Intro to NoSQL Databases

Introduction to NoSQL Databases

• NoSQL is a database management system designed for large volumes of unstructured and semi-structured data.
• Flexible data models are utilized, adapting to changes and scaling horizontally for growing data amounts.
• Evolved to mean "not only SQL", encompassing various database architectures and data models.
• Applications with high data volumes needing real-time processing commonly employ NoSQL databases.
• Applications include social media analytics, e-commerce, gaming, content management, and customer relationship management.
• Applications not requiring high data consistency and transactional guarantees as regular relational databases may find NoSQL unsuitable.

Key Features of NoSQL

• NoSQL databases do not have a fixed schema and can accommodate changing data structures with no need for migrations or schema alterations
• Horizontal scalability scales out by adding more nodes to a database cluster, making them well-suited for handling large amounts of data and high levels of traffic.

Data Models

• Document-based data model stores data as semi-structured documents (JSON or BSON).
• Key-value data model stores data as a collection of key-value pairs.
• Column-based data model organizes data into columns instead of rows.
• Graph data model stores data as nodes and edges, designed for complex relationships.

NoSQL Database Types

• Document databases store semi-structured documents (JSON or XML), queried using document-oriented languages.
• Examples include MongoDB, CouchDB, and Cloudant.
• Key-value stores optimize for simple, fast read/write operations, storing data as key-value pairs.
• Examples include Memcached, Redis, and Coherence.
• Column-family stores store data as column families, optimized for quick querying of large datasets.
• Examples include HBase, BigTable, and Accumulo.
• Graph databases, such as Amazon Neptune and Neo4j, use nodes and edges to store data and are ideal for complex relationships.

Introduction to MongoDB

• MongoDB is an open-source document database excelling in performance, availability, and automatic scaling.
• A NoSQL database with a document-oriented data model.
• Stores data in flexible, JSON-like documents, enabling dynamic schemas and scalability, unlike traditional relational databases.
• Suited for applications with evolving schemas and large amounts of unstructured/semi-structured data, providing high performance and horizontal scalability.
• MongoDB database environments include MongoDB Atlas, MongoDB Enterprise, and MongoDB Community.
• MongoDB Atlas: a fully managed cloud service.
• MongoDB Enterprise: a subscription-based, self-managed version.
• MongoDB Community: a source-available, free-to-use, and self-managed version.

MongoDB Features and Advantages

• Employs a document-oriented data model, using BSON documents for flexible data storage (Binary JSON).
• Schema-less approach allows developers to work with developing data structures, accommodating changes without a predefined schema.
• Designed for high performance, enabling fast read and write operations, with indexing and query optimization features.
• Scales horizontally by sharding data across servers, handling increased data loads seamlessly.
• Supports indexing techniques to enhance query performance.
• Features an aggregation framework for complex data transformations and analysis within the database.
• Enables pipeline-style aggregations for tasks such as filtering and grouping directly within the database.
• Built-in replication features ensure high availability.
• Maintaining multiple data copies across replica sets allows operations to continue during server failures.
• Includes Geospatial indexing, ideal for location-based applications.
• Uses GridFS, for storing and retrieving large files like images, videos, and audio.
• Active community provides tools, drivers, and extensions for development.

MongoDB Installation

• MongoDB is a cross-platform NoSQL database with operating system compatibility.
• Meets system requirements: Windows, Linux, macOS; 64-bit processor architecture; sufficient RAM; planned disk space; supported file system; robust network connectivity.
• Instructions for downloading the MongoDB Installer:
• Visit the official MongoDB website to access the download page.
• Select the appropriate operating system version.
• Choose the Community edition and click the download button.
• Follow the prompts to save the installer file to your local machine.

Installing MongoDB on Windows, Linux, and macOS:

• For Windows: Determine the MongoDB build needed from three options, accounting for Windows versions
• The .msi installer handles all software dependencies and seamlessly upgrades older versions. Run the downloaded installer, accepting the license agreement, and choose the "Complete" setup.
• For Linux: Extract the downloaded archive (.tgz file), move files, and create a symbolic link to the 'bin' directory for easy access.
• For macOS: Install using Homebrew with the command 'brew tap mongodb/brew && brew install mongodb/brew/mongodb-community`or download the .tgz file and use similar steps as Linux.

Configuration Options During Installation:

• Basic Configuration involves choosing the installation directory.
• Network Configuration involves specifying the port and network binding options.
• The default port number for MongoDB is 27017.
• Data and Log Paths involve setting the data directory for MongoDB's database storage.

Verifying the Installation:

• Open a command prompt or terminal window.
• Run the MongoDB shell with the mongod command.
• Verify the MongoDB server version and connection.

Starting and Stopping the MongoDB Server:

• On Windows, Manage the service using net start MongoDB and net stop MongoDB.
• On Linux and macOS, start MongoDB with mongod or sudo service mongod startand stop with mongod --shutdown or sudo service mongod stop.

Checking Server Status and Logs:

• Use commands to check server status and view logs:
• mongod --version: Displays MongoDB version.
• mongod --fork --logpath /var/log/mongodb/mongod.log': Starts MongoDB as a background process with logging.
• `mongo admin --eval "db.runCommand({whatsmyuri: 1})"': Checks the status and connection URI.
• Installation, configuration, and verification allow working with MongoDB databases.

Connecting to MongoDB:

• Connection string is a URI-like string defining the connection to a MongoDB instance.
• It includes the host, port, authentication details, and other parameters, formatted as mongodb://username:password@host:port/database. Connecting via MongoDB Shell:
• Open a terminal or command prompt.
• Run the mongo command and connect to MongoDB using the connection string.

Overview of MongoDB Compass:

• MongoDB Compass is a GUI tool for MongoDB.
• Main Features: Visual data, index management, query optimization, real-time stats, schema analysis, and query performance profiling.

MongoDB: Basic CRUD Operations

• CRUD operations define conventions for users to view, search, and modify database components.
• MongoDB documents can be modified by connecting to a server, querying documents, adjusting properties, and updating the database conforming to HTTP action verbs
• CRUD operations are data-oriented and standardized according to HTTP action verbs.
• CRUD stands for Create, Read, Update, and Delete.

CRUD Types

• The Create operation inserts new documents into MongoDB databases.
• The Read operation queries a document in the database.
• The Update operation modifies existing documents in the database.
• The Delete operation removes documents from the database.
• MongoDB uses commands createCollection, insertOne, insertMany.

Document database

• A record is a document of field and value pairs similar to JSON objects.
• Field values may include other documents, arrays, and arrays of documents.
• A document can follow this syntax: db.collection_name.insertOne ({key1: value1, key2: value2, ... })

To Add Documents to Collection

• Use the 'insertOne' or 'insertMany` method.
• insertMany Syntax : db.collection_name.insertMany ([ { key1: value1, key2: value2, ... }, { key1: value1, key2: value2, ... }, ... ])
• Read operations retrieve a collection's documents using the syntax: db.collection_name.find({"fieldname":"value"}).
• You can specify query filters or return criteria.

CQL - collection modifier

• collection modifier
• query criteria
• projection

db.users.find(
{age: { $gt: 18}}, //collection
{ name: 1, address: 1 }  //query criteria
).limit(5)   //projection

Update Operations

• Update operations modify existing values in a collection, offering methods like updateOne, updateMany, and replaceOne.
• To update a filer: Users must identify the documents to update.
• The example filters the table: db.users.updateMany (collection, update filter, update action)