Microsoft SQL Server vs Presto

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Microsoft SQL Server

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Presto

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Microsoft SQL Server vs Presto: What are the differences?

Developers describe Microsoft SQL Server as "A relational database management system developed by Microsoft". Microsoft® SQL Server is a database management and analysis system for e-commerce, line-of-business, and data warehousing solutions. On the other hand, Presto is detailed as "Distributed SQL Query Engine for Big Data". Presto is an open source distributed SQL query engine for running interactive analytic queries against data sources of all sizes ranging from gigabytes to petabytes.

Microsoft SQL Server can be classified as a tool in the "Databases" category, while Presto is grouped under "Big Data Tools".

"Reliable and easy to use" is the primary reason why developers consider Microsoft SQL Server over the competitors, whereas "Works directly on files in s3 (no ETL)" was stated as the key factor in picking Presto.

Presto is an open source tool with 9.22K GitHub stars and 3.12K GitHub forks. Here's a link to Presto's open source repository on GitHub.

Microsoft, Intuit, and Stack Exchange are some of the popular companies that use Microsoft SQL Server, whereas Presto is used by Airbnb, Facebook, and Netflix. Microsoft SQL Server has a broader approval, being mentioned in 470 company stacks & 425 developers stacks; compared to Presto, which is listed in 19 company stacks and 11 developer stacks.

Advice on Microsoft SQL Server and Presto

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
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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Christopher Wray
Web Developer at Soltech LLC · | 3 upvotes · 187.4K views

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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Julien DeFrance
Principal Software Engineer at Tophatter · | 3 upvotes · 187.1K views
Recommends
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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Recommends
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 · 187.1K views
Recommends
PostgreSQLPostgreSQL

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

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Decisions about Microsoft SQL Server and Presto
Ashish Singh
Tech Lead, Big Data Platform at Pinterest · | 37 upvotes · 1.1M views

To provide employees with the critical need of interactive querying, we’ve worked with Presto, an open-source distributed SQL query engine, over the years. Operating Presto at Pinterest’s scale has involved resolving quite a few challenges like, supporting deeply nested and huge thrift schemas, slow/ bad worker detection and remediation, auto-scaling cluster, graceful cluster shutdown and impersonation support for ldap authenticator.

Our infrastructure is built on top of Amazon EC2 and we leverage Amazon S3 for storing our data. This separates compute and storage layers, and allows multiple compute clusters to share the S3 data.

We have hundreds of petabytes of data and tens of thousands of Apache Hive tables. Our Presto clusters are comprised of a fleet of 450 r4.8xl EC2 instances. Presto clusters together have over 100 TBs of memory and 14K vcpu cores. Within Pinterest, we have close to more than 1,000 monthly active users (out of total 1,600+ Pinterest employees) using Presto, who run about 400K queries on these clusters per month.

Each query submitted to Presto cluster is logged to a Kafka topic via Singer. Singer is a logging agent built at Pinterest and we talked about it in a previous post. Each query is logged when it is submitted and when it finishes. When a Presto cluster crashes, we will have query submitted events without corresponding query finished events. These events enable us to capture the effect of cluster crashes over time.

Each Presto cluster at Pinterest has workers on a mix of dedicated AWS EC2 instances and Kubernetes pods. Kubernetes platform provides us with the capability to add and remove workers from a Presto cluster very quickly. The best-case latency on bringing up a new worker on Kubernetes is less than a minute. However, when the Kubernetes cluster itself is out of resources and needs to scale up, it can take up to ten minutes. Some other advantages of deploying on Kubernetes platform is that our Presto deployment becomes agnostic of cloud vendor, instance types, OS, etc.

#BigData #AWS #DataScience #DataEngineering

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Karthik Raveendran
CPO at Attinad Software · | 3 upvotes · 156.2K views

The platform deals with time series data from sensors aggregated against things( event data that originates at periodic intervals). We use Cassandra as our distributed database to store time series data. Aggregated data insights from Cassandra is delivered as web API for consumption from other applications. Presto as a distributed sql querying engine, can provide a faster execution time provided the queries are tuned for proper distribution across the cluster. Another objective that we had was to combine Cassandra table data with other business data from RDBMS or other big data systems where presto through its connector architecture would have opened up a whole lot of options for us.

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Pros of Microsoft SQL Server
Pros of Presto
  • 139
    Reliable and easy to use
  • 102
    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
    Security is forefront
  • 1
    Columnstore indexes
  • 1
    Great documentation
  • 1
    Faster Than Oracle
  • 1
    Decent management tools
  • 1
    Easy to setup and configure
  • 1
    Docker Delivery
  • 18
    Works directly on files in s3 (no ETL)
  • 13
    Open-source
  • 12
    Join multiple databases
  • 10
    Scalable
  • 7
    Gets ready in minutes
  • 6
    MPP

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Cons of Microsoft SQL Server
Cons of Presto
  • 4
    Expensive Licensing
  • 2
    Microsoft
    Be the first to leave a con

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    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.

    What is Presto?

    Distributed SQL Query Engine for Big Data

    Need advice about which tool to choose?Ask the StackShare community!

    What companies use Microsoft SQL Server?
    What companies use Presto?
    See which teams inside your own company are using Microsoft SQL Server or Presto.
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    What tools integrate with Microsoft SQL Server?
    What tools integrate with Presto?

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    What are some alternatives to Microsoft SQL Server and Presto?
    Oracle
    Oracle Database is an RDBMS. An RDBMS that implements object-oriented features such as user-defined types, inheritance, and polymorphism is called an object-relational database management system (ORDBMS). Oracle Database has extended the relational model to an object-relational model, making it possible to store complex business models in a relational database.
    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.
    Apache Aurora
    Apache Aurora is a service scheduler that runs on top of Mesos, enabling you to run long-running services that take advantage of Mesos' scalability, fault-tolerance, and resource isolation.
    Microsoft Access
    It is an easy-to-use tool for creating business applications, from templates or from scratch. With its rich and intuitive design tools, it can help you create appealing and highly functional applications in a minimal amount of time.
    MariaDB
    Started by core members of the original MySQL team, MariaDB actively works with outside developers to deliver the most featureful, stable, and sanely licensed open SQL server in the industry. MariaDB is designed as a drop-in replacement of MySQL(R) with more features, new storage engines, fewer bugs, and better performance.
    See all alternatives