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Aisalkyn Aidarova
Aisalkyn Aidarova

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COUCHBASE

#distributedsystems #database #sql #performance

1. What Is Couchbase?

Couchbase is a NoSQL document database.

✔ Stores data as JSON

No tables, no rows.
Everything is a JSON document.

✔ Extremely fast (in-memory + disk)

Couchbase keeps hot data in memory → super fast reads/writes.

✔ High availability & auto-sharding

Clusters, nodes, buckets, replication — built-in.

✔ Has a SQL-like query language

Called N1QL (read: "nickel").
This lets you query JSON documents using something similar to SQL.

2. When Do Companies Use Couchbase?

Companies use Couchbase when they need:

✔ Real-time analytics

Live dashboards, leaderboards, metrics.

✔ Caching + Database in one system

No need for Redis + MongoDB separately.

✔ High-speed user/session data

Mobile apps, gaming, IoT, fraud detection systems.

✔ Distributed databases

Across data centers or cloud clusters.

3. Couchbase Architecture (Simple)

🔹 Cluster → a group of nodes

🔹 Node → one machine (EC2, VM, container)

🔹 Bucket → a database inside the cluster

🔹 Document → JSON record

🔹 Index → makes search faster

🔹 Services inside Couchbase:

  • Data Service
  • Query Service (for N1QL)
  • Index Service
  • Search Service
  • Analytics Service

You can enable/disable them per node.

4. Why DevOps Engineers Work With Couchbase

As a DevOps engineer, you will:

✔ Deploy Couchbase clusters

Docker, Kubernetes, EC2, or on-prem.

✔ Configure buckets, users, roles

For developers & analytics teams.

✔ Monitor latency, rebalance, replication

Because Couchbase is distributed.

✔ Set up backup/restore processes

Very important in production.

✔ Integrate with apps

Python, Java, NodeJS, Kafka.

5. Couchbase in Your Kafka Real-Time Project

Your architecture:

Order Producer → Kafka → Consumers → Analytics Service → Couchbase
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Why Couchbase here?

1️⃣ Kafka gives real-time events
2️⃣ Analytics-service calculates metrics
3️⃣ Couchbase stores FINAL metrics
4️⃣ UI shows them instantly

Couchbase is used as a Real-Time Analytics Store.

6. Installing Couchbase (Docker Version)

docker-compose snippet: 

couchbase:
  image: couchbase:community
  container_name: couchbase
  ports:
    - "8091-8096:8091-8096"
    - "11210:11210"
  environment:
    - COUCHBASE_ADMINISTRATOR_USERNAME=Administrator
    - COUCHBASE_ADMINISTRATOR_PASSWORD=password
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After running:

docker compose up -d
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Open browser:

http://localhost:8091
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7. Setup Couchbase Cluster (UI)

Step 1 — "Setup New Cluster"

Enter any name and password.

Step 2 — Configure services

Check:

  • Data
  • Query
  • Index

Step 3 — Memory settings

Leave defaults for local development.

Step 4 — Create bucket

Examples:

Bucket Name:

order_analytics
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RAM: 256MB (enough for dev)

Click Create Bucket.

DONE.
Cluster + bucket ready.

8. What Is a Bucket?

A bucket = database inside Couchbase.

Types:

  • Couchbase Bucket (default)
  • Ephemeral Bucket (memory only)
  • Memcached Bucket (cache only)

For analytics → use Couchbase bucket.

9. Insert Documents Into Couchbase (UI)

Go to:

Buckets → order_analytics → Documents → Add Document
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Example:

{
  "total_orders": 120,
  "total_revenue": 15000,
  "top_country": "USA"
}
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This is how your analytics-service will store results.

10. Querying Couchbase (N1QL)

Example 1: Select all documents 

SELECT * FROM order_analytics;
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Example 2: Find specific fields 

SELECT total_orders, total_revenue
FROM order_analytics;
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Example 3: Filter by key 

SELECT *
FROM order_analytics
WHERE meta().id = "global_analytics";
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11. How Python Writes to Couchbase (Your Analytics Service)

Example Python code:

from couchbase.cluster import Cluster, ClusterOptions
from couchbase.auth import PasswordAuthenticator
from couchbase.collection import DeltaValue

cluster = Cluster("couchbase://couchbase", 
    ClusterOptions(PasswordAuthenticator("Administrator", "password")))

bucket = cluster.bucket("order_analytics")
collection = bucket.default_collection()

analytics_data = {
    "total_orders": 300,
    "total_revenue": 55000,
    "fraud_count": 12
}

collection.upsert("global_metrics", analytics_data)
print("Updated Couchbase analytics!")
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You will include this inside your analytics-service consumer.

12. How Couchbase Works with Kafka

You push messages to Kafka.
You consume messages → calculate metrics.
You store metrics in Couchbase.

This gives:

  • Kafdrop → raw events
  • Couchbase → clean, summarized analytics

Use this in UI dashboards.

13. Monitoring Couchbase

Important metrics:

  • Ops per second
  • Disk queue
  • Resident ratio
  • Index fragmentation
  • Replication status
  • Node health

Tools:

  • Prometheus + Couchbase Exporter
  • Grafana dashboards
  • Couchbase UI (built-in)

14. Backup & Restore

Backup: 

cbbackup http://localhost:8091 /backup/dir \
  -u Administrator -p password
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Restore: 

cbrestore /backup/dir http://localhost:8091 \
  -u Administrator -p password
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15. Couchbase vs Other Databases

Feature Couchbase MongoDB Redis
JSON DB ✔ ✔ ✖
In-memory speed ✔ 50% ✔
SQL-like queries ✔ N1QL ❌ ❌
Perfect for real-time analytics ✔ ⚠️ slow ✔ (but no persistence)
Distributed clusters ✔ ✔ ⚠️ limited

Couchbase = Best of MongoDB + Redis combined.

16. Real World Use Cases

E-commerce

Live inventory, carts, personalization.

Banking/Fraud

Real-time anomaly detection.

Mobile Apps

User profiles, sessions.

Gaming

Scores, leaderboards, live match data.

IoT

Stream processing + real-time dashboards.

*17. Summary *

  • Couchbase is a NoSQL JSON database
  • It is extremely fast and distributed
  • It supports SQL-like queries with N1QL
  • It works perfectly with Kafka real-time pipelines
  • It is great for analytics dashboards
  • Simple to install and explore using the UI
  • Perfect demonstration for beginners

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