10 NoSQL Stores with JSON in 10 Days (MongoDB, CouchDB, etc)

Explore JSON basics, including objects and arrays, and map them to Python dictionaries and lists while surveying NoSQL document models and the top ten document stores.

master json objects and arrays as the core of hierarchical data in nosql stores, using curly braces and square brackets, with nested objects and arrays.

Explore how to work with JSON in Python by loading data into dictionaries and lists, accessing values by key, and printing pretty-printed outputs in VS Code and Jupyter notebooks.

Explore how JSON serves as a hierarchical data format, compare it with XML and YAML, and review NDJSON, GeoJSON, binary JSON, and JSON with comments.

Explore NoSQL document stores and JSON documents, compare BSON and JSON storage, and understand queries with JavaScript in NoSQL contexts for web applications.

Examine NoSQL document stores and JSON storage through the Db-engines ranking, noting MongoDB as the leading option alongside DynamoDB, Redis JSON, MySQL document store, and Azure Cosmos DB for NoSQL.

Examine notable omissions when surveying NoSQL document stores for JSON storage, distinguishing true document stores from multi-model and relational options highlighted in the course.

Explore MongoDB, a leading no-sql document store, by creating a free Atlas cluster, filtering JSON data, using Compass and VS Code with MongoDB extension, querying via PyMongo and aggregation pipelines.

Learn about MongoDB as the leading JSON document store, its editions (community, enterprise, Atlas cloud), and core features like BSON, JavaScript queries, sharding, replication, and Atlas SQL.

Discover how to create and access a free MongoDB Atlas cluster, configure an organization and project, set username, password, and IP address access, and explore starter dashboards with sample data.

Filter JSON data from the web UI using JavaScript-based queries, applying equality, range, and logical operators, plus projections, sort, and handling optional attributes.

Install the compass desktop app to explore, modify, and visualize MongoDB data locally, connect via native drivers, and practice using the mongo shell and aggregation pipeline.

Explore using MongoDB for vscode to perform CRUD operations on JSON data, including insert, find, update, delete, and aggregation, with a playground and examples in JavaScript.

Learn to build aggregation pipelines in PyMongo using match, project, sort, and limit. Explore applying pipelines to sample movie data, and compare Python dictionaries with dot notation for access.

Explore MongoDB tools and features across shells, GUIs, and drivers. Review Atlas components, from search and charts to triggers and streams, plus JSON documents in collections.

Explore MongoDB certifications, including associate developer, data modeler, atlas administrator, and database administrator, with $150 exam attempts, student and educator benefits, and study resources.

Explore Amazon DocumentDB and its MongoDB compatibility as a hosted cloud service, learn to create a DocumentDB cluster, and review pricing, security, and architecture considerations.

Explore Amazon DocumentDB with MongoDB compatibility as a cloud hosted NoSQL document store on AWS, compare standard and IO optimized pricing, and note the 30-day free trial and cluster pricing.

Connect with AWS CloudShell to access a MongoDB cluster, create collections, insert and query documents, update records, and drop collections using MongoDB shell commands.

Configure Amazon DocumentDB TLS settings by creating custom parameter groups, applying them to clusters, and managing certificate download for secure or non-secure connections in a VPC environment.

Connect to a document database from a Python notebook using PyMongo and a connection string. Create and query a sample database and collection, using environment credentials and closing the client.

Explore the features and architecture of Amazon DocumentDB, a fully managed NoSQL JSON document service with MongoDB compatibility, offering elastic clusters, a primary instance, read-only replicas, and endpoints.

Discover how AWS certifications are organized from foundation to specialty, with exams, vouchers, renewals, and DocumentDB's role in NoSQL data-focused questions.

Explore Azure Cosmos DB for NoSQL and MongoDB APIs, set up a free tier, install a VS Code extension, and query JSON data with SQL-like queries using the Azure SDK.

Explore Azure Cosmos DB APIs for NoSQL, including document stores with JSON documents and MongoDB, Cassandra, and Gremlin models, using native SQL syntax and the .NET SDK.

Set up an Azure Cosmos DB free tier account by choosing the NoSQL API, creating a resource group, and configuring provisioning and throughput.

Install the Azure Databases extension for Visual Studio Code to browse and query Azure databases (MongoDB, Cosmos DB) with the databases explorer, including JSON documents.

Run sql queries from the VSCode extension to interrogate NoSQL json data in Cosmos DB, using the query editor to view results in table, json, or tree formats.

Deploy a Python application with the Azure SDK for Python to interact with Azure Cosmos DB NoSQL, using quickstart, Codespaces, and data explorer workflows.

Navigate Azure certifications and manage your credentials in the Microsoft Learn portal, covering exam paths, renewals, and free online quizzes for roles like solutions architect and data scientist.

Explore Couchbase as a document store and use SQL++ to query dynamic JSON data; practice with notebooks and VS Code, covering create, update, delete, aggregate queries, and nesting concepts.

