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MemSQL vs Microsoft SQL Server: What are the differences?
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- Database Architecture: MemSQL is a distributed, in-memory, columnar database designed for real-time analytics, while Microsoft SQL Server is a traditional disk-based relational database management system. MemSQL uses lock-free data structures and parallel processing to achieve high performance, whereas SQL Server relies on traditional disk I/O operations.
- Scalability: MemSQL is highly scalable and can easily scale out by adding more nodes to the cluster to handle increased workload. On the other hand, SQL Server has limitations in terms of scalability due to its monolithic architecture and reliance on a single server instance for processing.
- Real-Time Analytics: MemSQL is optimized for real-time analytics by supporting both transactional and analytical workloads in one system, enabling users to run complex queries on live data with minimal latency. SQL Server, while capable of handling analytical workloads, may not provide the same level of real-time performance as MemSQL.
- Data Processing Speed: MemSQL is known for its high-speed data processing capabilities, achieved through an in-memory architecture and parallel processing of queries. SQL Server, while efficient for traditional OLTP operations, may not match the data processing speed of MemSQL for analytical workloads.
- High Availability: MemSQL offers built-in high availability features such as automatic failover and data replication to ensure data consistency and minimize downtime. SQL Server also provides high availability options, but they may require additional configurations and maintenance compared to MemSQL's out-of-the-box solutions.
In Summary, MemSQL and Microsoft SQL Server differ in their database architecture, scalability, real-time analytics support, data processing speed, and high availability features.
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.
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.
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,
- 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 MemSQL
- Distributed9
- Realtime5
- Columnstore4
- Sql4
- Concurrent4
- JSON4
- Ultra fast3
- Scalable3
- Unlimited Storage Database2
- Pipeline2
- Mixed workload2
- Availability Group2
Pros of Microsoft SQL Server
- Reliable and easy to use139
- High performance101
- Great with .net95
- Works well with .net65
- Easy to maintain56
- Azure support21
- Always on17
- Full Index Support17
- Enterprise manager is fantastic10
- In-Memory OLTP Engine9
- Easy to setup and configure2
- Security is forefront2
- Great documentation1
- Faster Than Oracle1
- Columnstore indexes1
- Decent management tools1
- Docker Delivery1
- Max numar of connection is 140001
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Cons of MemSQL
Cons of Microsoft SQL Server
- Expensive Licensing4
- Microsoft2
- Data pages is only 8k1
- Allwayon can loose data in asycronious mode1
- Replication can loose the data1
- The maximum number of connections is only 14000 connect1