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Microsoft SQL Server vs Redis: What are the differences?
Introduction
Microsoft SQL Server and Redis are both powerful database management systems, but they have key differences that set them apart. Here are six specific differences between Microsoft SQL Server and Redis:
Data Structure: The primary difference between Microsoft SQL Server and Redis is their data storage model. SQL Server follows a relational database model, where data is organized into tables with rows and columns, and relationships between the tables are defined using foreign keys. In contrast, Redis is a key-value store that stores data in a simple key-value format, allowing quick and easy storage and retrieval.
Read-Write Speed: Redis is known for its high-performance and fast read-write operations. It is an in-memory database, meaning that data is stored in RAM, which allows for low-latency reads and writes. On the other hand, SQL Server, being a disk-based database, may have slower read and write speeds due to the physical disk I/O operations involved.
Scalability: Redis is highly scalable and can handle large amounts of data and high-throughput workloads with ease. It supports distributed data storage and can be clustered to achieve horizontal scaling. SQL Server, while also capable of scaling through clustering and partitioning, may require additional configuration and optimization to handle large-scale workloads.
Data Persistence: SQL Server ensures data durability by persisting data to disk through transaction logs and write-ahead logs. This makes it suitable for applications where data integrity and recovery are critical. Redis, being an in-memory database, relies on periodic or continuous data persistence mechanisms such as snapshots or append-only logs. While these mechanisms can provide data persistence, they may not offer the same level of durability as SQL Server.
Data Querying and Manipulation: SQL Server is renowned for its powerful querying capabilities using the SQL (Structured Query Language). It supports complex JOIN operations, subqueries, and advanced analytical functions. Redis, on the other hand, provides a limited set of operations for data retrieval and manipulation. While it supports basic querying with commands like GET, SET, and DEL, it does not offer the same level of advanced querying capabilities as SQL Server.
Data Model Flexibility: SQL Server provides a flexible data model, allowing the definition of complex relationships, constraints, and data types. It supports ACID (Atomicity, Consistency, Isolation, Durability) properties, ensuring data integrity. Redis, being a NoSQL database, has a flexible schemaless data model. It allows storing semi-structured data like JSON and provides built-in data types. However, it lacks some of the traditional relational database features like referential integrity and complex transactional capabilities.
In Summary, Microsoft SQL Server and Redis differ in their data storage model, read-write speed, scalability, data persistence mechanisms, querying capabilities, and data model flexibility.
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 performance101
- 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
- Security is forefront2
- Easy to setup and configure2
- Docker Delivery1
- Columnstore indexes1
- Great documentation1
- Faster Than Oracle1
- Decent management tools1
Pros of Redis
- Performance886
- Super fast542
- Ease of use513
- In-memory cache444
- Advanced key-value cache324
- Open source194
- Easy to deploy182
- Stable164
- Free155
- Fast121
- High-Performance42
- High Availability40
- Data Structures35
- Very Scalable32
- Replication24
- Great community22
- Pub/Sub22
- "NoSQL" key-value data store19
- Hashes16
- Sets13
- Sorted Sets11
- NoSQL10
- Lists10
- Async replication9
- BSD licensed9
- Bitmaps8
- Integrates super easy with Sidekiq for Rails background8
- Keys with a limited time-to-live7
- Open Source7
- Lua scripting6
- Strings6
- Awesomeness for Free5
- Hyperloglogs5
- Transactions4
- Outstanding performance4
- Runs server side LUA4
- LRU eviction of keys4
- Feature Rich4
- Written in ANSI C4
- Networked4
- Data structure server3
- Performance & ease of use3
- Dont save data if no subscribers are found2
- Automatic failover2
- Easy to use2
- Temporarily kept on disk2
- Scalable2
- Existing Laravel Integration2
- Channels concept2
- Object [key/value] size each 500 MB2
- Simple2
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Cons of Microsoft SQL Server
- Expensive Licensing4
- Microsoft2
Cons of Redis
- Cannot query objects directly15
- No secondary indexes for non-numeric data types3
- No WAL1