MongoDB,Redis,InfluxDB - Master the 3 TOP 1 Ranked Databases

Learn the basics of MongoDB as a document store and server, including community edition, enterprise, and Atlas free tier, with practical notes on JSON documents and collections.

Get a helicopter view of MongoDB’s architecture and key features. Learn from collections, documents, fields, and CRUD to advanced querying, aggregation, gridfs, time series, geospatial, and change streams.

Discover why MongoDB offers a schemaless json data model with json data format, Atlas Search, aggregation pipeline, GridFS, time series and geospatial data, and change streams for real-time updates.

Learn to connect MongoDB Atlas with MongoDB Compass, set up a free Google Cloud cluster, create a user, configure IP access, and work with a demo db and sample data.

Pull the official MongoDB image with Docker Desktop, run the container on port 27017, connect with mongo, create a demo db, insert vehicle data, and verify with show dbs.

Discover MongoDB Compass, a Java-based GUI and CLI, to connect to a server, browse databases and collections, and perform insert, edit, and delete in JSON, list, and tabular views.

Connect to MongoDB Atlas from MongoDB Compass to set up a free cloud cluster. Create a demo db and server metrics collection, add documents, and explore sample weather data.

Connect Studio 3T and MongoDB Compass to MongoDB Atlas via the connection URL, test and save the connection, then view databases and Airbnb collections in json and table formats.

master the visual query builder in studio3t to create a three-stage query with filter, projection, and sort; view results in table or json, and generate mongo shell or c# code.

Explore how to run sql in mongodb with Studio 3D, view sql queries and query code, and generate Python and JavaScript code to reproduce results with sorting and conditions.

Explore how to work with arrays in MongoDB using essential operators. Learn size, push, pull, pop, each, in, not in, and add to set via element match with practical demos.

GridFS, MongoDB's solution for storing large binary content beyond 16 MB, using a bucket with files and chunks collections and a 255 KB default chunk size.

Master the MongoDB lookup operator to perform left outer joins between collections, map local to foreign fields, and produce output arrays, with examples and advanced let-and-pipeline workflows.

Connect Python with MongoDB using PyMongo and Atlas, then find, insert many, update one or many, delete many, sort, limit, and list databases and collections.

Learn to use Node.js with MongoDB by installing the MongoDB driver, connecting to Atlas, and performing insert, find, update, and delete operations on databases and collections.

Explore mongodb full text search, including creating a text index and using $text and $search operators. Understand stemming, stop words, phrase search, case sensitivity, and ranking scores that rank results.

Explore MongoDB change streams, near real-time notifications that act like triggers. Watch inserts, updates, deletes on replica sets or sharded clusters with resume tokens, filters, and observer integrations.

Explore MongoDB views, including dynamic standard views and materialized views stored on disk, their use in reporting and data sharing, and how to create and query them with aggregation pipelines.

Create on demand materialized views in MongoDB by using match and merge stages to store results in a dedicated collection, with indexing for fast queries.

Demonstrate MongoDB geospatial queries with GeoJSON points and the near operator in a ride-hailing scenario. Explore 2D sphere indexes, geo within, geo intersects, and center sphere radius conversions.

Redis shines as an in-memory NoSQL key-value data store with microsecond reads and millisecond writes, enabling persistence, multi-model capabilities, and wide AWS popularity for caching and real-time analytics.

Learn the five essentials of Redis: key-value storage, data types and commands, editions (open source, enterprise, cloud), GUI/CLI tools like Redis Insight, and modules such as Redis Search and JSON.

Master Redis key management with commands like keys, set, get, del, and copy. Explore key naming conventions using object type:ID, data types, key space, and expiry features.

Master Redis by exploring its rich data types—strings, lists, sets, sorted sets, hashes, hyperloglog, streams, geospatial data, and bitmaps—as the core for caching, sessions, and analytics in real world apps.

Master the set data type, which disallows duplicates and is unordered, and learn key commands (add, members, card, union, inter, diff, scan) and use cases for counting unique items.