Couchbase is a multi-model NoSQL document store using JSON with key-value and transactional and analytics workloads, available on-premises and as cloud Capella with SQL++ queries.

Set up a free Couchbase Capella trial to create an operational cluster, bucket, scope, and collection, connect with VS Code, and run JSON document queries using SQL++.

Query dynamic json data using the Couchbase SQL engine in VSCode, exploring objects and arrays, aliasing, on-the-fly data, and array operations like sort, reverse, and length.

Explore scope samples and practical SQL++ for JSON documents in Couchbase, including inserting into collections, returning inserted content, updating documents with dot notation, and using sequences, unnest, and metadata queries.

Explore advanced aggregate sql++ queries in Couchbase, grouping by person name, using unnest, array_agg, and window functions like lag and lead on dynamic data.

Explore sql++ features for querying and manipulating json documents with an sql extension, including json functions, nested arrays, joins, and indexing for transactional operations.

Explore Couchbase certifications, including associate and professional tracks, exam formats and pricing. Learn how the certification path has evolved to non-proctored online quizzes since 2023.

Introduce Apache CouchDB as a free open source nosql document store, expose its http json api, and demo docker setup with foxtone ui and python access.

Explore Apache CouchDB, a free, open source document store for JSON data with offline-first synchronization and master replication, ideal for mobile apps and offline operation.

Learn to start the Fauxton web UI for CouchDB using Docker Desktop, mapping port 5984, and using a preconfigured Bitnami image for local testing on Windows, macOS, or Linux.

Run mango queries from Fauxton, create a test database and documents, index the year field, execute refined queries, view the query plan, and consider partitioning and replication for performance.

Learn to run the CouchDB HTTP JSON API from curl, issuing GET, PUT, POST, and DELETE requests with local authentication to manage databases and JSON documents.

Learn to access CouchDB from Python with a minimal Jupyter notebook, install the CouchDB library, create a client, a database, and documents, then delete them.

Explore couchdb features such as mapreduce views, server-side javascript, json-based queries, and a unique http json api. Use multi-master replication, offline/mobile sync, mvcc versioning, and eventual consistency for distributed deployments.

Introduce MySQL document store as a NoSQL option within a relational database, storing and querying JSON with extensions. Install the X plugin and access JSON via the X Dev API.

Discover how MySQL combines relational tables with a native JSON document store, enabling NoSQL collections alongside SQL. Use the X protocol and MySQL shell to CRUD JSON collections.

Install the MySQL community edition for a document store, and optionally MariaDB; configure distinct ports, use MySQL Workbench and MySQL Shell, then install the mysql-x-connector-python package.

Use the MySQL shell to access the JSON document store via the X protocol, create a store database, and define a books collection for JSON data.

Explore using the MySQL X DevAPI with Python to store and query JSON collections, via a Jupyter notebook and environment variables for credentials.

Examine the system architecture of a MySQL document store, an extension of relational SQL with JSON collections stored as NoSQL data, accessible via the X protocol and MySQL Shell.

Explore Google Cloud Firestore as a NoSQL document store alongside Firebase real-time database and datastore, and learn native mode, legacy datastore mode, and the query builder.

Discover Google Cloud Firestore, an auto scaling JSON document database for mobile and web apps. Explore collections, documents, subcollections, real time updates, offline persistence, and its pricing model.

Learn to create and populate a Firestore datastore mode database within a Google Cloud project, including adding book entities, indexing fields, and exploring native mode options.

Learn gql basics for querying json in nosql stores, including sort by title and filter by isbn or category. Understand limits, indexing, and the restrictions on aggregate queries and joins.

switch to native mode to create and manage a database with collections. explore billing implications, regional settings, test rules, and Firestore studio's query builder and documents.

Authenticate with Google Cloud, install the Firestore Python client, and connect to a Firestore database to create and query books in Python.

Master Firestore Studio's query builder by applying where filters and order by, and learn about index creation as you navigate nested collections and subcollections.

Explore Google Cloud certifications across foundational, associate, and professional levels, including cloud engineer and cloud architect paths, with insights on Firestore, data certifications, and renewal considerations.

Explore RethinkDB to understand its event-driven data synchronization and push updates for mobile document stores. Query JSON data from JavaScript and Python while examining features and architecture.

Explore Rethinkdb, a free open source JSON document store that streams real-time changes via push-based, event-driven updates, with fluent table queries and multi-language drivers.

Install and explore rethinkdb locally in a docker container using the official docker hub image, then browse the admin console and data explorer to prepare databases, tables, and json data.

Demonstrates querying and mutating JSON data in a NoSQL store using JavaScript in a data explorer, including creating stores and tables, inserting, updating, filtering, grouping, and deleting records.

Learn how to query json data from python using rethinkdb in a Jupyter notebook inside VSCode, set up a virtual env, install drivers, and perform lazy operations with json results.