Chapter 48: AWS DynamoDB vs BDS

AWS DynamoDB vs BDS.

First — very important clarification:

There is no service called “BDS” in AWS.

“BDS” is not an official AWS database, storage, or compute service in 2026 (nor was it ever). It is most likely one of these common confusions/mistypes/mishearings that happen very often in India (especially in Telugu/English mixed tech discussions, YouTube comments, WhatsApp groups):

1. RDS (Amazon Relational Database Service) ← by far the most common mix-up People say/write “BDS” when they mean “RDS” (R and B are next to each other on keyboard, or pronunciation slip)
2. DocumentDB (MongoDB-compatible) ← sometimes misheard/mistyped as “BDS”
3. Bedrock (AWS generative AI service) ← very rare, but some people say “BDS” when trying to say “Bedrock”
4. Big Data Service (old informal name for EMR / Glue / Athena ecosystem) ← almost never used now

In 95%+ of real questions I see from Indian learners (Naukri, LinkedIn, GeeksforGeeks comments, Telugu tech channels), when someone writes “DynamoDB vs BDS”, they actually mean

DynamoDB vs RDS

So today we will do a proper, detailed, honest, 2026-up-to-date comparison between:

Amazon DynamoDB (NoSQL, key-value + document, serverless) vs Amazon RDS (managed relational SQL databases — MySQL, PostgreSQL, MariaDB, Oracle, SQL Server)

… and I’ll also very briefly touch Aurora (RDS’s faster cousin) and DocumentDB (MongoDB-like) so you see the full landscape.

Let’s go step-by-step like a real classroom whiteboard session — analogies, Hyderabad startup examples, decision table, pricing reality, and when Indian teams actually choose one over the other.

1. Quick One-Line Summary (Memorize This)

2. Head-to-Head Comparison – DynamoDB vs RDS (2026 Reality)

3. Real Hyderabad Startup Example – Hybrid DynamoDB + RDS/Aurora

Your “TeluguBites” food discovery & ordering app (very typical 2026 stack in Hyderabad):

RDS / Aurora PostgreSQL (relational – core transactional data)

• Tables: Users, Restaurants, Orders, OrderItems, Payments, Addresses
• Why RDS/Aurora?
  • Strong ACID needed (order total must match payment exactly)
  • Complex queries needed (show user’s past orders with restaurant names, ratings, join multiple tables)
  • Foreign keys & referential integrity important
• Multi-AZ deployment → automatic failover
• Read replicas for reporting dashboard

DynamoDB (NoSQL – high-scale, low-latency parts)

• Tables:
  • Sessions (sessionId → user preferences, current cart items)
  • TrendingRestaurants (restaurantId → viewCount, lastUpdated)
  • UserActivityFeed (userId + timestamp → recent searches/views)
  • Cart (userId → current cart items – flexible schema)
• Why DynamoDB?
  • Millions of reads/writes during lunch & dinner rush
  • Single-digit ms latency critical (real-time “trending now” section)
  • Schema changes frequent (add new user preference fields)
  • Global Tables if expanding to Dubai/Singapore users
  • DAX cluster for sub-ms caching of hot restaurants

Monthly cost rough estimate (moderate–high traffic):

• Aurora PostgreSQL db.t4g.large Multi-AZ → ~₹10,000–18,000
• DynamoDB on-demand (~5–20 million reads/writes) → ~₹3,000–12,000
• DAX (optional cache) → ~₹3,000–8,000
• Total database bill: ₹16,000–40,000 (very reasonable for scaling app)

4. Quick Hands-On – Create a DynamoDB Table vs RDS Table

DynamoDB (NoSQL)

1. DynamoDB console → Create table
2. Table name: “TeluguUsers”
3. Partition key: userId (String)
4. Create → add item
   • userId: “rahul123”
   • name: “Rahul from Gachibowli”
   • city: “Hyderabad”
   • preferences: [“biryani”, “irani chai”, “mirchi bajji”] (list – flexible!)
5. Query → GetItem → <10 ms response

RDS PostgreSQL (Relational)

1. RDS console → Create PostgreSQL → db.t4g.micro (free tier)
2. Wait 5–10 min → get endpoint
3. Connect with DBeaver/pgAdmin → run SQL:
   SQL

   PHP

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   CREATE TABLE users (     id SERIAL PRIMARY KEY,     name VARCHAR(100) NOT NULL,     city VARCHAR(50),     created_at TIMESTAMP DEFAULT CURRENT_TIMESTAMP ); INSERT INTO users (name, city) VALUES ('Rahul', 'Hyderabad'); SELECT * FROM users WHERE name = 'Rahul';

Summary Table – DynamoDB vs RDS/Aurora (Quick Decision 2026)

Teacher’s final note (2026 Hyderabad reality):

Most growing startups in Hyderabad use both — not one or the other.

Typical pattern:

• Aurora PostgreSQL / RDS → core money-related data (orders, payments, users with relations)
• DynamoDB → everything that needs massive scale & low predictable latency (carts, sessions, activity feeds, preferences, metadata, counters)

Once you stop trying to force DynamoDB to do relational work (or RDS to handle 10 million writes/sec), your architecture becomes faster, cheaper, more scalable, and much easier to hire developers for.

Got it? This is the “when should I actually pick DynamoDB instead of RDS?” lesson.

Next?

• Deep dive: DynamoDB single-table design (how to model orders + users + restaurants in one table)
• Step-by-step: Build real-time “trending restaurants” with DynamoDB Streams + Lambda?
• Or cost comparison calculator for 1 million daily active users?

Tell me — next whiteboard ready! 🚀🗄️