Rupert  Beatty

Rupert Beatty

1665745697

Realm is A Mobile Database: A Replacement for Core Data & SQLite

Realm

Realm is a mobile database that runs directly inside phones, tablets or wearables. This repository holds the source code for the iOS, macOS, tvOS & watchOS versions of Realm Swift & Realm Objective-C.

Why Use Realm

  • Intuitive to Developers: Realm’s object-oriented data model is simple to learn, doesn’t need an ORM, and lets you write less code.
  • Built for Mobile: Realm is fully-featured, lightweight, and efficiently uses memory, disk space, and battery life.
  • Designed for Offline Use: Realm’s local database persists data on-disk, so apps work as well offline as they do online.
  • Device Sync: Makes it simple to keep data in sync across users, devices, and your backend in real-time. Get started for free with a template application that includes a cloud backend and Sync.

Object-Oriented: Streamline Your Code

Realm was built for mobile developers, with simplicity in mind. The idiomatic, object-oriented data model can save you thousands of lines of code.

// Define your models like regular Swift classes
class Dog: Object {
    @Persisted var name: String
    @Persisted var age: Int
}
class Person: Object {
    @Persisted(primaryKey: true) var _id: String
    @Persisted var name: String
    @Persisted var age: Int
    // Create relationships by pointing an Object field to another Class
    @Persisted var dogs: List<Dog>
}
// Use them like regular Swift objects
let dog = Dog()
dog.name = "Rex"
dog.age = 1
print("name of dog: \(dog.name)")

// Get the default Realm
let realm = try! Realm()
// Persist your data easily with a write transaction 
try! realm.write {
    realm.add(dog)
}

Live Objects: Build Reactive Apps

Realm’s live objects mean data updated anywhere is automatically updated everywhere.

// Open the default realm.
let realm = try! Realm()

var token: NotificationToken?

let dog = Dog()
dog.name = "Max"

// Create a dog in the realm.
try! realm.write {
    realm.add(dog)
}

//  Set up the listener & observe object notifications.
token = dog.observe { change in
    switch change {
    case .change(let properties):
        for property in properties {
            print("Property '\(property.name)' changed to '\(property.newValue!)'");
        }
    case .error(let error):
        print("An error occurred: (error)")
    case .deleted:
        print("The object was deleted.")
    }
}

// Update the dog's name to see the effect.
try! realm.write {
    dog.name = "Wolfie"
}

SwiftUI

Realm integrates directly with SwiftUI, updating your views so you don't have to.

struct ContactsView: View {
    @ObservedResults(Person.self) var persons
    
    var body: some View {
        List {
            ForEach(persons) { person in
                Text(person.name)
            }
            .onMove(perform: $persons.move)
            .onDelete(perform: $persons.remove)
        }.navigationBarItems(trailing:
            Button("Add") {
                $persons.append(Person())
            }
        )
    }
}

Fully Encrypted

Data can be encrypted in-flight and at-rest, keeping even the most sensitive data secure.

// Generate a random encryption key
var key = Data(count: 64)
_ = key.withUnsafeMutableBytes { bytes in
    SecRandomCopyBytes(kSecRandomDefault, 64, bytes)
}

// Add the encryption key to the config and open the realm
let config = Realm.Configuration(encryptionKey: key)
let realm = try Realm(configuration: config)

// Use the Realm as normal
let dogs = realm.objects(Dog.self).filter("name contains 'Fido'")

Getting Started

We support installing Realm via Swift Package Manager, CocoaPods, Carthage, or by importing a dynamic XCFramework.

For more information, see the detailed instructions in our docs.

Interested in getting started for free with a template application that includes a cloud backend and Sync? Create a MongoDB Atlas Account.

Documentation

The documentation can be found at docs.mongodb.com/realm/sdk/ios/.
The API reference is located at docs.mongodb.com/realm-sdks/swift/latest/

Getting Help

  • Need help with your code?: Look for previous questions with therealm tag on Stack Overflow or ask a new question. For general discussion that might be considered too broad for Stack Overflow, use the Community Forum.
  • Have a bug to report? Open a GitHub issue. If possible, include the version of Realm, a full log, the Realm file, and a project that shows the issue.
  • Have a feature request? Open a GitHub issue. Tell us what the feature should do and why you want the feature.

