Overview

Microsoft SQL Server

Stacks21.3K

Followers15.5K

Votes540

EdgeDB

Stacks17

Followers52

Votes0

EdgeDB vs Microsoft SQL Server: What are the differences?

Introduction

When comparing EdgeDB and Microsoft SQL Server, there are key differences that users should be aware of. Below are the specific distinctions between these two database management systems.

Data Modeling Approach: EdgeDB uses a declarative data modeling approach that allows users to define complex data structures with constraints and relationships directly, making it more intuitive and easier to work with. On the other hand, Microsoft SQL Server uses a more traditional relational database model that may require more effort to set up and manage relationships between tables.
Query Language: EdgeDB introduces its own query language called EdgeQL, which is tailored specifically for working with complex data models and allows for deeply nested queries and relationships. In contrast, Microsoft SQL Server uses Transact-SQL (T-SQL), a powerful query language with a wide range of features but may be less intuitive for handling complex data models.
Schema Evolution: EdgeDB supports automatic schema migrations and versioning, offering more flexibility for evolving data structures without breaking existing applications. In comparison, Microsoft SQL Server may require manual intervention when making schema changes, which can be cumbersome and time-consuming.
Performance Optimization: EdgeDB comes with built-in optimization mechanisms that automatically tune queries and optimize data retrieval, leading to better overall performance. Meanwhile, Microsoft SQL Server also provides optimization tools, but they may require more manual tweaking and monitoring to achieve similar levels of performance.
Containerization Support: EdgeDB is designed with containerization in mind and offers seamless integration with container orchestration tools like Kubernetes, facilitating easy deployment and management in containerized environments. Microsoft SQL Server also supports containerization, but some limitations may exist in terms of scaling and resource management within containers.
Platform Compatibility: EdgeDB is compatible with Linux, macOS, and Windows operating systems, offering flexibility in terms of platform support. While Microsoft SQL Server runs on Windows natively, it also provides versions for Linux and Docker containers, expanding its platform compatibility but may require additional configuration and setup.

In Summary, EdgeDB and Microsoft SQL Server differ in their data modeling approach, query language, schema evolution, performance optimization, containerization support, and platform compatibility.

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Advice on Microsoft SQL Server, EdgeDB

Erin

IT Specialist

Mar 10, 2020

Needs adviceon

Microsoft SQL Server

MySQL

PostgreSQL

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}|tool:1025| or @{PostgreSQL}|tool:1028| on a @{Linux}|tool:10483| 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.

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Detailed Comparison

Microsoft SQL Server	EdgeDB
Microsoft® SQL Server is a database management and analysis system for e-commerce, line-of-business, and data warehousing solutions.	An object-relational database that stores and describes the data as strongly typed objects and relationships between them.
-	Strict, strongly typed schema; Powerful and clean query language; Ability to easily work with complex hierarchical data; Built-in support for schema migrations
Statistics
Stacks 21.3K	Stacks 17
Followers 15.5K	Followers 52
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
Integrations
No integrations available	GraphQL Python

What are some alternatives to Microsoft SQL Server, EdgeDB?

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

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.

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

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 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

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 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

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 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.