Intel M1 chip vs Apple M1 silicon chip

The Intel M1 vs Apple M1 Silicon debate has garnered significant attention in the tech world. Both processors have their unique strengths and have been designed to optimize performance in different ways.

Intel’s M1 chip, part of their 11th generation lineup, brings several improvements over its predecessors. It offers increased power efficiency, faster processing speeds, and improved graphics performance. The M1 chip also integrates advanced artificial intelligence capabilities, allowing for enhanced machine learning processes and improved overall system responsiveness.

On the other hand, Apple’s M1 Silicon chip has caused quite a stir with its impressive performance and power efficiency. Built specifically for Apple’s Mac devices, the M1 Silicon chip delivers lightning-fast speeds and efficient power consumption, resulting in longer battery life. Additionally, the M1 chip boasts an 8-core GPU, enabling exceptional graphics performance for tasks such as video editing and gaming.

Understanding the differences between these two processors is crucial for consumers making purchasing decisions. Both Intel and Apple have their own dedicated user bases, each with varying needs and preferences. Some users might prioritize compatibility with a wide range of software and peripherals, favoring the Intel M1 chip. Others might value the seamless integration between hardware and software offered by Apple’s M1 Silicon chip, especially for Mac-exclusive applications.

Ultimately, the choice between Intel’s M1 and Apple’s M1 Silicon depends on individual requirements and personal preferences. It’s essential to consider factors such as system compatibility, performance benchmarks, and the specific tasks you wish to accomplish on your device. By carefully evaluating these aspects, you can make an informed decision that best suits your needs.

• Intel M1 chip vs Apple M1 silicon chip
• How to use MSSQL Server on ARM based Mac.
• Create Docker Container for MSSQL on Mac
• Access Docker MSSQL Container from Parallel (Mac Mini M2)
• How to quickly open code editor from console on Windows / Linux and Mac

What are the steps to use Swift Core Data ?

Here are some steps to effectively use Swift Core Data:

1. Import the Core Data framework: Start by importing the necessary Core Data framework into your Swift project. This can be done by adding the following line at the beginning of your code:

import CoreData

2. Create a Core Data Model: Define your Core Data model by designing the entities and their attributes. This can be done visually using the Core Data Model Editor in Xcode. Make sure to specify the relationships and properties that your entities will have.
3. Generate Managed Object Subclasses: In order to interact with the data in your Core Data model, you need to generate managed object subclasses. Xcode provides a convenient way to generate these subclasses for your entities. To do this, select your .xcdatamodeld file, navigate to “Editor” in the Xcode menu, and choose “Create NSManagedObject Subclass”. This will generate Swift classes that represent your entities.
4. Set Up the Core Data Stack: Initialize the Core Data stack in your application delegate. This involves creating a persistent container, configuring the managed object context, and linking them together. The persistent container is responsible for managing the Core Data model, while the managed object context is responsible for interacting with the data.
5. Perform Fetch Requests: Use fetch requests to retrieve data from your Core Data model. You can define various predicates and sort descriptors to filter and order the results as needed. Fetch requests are executed on the managed object context and return a collection of managed objects that match the specified criteria.
6. Create, Update, and Delete Data: Use the managed object context to create, update, and delete data in your Core Data model. You can create new managed objects, modify their attributes, establish relationships between entities, and delete existing objects. Changes made on the managed object context are only saved to the persistent store when explicitly called.
7. Save Changes: Remember to save any changes made to the managed object context to persist them in the persistent store. This is done by calling the save() method on the managed object context. It’s important to handle any potential errors that may occur during the save operation.
8. Handle Concurrency: When working with Core Data, it’s important to consider concurrency when performing operations on the managed object context. You can use parent-child contexts or perform operations on background threads to improve performance and avoid blocking the main thread.

By following these steps, you will be able to effectively utilize Swift Core Data in your projects. It provides a powerful means of managing and persisting data, allowing you to create robust and scalable applications.

What is swift data ?

Swiftdata is a powerful data processing software designed to streamline and optimize your data management needs. With its innovative features and user-friendly interface, Swiftdata empowers businesses to efficiently gather, organize, analyze, and utilize data in the most effective way possible.

Featuring cutting-edge technology, Swiftdata allows you to seamlessly integrate data from various sources, whether it’s transactional databases, spreadsheets, or even IoT devices. Its robust data integration capabilities enable you to consolidate and harmonize disparate data sets, ensuring accuracy and consistency across your organization.

Thanks to Swiftdata’s advanced data processing capabilities, you can effortlessly perform complex data transformations, calculations, and aggregations. Whether you need to generate insightful reports, create predictive models, or extract meaningful patterns from your data, Swiftdata has got you covered.

Moreover, Swiftdata offers a highly scalable and parallelized computing framework, allowing you to handle massive volumes of data without compromising performance. Its distributed architecture ensures fast processing speed and optimal resource utilization, enabling you to tackle big data challenges with ease.

With Swiftdata, data governance and security are at the forefront. You have full control over access rights, data privacy, and compliance, ensuring that sensitive information is protected and only accessible to authorized personnel.

