
+ 1
49
Microsoft SQL Server

20K
15.4K
+ 1
540
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Knex.js vs Microsoft SQL Server: What are the differences?

  1. Query Building and ORM: One key difference between Knex.js and Microsoft SQL Server is that Knex.js is a query builder and ORM for Node.js, providing a way to interact with different databases using JavaScript, while Microsoft SQL Server is a relational database management system specifically designed by Microsoft for storing and retrieving data.

  2. Cross-Platform Compatibility: Knex.js is cross-platform compatible, meaning it can be used with different types of databases such as MySQL, PostgreSQL, SQLite, etc., whereas Microsoft SQL Server is a proprietary database management system developed by Microsoft and mainly geared towards Windows operating systems.

  3. Open Source vs Proprietary: Knex.js is an open-source library available under the MIT license, offering flexibility for developers to customize and contribute to the codebase, while Microsoft SQL Server is a proprietary software that requires licensing and does not provide access to its underlying code.

  4. Performance and Scalability: Knex.js may not provide the same level of performance and scalability as Microsoft SQL Server, which has been optimized by Microsoft for large-scale enterprise applications with features like data partitioning, replication, and advanced indexing options.

  5. Learning Curve and Documentation: Knex.js might have a steeper learning curve due to its lower-level interaction with databases compared to the graphical interfaces and user-friendly tools provided by Microsoft SQL Server, but it offers comprehensive documentation and a large community for support and resources.

  6. Deployment and Maintenance: Deploying and maintaining Knex.js can be more straightforward and cost-effective for small to medium projects since it can run on various platforms without requiring specific hardware or licensing fees, unlike Microsoft SQL Server which may require dedicated servers and licensing agreements.

In Summary, Knex.js and Microsoft SQL Server differ in terms of query building capabilities, platform compatibility, licensing models, performance, learning curve, and deployment options.

Advice on Knex.js and Microsoft SQL Server

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:

  1. I need to use either MySQL or PostgreSQL on a Linux based OS. Which would be better for this application?
  2. I have not dealt with a sound based data type before. How do I store that and put it in a table? Thank you.
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Replies (6)

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.

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Aaron Westley
Recommends
on
PostgreSQLPostgreSQL

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.

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Julien DeFrance
Principal Software Engineer at Tophatter · | 3 upvotes · 486.8K views
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on
Amazon AuroraAmazon Aurora

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.

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Christopher Wray
Web Developer at Soltech LLC · | 3 upvotes · 487.2K views
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DirectusDirectus
at

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!

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Recommends
on
PostgreSQLPostgreSQL

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,

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Klaus Nji
Staff Software Engineer at SailPoint Technologies · | 1 upvotes · 486.9K views
Recommends
on
PostgreSQLPostgreSQL

I recommend Postgres as well. Superior performance overall and a more robust architecture.

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Pros of Knex.js
Pros of Microsoft SQL Server
  • 11
    Write once and then connect to almost any sql engine
  • 10
    Faster
  • 8
    Nice api, Migrations/Seeds
  • 7
    Flexibility in what engine you choose
  • 7
    Free
  • 5
    Multi support and easy to use
  • 1
    Simple query API
  • 139
    Reliable and easy to use
  • 101
    High performance
  • 95
    Great with .net
  • 65
    Works well with .net
  • 56
    Easy to maintain
  • 21
    Azure support
  • 17
    Always on
  • 17
    Full Index Support
  • 10
    Enterprise manager is fantastic
  • 9
    In-Memory OLTP Engine
  • 2
    Easy to setup and configure
  • 2
    Security is forefront
  • 1
    Great documentation
  • 1
    Faster Than Oracle
  • 1
    Columnstore indexes
  • 1
    Decent management tools
  • 1
    Docker Delivery
  • 1
    Max numar of connection is 14000

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Cons of Knex.js
Cons of Microsoft SQL Server
    Be the first to leave a con
    • 4
      Expensive Licensing
    • 2
      Microsoft
    • 1
      Data pages is only 8k
    • 1
      Allwayon can loose data in asycronious mode
    • 1
      Replication can loose the data
    • 1
      The maximum number of connections is only 14000 connect

    Sign up to add or upvote consMake informed product decisions

    What is Knex.js?

    Knex.js is a "batteries included" SQL query builder for Postgres, MySQL, MariaDB, SQLite3, and Oracle designed to be flexible, portable, and fun to use. It features both traditional node style callbacks as well as a promise interface for cleaner async flow control, a stream interface, full featured query and schema builders, transaction support (with savepoints), connection pooling and standardized responses between different query clients and dialects.

    What is Microsoft SQL Server?

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

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    What companies use Knex.js?
    What companies use Microsoft SQL Server?
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    What tools integrate with Knex.js?
    What tools integrate with Microsoft SQL Server?

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    What are some alternatives to Knex.js and Microsoft SQL Server?
    Sequelize
    Sequelize is a promise-based ORM for Node.js and io.js. It supports the dialects PostgreSQL, MySQL, MariaDB, SQLite and MSSQL and features solid transaction support, relations, read replication and more.
    MySQL
    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.
    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.
    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.
    Redis
    Redis is an open source (BSD licensed), in-memory data structure store, used as a database, cache, and message broker. Redis provides data structures such as strings, hashes, lists, sets, sorted sets with range queries, bitmaps, hyperloglogs, geospatial indexes, and streams.
    See all alternatives