Explore the sorted set data type, its unique members with scores, and how scores drive ordering, ranking, and use cases like leaderboards and IoT metrics, with z commands for manipulation.

Explore the bitmap data type in Redis, learning how bitmaps store 0/1 values, use memory-efficient bitwise operations, and master key commands like set bit, get bit, bit count, and bitop.

Hyperloglog data type estimates the number of unique values in large data sets without storing the values, using about 12 KB of memory and an error rate under 1%.

Explore how Redis streams provide an inbuilt, append-only event log for near real-time streaming, with unique IDs and consumer groups, contrasting with pub-sub and batch processing.

Master Redis basics: persistence with AOF and snapshots, core data types, and modules like Redis Json, Redis Search, and time series.

Explore Redis pub/sub fundamentals, including publish and subscribe, pattern subscriptions, and the fire-and-forget delivery with no data storage and no guaranteed deliveries, ideal for real-time, low-latency messaging.

Explore Redis persistence options for in-memory data: RDB snapshots, AOF, hybrid AOF with RDB, or no persistence, and compare durability and data-loss implications.

Master Redis transactions as atomic, isolated command blocks using multi and exec, with watch for aborting on key changes and discard to abort, and reduce round trips via pipelining.

Master the Redis search module to perform full-text search on hashes and Redis JSON, with real-time indexing, autocomplete, and features like sorting, fuzzy search, and paging.

Discover the Redis json module, a binary json store in Redis stack with dynamic schema and jsonpath support, and learn use cases like mobile app backends, analytics, and IoT data.

Explore the Redis graph module to model data as graphs with nodes, relationships, and properties, using Cypher-style queries to create, query, and delete graphs, and compare Neo4j's approach.

Learn how Redis gears embeds functions in Python, Java, and JavaScript for in-server data processing with no extra layer. Explore IoT use cases, data cleansing, language detection, and write-behind architectures.

Explore how Redis can act as a configuration database, a pub-sub system, and a primary database alongside MongoDB and other NoSQL solutions, with Redis modules and Memorydb for Redis.

Explore what a time series database is, its importance, data structure, use cases, and how it differs from traditional RDBMS, with examples from InfluxDB and TimescaleDB.

Discover the five basics of InfluxDB: line protocol, buckets, the 2.0 interface, the Data Explorer, and Flux script. Use tasks, alerts, and API to manage time-series data.

Explore InfluxDB 2.0 components, including the time series database engine, buckets, and a feature-rich user interface with load data, data explorer, dashboards, and alerts.

Explore InfluxDB 3.0's 180-degree revamp with the Ten-x engine, Parquet storage, and Arrow processing. Learn native SQL via Arrow Flight SQL and Influx SQL for faster queries and unlimited cardinality.

Explore InfluxDB 3.0 core components and architecture, including Apache Parquet as a columnar, SQL-compatible storage format, and the Apache Arrow framework for efficient data interchange.

Explore InfluxDB 2.0 and 3.0, and why learning both matters, comparing TSM versus SQL, cloud serverless versus OS editions, within the arrow ecosystem powered by Apache Parquet.

Learn to query InfluxDB 3.0 cloud serverless with SQL, load line protocol data, and perform selects, aggregations, and casting using the data explorer and SQL sync.

Learn InfluxDB 2.0 basics: buckets with retention, api tokens, and flux; understand measurements, line protocol, tags, fields, and timestamps, and how indexing, series, and data types govern updates.

Explore InfluxDB's time series features - high write speed, fast aggregations, and data summarization before eviction - and use buckets, flux, and the telegraf-prometheus-grafana stack for monitoring.

Explore InfluxDB 2.0 notebooks to analyze data with queries, create alerts and tasks, and build multi-panel visualizations that can be exported as PNG or PDF.

InfluxDB offers threshold and dead man alerts with a four-step process (query, configure the check, set a notification endpoint such as Slack, and define rules) using schedule every and offset.

Master InfluxDB 2.0 tasks with flux scripts, detailing options, data sources, processing, and destinations. Explore three examples: copy between buckets, add a calculated column, and post results to http endpoint.