In conclusion, Swiftdata is an all-in-one solution for data management, processing, and analysis. It empowers businesses of all sizes to unlock the true potential of their data, make data-driven decisions, and stay ahead in today’s competitive landscape. Explore the possibilities with Swiftdata and witness the transformation of your data into actionable insights.

• Intel M1 chip vs Apple M1 silicon chip
• How to use MSSQL Server on ARM based Mac.
• Create Docker Container for MSSQL on Mac
• Access Docker MSSQL Container from Parallel (Mac Mini M2)
• How to quickly open code editor from console on Windows / Linux and Mac

How to use MSSQL Server on ARM based Mac.

Microsoft SQL Server can be run on Linux, Windows but they may not work with Apple Mac/Mac mini. We can’t change a just DBMS for new OS, different platform .

The fact that Mac/Mac mini with M2 chip is ideal for Multi platform development. It is better alternative for Windows Machine, since you are looking for a desktop.

We have two options to consider for getting things work, a Virtual machine dedicated to MSSQL or just containerise the SQL server which is a better choice.

VM don’t like Mac, I tried Virtual Box and Parallel. VB didn’t start up correctly. In case Parallel it didn’t get installed.

So we move to the Docker option. Most of the docker images (ARM based MSSQL) designed for Intel Mac ? For Mac with M1 and M2 (Apple Silicon).

Wee needs to user Rosetta for the transition from Intel to New M1/M2. It work behind the seen.

For complete Guide on Containerising MSSQL Server visit this Post.

Create Docker Container for MSSQL on Mac

As the first step we need to install Docker Mac and make sure you have Rosetta get installed, in case of using Mac with M1 or M2. These Models come with Apple Silicon. Some of the older apps come with Intel chip support, Rosetta will help you the migrate to Apple Silicon.

Docker Compose

Using the Docker-Compose we can containerise MSSQL. Here is the working Docker-Compose file.

Create a Folder called MSSQL and add Docker-Compose.yml file with following contents

version: '3.9'

services:
  mssql-azur-edge:
    image: mcr.microsoft.com/azure-sql-edge 
    platform: linux/arm64
    ports:
      - 1433:1433
    volumes:
      - ~/apps/mssql/data:/var/lib/mssqlql/data
    environment:
      - ACCEPT_EULA=Y
      - SA_PASSWORD=mssql1Ipw

Since I’am using the Mac Min M2, which is an arm device, should specify in the platform key. Port key expose the internal port to external. Volume indicate the storage location which is optional.

In the environment key we can pass the Password for SQL Server etc.

Now . Run the Docker-compose up -d. for running the Container. If there is any problem , run this command for the log docker-compose logs

You are ready to use the sever. You can also use the Mac IP and exposed port in SQL Management studio or in a connection string as (source)

 Mac IP, 1433

Access Docker MSSQL Container from Parallel (Mac Mini M2)

Docker not working with Windows 11 in Parallels. Is there any way to use MSSQL with Parallel ? Yes.

Using the Mac Network IP and container exposed port number, we can access the server (Docker) within MSQL Management Studio or in a connection strings, separated by a single comma

Where Did I get the IP ?

In System Settings – Network- Find the IP.

connectionString="Data Source=192.168.20.100,1433;Password=mssql1Ipw;User Id=sa;Initial Catalog=dolphinedb;Integrated Security=False" />

The above code is sample sql connection string. Thanks for Docker.

Mac Mini M2 for Windows Developers

I got Mac Mini M2 last Saturday, wow. I love the Machine it saved my Desk. It is the base Model , with 8GB ,250 GB SSD.

I would like to share some of my experiences With M2. It is incredibly fast.

Running Windows 11 with Parallel VM

I’am using Parallels 8.0.1 , successfully configured windows 11 and installed Microsoft Visual Studio and it work without any trouble. Parallels allow me switch between Windows Apps and Mac Apps with ease and peace.

I did find some kinda of hanging and black out while the Mac went to sleep and wake from sleep.

Following Not working for me – Parallels

MSSQL Server

Docker

Above mentioned Apps can’t run on VM. So I decided to run it from Docker container which is on the Mac.

Apple Silicon and Docker

Some of the Docker Images not working with M2, it could be designed for Intel chip. So we need Rosetta for using such Docker images.

Installing Rosetta

Rosetta is referred as translater for Intel Mac Apps. You need not worry about any thing at all. Just install and move on.

 softwareupdate --install-rosetta

For more guides on Rosetta please visit MacHow

If you are a developer looking for Work Station with Multiple Display capabilities. Don’t wait to grab the deal today.

Install apps in openSUSE Linux with zypper

openSUSE is one of the customizable and developer friendly Linux distribution. You can install SUSE along with Windows or can be install using VirtualBox, which is the easiest way of trying this Linux on Windows/Mac.

Zypper

zypper is a command line utility like apt, which fetch application from SUSE’s repository.

Search for an app

You can search for an app/package in the repository using zypper option

sudo zypper search sublim

In this case I search for sublimText package.

Install the app

You can install the app using the package name as

sudo zypper install sublimText