Chapter 51: AWS Additional Database Services

AWS Additional Database Services

First — very important clarification so we don’t waste time:

There is no official AWS service or category literally named “Additional Database Services”.

When people (especially on YouTube, Reddit India, LinkedIn groups, Telugu tech channels, or in college WhatsApp groups) search or ask for “AWS Additional Database Services”, they almost always mean one of these three things:

1. All the database services beyond RDS (the “additional” ones people discover after learning RDS)
2. The specialized / non-relational / purpose-built databases that are not RDS (the “extra” family members)
3. A misunderstanding/misremembering of the full AWS Database Portfolio (RDS + Aurora + DynamoDB + DocumentDB + Neptune + Timestream + Keyspaces + Redshift + ElastiCache + MemoryDB + QLDB + etc.)

So today we’re going to do the complete, honest, practical overview of the full AWS Database family — with special focus on the “additional” ones that come after people learn RDS.

We’ll walk through it like a real classroom session — analogies from daily Hyderabad life, real startup/fintech/edtech examples from Telangana/India in 2026, when teams actually choose each one, rough pricing in ap-south-2, and the decision tree most Indian developers use.

1. The Full AWS Database Family – 2026 Overview (The Ones That Matter)

Here is the realistic list of databases that 95%+ of Hyderabad companies actually use or evaluate:

2. Quick Decision Tree – Which AWS Database Should You Pick? (2026 Hyderabad Reality)

Ask these questions in order — this is the exact path most Indian teams follow:

1. Do you need relational tables + SQL joins + full ACID transactions?
   • Yes → go to RDS or Aurora
   • No → continue
2. Do you need massive scale + single-digit millisecond latency + automatic scaling?
   • Yes → DynamoDB (most popular NoSQL choice in India 2026)
   • No → continue
3. Do you need super-fast caching / session store / pub-sub?
   • Yes → ElastiCache (Redis) or MemoryDB (if you need strong durability)
   • No → continue
4. Do you need analytics / reporting / large GROUP BY / aggregations on big data?
   • Yes → Redshift Serverless or Athena (serverless on S3)
   • No → continue
5. Do you have existing MongoDB / Cassandra / graph code you want to lift-and-shift?
   • MongoDB → DocumentDB
   • Cassandra → Keyspaces
   • Graph → Neptune
6. Do you have time-series data (metrics, IoT, logs over time)?
   • Yes → Timestream
7. Do you need immutable, cryptographically verifiable ledger (financial audit trail)?
   • Yes → QLDB

3. Real Hyderabad Example – Typical Multi-Database Stack (2026)

Your startup “TeluguBites” — restaurant discovery + food ordering app:

Total database/storage bill (moderate–high traffic): ~₹25,000–70,000/month → Very reasonable for a scaling app serving thousands of daily orders

4. Quick Hands-On – Create Your First DynamoDB & Aurora Table

DynamoDB (NoSQL)

1. DynamoDB console → Create table
2. Table name: “HyderabadUsers”
3. Partition key: userId (String)
4. Create → add item: userId = “rahul123”, name = “Rahul from Gachibowli”, city = “Hyderabad”

Aurora PostgreSQL (Relational)

1. RDS console → Create database → Aurora → PostgreSQL → Serverless v2
2. Min capacity 0.5 ACU → max 8 ACU
3. Create → wait 5–10 min → get endpoint
4. Connect with DBeaver → run:
   SQL

   PHP

   0 1 2 3 4 5 6 7 8 9 10 11 12

   CREATE TABLE orders (     order_id SERIAL PRIMARY KEY,     user_id VARCHAR(50),     amount DECIMAL(10,2),     city VARCHAR(50),     order_date TIMESTAMP DEFAULT CURRENT_TIMESTAMP );

Summary Table – AWS Databases Quick Decision Guide (2026 – India Focus)

Teacher’s final note (2026 Hyderabad reality):

Most growing startups in Hyderabad do NOT choose one database — they use 2–4 in the same application.

Typical healthy 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)
• ElastiCache Redis → caching & real-time pub/sub
• Redshift Serverless → business intelligence & reporting once you have enough data

Once you stop trying to force every problem into one engine, your architecture becomes faster, cheaper, more scalable, and much easier to hire developers for.

Got it? This is the “which AWS database should I actually use?” master 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 full cost comparison for 1 million daily active users?

Tell me — next whiteboard ready! 🚀🗄️