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  1. Stackups
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  5. Mentat vs Microsoft SQL Server

Mentat vs Microsoft SQL Server

OverviewDecisionsComparisonAlternatives

Overview

Microsoft SQL Server
Microsoft SQL Server
Stacks21.3K
Followers15.5K
Votes540
Mentat
Mentat
Stacks199
Followers12
Votes0
GitHub Stars1.7K
Forks115

Mentat vs Microsoft SQL Server: What are the differences?

## Introduction

Key differences between Mentat and Microsoft SQL Server are outlined below:

1. **Database structure**: Mentat uses a hierarchical database structure, primarily based on nodes and connections, while Microsoft SQL Server follows a relational database model with tables and rows. This fundamental difference affects how data is stored, queried, and managed in each system.
  
2. **Query language**: Mentat uses MQL (Mentat Query Language) as its query language, specifically designed to navigate through the hierarchical database structure, while Microsoft SQL Server employs T-SQL (Transact-SQL) for interacting with its relational database. The syntax and capabilities of these query languages differ significantly.
  
3. **Scalability**: Mentat is designed for small to medium-scale applications with a focus on flexibility and ease of use, whereas Microsoft SQL Server is known for its scalability and performance in handling large enterprise-level datasets. The choice between the two systems often depends on the size and growth potential of the organization.
  
4. **Support for transaction management**: Microsoft SQL Server has robust support for transaction management, ensuring ACID (Atomicity, Consistency, Isolation, Durability) properties, while Mentat provides more lightweight transaction capabilities suitable for simpler applications. This can impact the reliability and integrity of data operations in each system.
  
5. **Vendor and licensing**: Mentat is an open-source project, offering its database system freely without licensing fees, whereas Microsoft SQL Server is a commercial product that requires licensing for enterprise usage. The decision on which system to adopt can hinge on budget considerations and the level of support required.
  
6. **Ecosystem and integration**: Microsoft SQL Server has a well-established ecosystem with numerous tools, libraries, and third-party integrations available, making it easier to work with in a diverse technology landscape. In contrast, Mentat may have limitations in terms of ecosystem support and compatibility with other systems, impacting the overall development environment.

## Summary

In summary, the key differences between Mentat and Microsoft SQL Server lie in their database structure, query language, scalability, transaction management, vendor and licensing models, as well as ecosystem and integration capabilities.

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Advice on Microsoft SQL Server, Mentat

Erin
Erin

IT Specialist

Mar 10, 2020

Needs adviceonMicrosoft SQL ServerMicrosoft SQL ServerMySQLMySQLPostgreSQLPostgreSQL

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}|tool:1025| or @{PostgreSQL}|tool:1028| on a @{Linux}|tool:10483| 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.
668k views668k
Comments

Detailed Comparison

Microsoft SQL Server
Microsoft SQL Server
Mentat
Mentat

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

Project Mentat is a persistent, embedded knowledge base. It draws heavily on DataScript and Datomic. Mentat is implemented in Rust.

-
Flexible rotational store; Makes it easy to describe, grow, and reuse your domain schema
Statistics
GitHub Stars
-
GitHub Stars
1.7K
GitHub Forks
-
GitHub Forks
115
Stacks
21.3K
Stacks
199
Followers
15.5K
Followers
12
Votes
540
Votes
0
Pros & Cons
Pros
  • 139
    Reliable and easy to use
  • 101
    High performance
  • 95
    Great with .net
  • 65
    Works well with .net
  • 56
    Easy to maintain
Cons
  • 4
    Expensive Licensing
  • 2
    Microsoft
  • 1
    Replication can loose the data
  • 1
    Allwayon can loose data in asycronious mode
  • 1
    The maximum number of connections is only 14000 connect
No community feedback yet

What are some alternatives to Microsoft SQL Server, Mentat?

MongoDB

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.

MySQL

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

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.

SQLite

SQLite

SQLite is an embedded SQL database engine. Unlike most other SQL databases, SQLite does not have a separate server process. SQLite reads and writes directly to ordinary disk files. A complete SQL database with multiple tables, indices, triggers, and views, is contained in a single disk file.

Cassandra

Cassandra

Partitioning means that Cassandra can distribute your data across multiple machines in an application-transparent matter. Cassandra will automatically repartition as machines are added and removed from the cluster. Row store means that like relational databases, Cassandra organizes data by rows and columns. The Cassandra Query Language (CQL) is a close relative of SQL.

Memcached

Memcached

Memcached is an in-memory key-value store for small chunks of arbitrary data (strings, objects) from results of database calls, API calls, or page rendering.

MariaDB

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.

RethinkDB

RethinkDB

RethinkDB is built to store JSON documents, and scale to multiple machines with very little effort. It has a pleasant query language that supports really useful queries like table joins and group by, and is easy to setup and learn.

ArangoDB

ArangoDB

A distributed free and open-source database with a flexible data model for documents, graphs, and key-values. Build high performance applications using a convenient SQL-like query language or JavaScript extensions.

InfluxDB

InfluxDB

InfluxDB is a scalable datastore for metrics, events, and real-time analytics. It has a built-in HTTP API so you don't have to write any server side code to get up and running. InfluxDB is designed to be scalable, simple to install and manage, and fast to get data in and out.

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