Building Realm

In case you don't want to use the precompiled version, you can build Realm yourself from source.

Prerequisites:

  • Building Realm requires Xcode 11.x or newer.
  • Building Realm documentation requires jazzy

Once you have all the necessary prerequisites, building Realm.framework just takes a single command: sh build.sh build. You'll need an internet connection the first time you build Realm to download the core binary.

Run sh build.sh help to see all the actions you can perform (build ios/osx, generate docs, test, etc.).

Contributing

See CONTRIBUTING.md for more details!

Code of Conduct

This project adheres to the MongoDB Code of Conduct. By participating, you are expected to uphold this code. Please report unacceptable behavior to community-conduct@mongodb.com.

Feedback

If you use Realm and are happy with it, please consider sending out a tweet mentioning @realm to share your thoughts!

And if you don't like it, please let us know what you would like improved, so we can fix it!

Download Details:

Author: Realm
Source Code: https://github.com/realm/realm-swift 
License: Apache-2.0 license

#swift #ios #sync #mobile #database 

What is GEEK

Buddha Community

Realm is A Mobile Database: A Replacement for Core Data & SQLite
 iOS App Dev

iOS App Dev

1625133780

SingleStore: The One Stop Shop For Everything Data

  • SingleStore works toward helping businesses embrace digital innovation by operationalising “all data through one platform for all the moments that matter”

The pandemic has brought a period of transformation across businesses globally, pushing data and analytics to the forefront of decision making. Starting from enabling advanced data-driven operations to creating intelligent workflows, enterprise leaders have been looking to transform every part of their organisation.

SingleStore is one of the leading companies in the world, offering a unified database to facilitate fast analytics for organisations looking to embrace diverse data and accelerate their innovations. It provides an SQL platform to help companies aggregate, manage, and use the vast trove of data distributed across silos in multiple clouds and on-premise environments.

**Your expertise needed! **Fill up our quick Survey

#featured #data analytics #data warehouse augmentation #database #database management #fast analytics #memsql #modern database #modernising data platforms #one stop shop for data #singlestore #singlestore data analytics #singlestore database #singlestore one stop shop for data #singlestore unified database #sql #sql database

 iOS App Dev

iOS App Dev

1620466520

Your Data Architecture: Simple Best Practices for Your Data Strategy

If you accumulate data on which you base your decision-making as an organization, you should probably think about your data architecture and possible best practices.

If you accumulate data on which you base your decision-making as an organization, you most probably need to think about your data architecture and consider possible best practices. Gaining a competitive edge, remaining customer-centric to the greatest extent possible, and streamlining processes to get on-the-button outcomes can all be traced back to an organization’s capacity to build a future-ready data architecture.

In what follows, we offer a short overview of the overarching capabilities of data architecture. These include user-centricity, elasticity, robustness, and the capacity to ensure the seamless flow of data at all times. Added to these are automation enablement, plus security and data governance considerations. These points from our checklist for what we perceive to be an anticipatory analytics ecosystem.

#big data #data science #big data analytics #data analysis #data architecture #data transformation #data platform #data strategy #cloud data platform #data acquisition

Einar  Hintz

Einar Hintz

1602560783

jQuery Ajax CRUD in ASP.NET Core MVC with Modal Popup

In this article, we’ll discuss how to use jQuery Ajax for ASP.NET Core MVC CRUD Operations using Bootstrap Modal. With jQuery Ajax, we can make HTTP request to controller action methods without reloading the entire page, like a single page application.

To demonstrate CRUD operations – insert, update, delete and retrieve, the project will be dealing with details of a normal bank transaction. GitHub repository for this demo project : https://bit.ly/33KTJAu.

Sub-topics discussed :

  • Form design for insert and update operation.
  • Display forms in modal popup dialog.
  • Form post using jQuery Ajax.
  • Implement MVC CRUD operations with jQuery Ajax.
  • Loading spinner in .NET Core MVC.
  • Prevent direct access to MVC action method.

Create ASP.NET Core MVC Project

In Visual Studio 2019, Go to File > New > Project (Ctrl + Shift + N).

From new project window, Select Asp.Net Core Web Application_._

Image showing how to create ASP.NET Core Web API project in Visual Studio.

Once you provide the project name and location. Select Web Application(Model-View-Controller) and uncheck HTTPS Configuration. Above steps will create a brand new ASP.NET Core MVC project.

Showing project template selection for .NET Core MVC.

Setup a Database

Let’s create a database for this application using Entity Framework Core. For that we’ve to install corresponding NuGet Packages. Right click on project from solution explorer, select Manage NuGet Packages_,_ From browse tab, install following 3 packages.

Showing list of NuGet Packages for Entity Framework Core

Now let’s define DB model class file – /Models/TransactionModel.cs.

public class TransactionModel
{
    [Key]
    public int TransactionId { get; set; }

    [Column(TypeName ="nvarchar(12)")]
    [DisplayName("Account Number")]
    [Required(ErrorMessage ="This Field is required.")]
    [MaxLength(12,ErrorMessage ="Maximum 12 characters only")]
    public string AccountNumber { get; set; }

    [Column(TypeName ="nvarchar(100)")]
    [DisplayName("Beneficiary Name")]
    [Required(ErrorMessage = "This Field is required.")]
    public string BeneficiaryName { get; set; }

    [Column(TypeName ="nvarchar(100)")]
    [DisplayName("Bank Name")]
    [Required(ErrorMessage = "This Field is required.")]
    public string BankName { get; set; }

    [Column(TypeName ="nvarchar(11)")]
    [DisplayName("SWIFT Code")]
    [Required(ErrorMessage = "This Field is required.")]
    [MaxLength(11)]
    public string SWIFTCode { get; set; }

    [DisplayName("Amount")]
    [Required(ErrorMessage = "This Field is required.")]
    public int Amount { get; set; }

    [DisplayFormat(DataFormatString = "{0:MM/dd/yyyy}")]
    public DateTime Date { get; set; }
}

C#Copy

Here we’ve defined model properties for the transaction with proper validation. Now let’s define  DbContextclass for EF Core.

#asp.net core article #asp.net core #add loading spinner in asp.net core #asp.net core crud without reloading #asp.net core jquery ajax form #asp.net core modal dialog #asp.net core mvc crud using jquery ajax #asp.net core mvc with jquery and ajax #asp.net core popup window #bootstrap modal popup in asp.net core mvc. bootstrap modal popup in asp.net core #delete and viewall in asp.net core #jquery ajax - insert #jquery ajax form post #modal popup dialog in asp.net core #no direct access action method #update #validation in modal popup

Database Vs Data Warehouse Vs Data Lake: A Simple Explanation

Databases store data in a structured form. The structure makes it possible to find and edit data. With their structured structure, databases are used for data management, data storage, data evaluation, and targeted processing of data.
In this sense, data is all information that is to be saved and later reused in various contexts. These can be date and time values, texts, addresses, numbers, but also pictures. The data should be able to be evaluated and processed later.

The amount of data the database could store is limited, so enterprise companies tend to use data warehouses, which are versions for huge streams of data.

#data-warehouse #data-lake #cloud-data-warehouse #what-is-aws-data-lake #data-science #data-analytics #database #big-data #web-monetization

Gerhard  Brink

Gerhard Brink

1620629020

Getting Started With Data Lakes

Frameworks for Efficient Enterprise Analytics

The opportunities big data offers also come with very real challenges that many organizations are facing today. Often, it’s finding the most cost-effective, scalable way to store and process boundless volumes of data in multiple formats that come from a growing number of sources. Then organizations need the analytical capabilities and flexibility to turn this data into insights that can meet their specific business objectives.

This Refcard dives into how a data lake helps tackle these challenges at both ends — from its enhanced architecture that’s designed for efficient data ingestion, storage, and management to its advanced analytics functionality and performance flexibility. You’ll also explore key benefits and common use cases.

Introduction

As technology continues to evolve with new data sources, such as IoT sensors and social media churning out large volumes of data, there has never been a better time to discuss the possibilities and challenges of managing such data for varying analytical insights. In this Refcard, we dig deep into how data lakes solve the problem of storing and processing enormous amounts of data. While doing so, we also explore the benefits of data lakes, their use cases, and how they differ from data warehouses (DWHs).


This is a preview of the Getting Started With Data Lakes Refcard. To read the entire Refcard, please download the PDF from the link above.

#big data #data analytics #data analysis #business analytics #data warehouse #data storage #data lake #data lake architecture #data lake governance #data lake management