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Spring Boot with Amazon OpenSearch

Learn how to integrate Spring Boot with Amazon OpenSearch step by step. This guide covers OpenSearch architecture, indexing, searching, full-text search, REST APIs, Spring Boot integration, AWS SDK, monitoring, and production best practices.

Introduction

Modern applications need more than simple database queries.

Users expect features like:

  • Instant product search
  • Full-text document search
  • Auto-complete
  • Fuzzy search
  • Log analytics
  • Monitoring dashboards
  • Real-time search

Traditional relational databases are not optimized for complex search operations.

Amazon OpenSearch Service provides a fully managed search and analytics engine built on the OpenSearch project.

In this article, we will integrate Spring Boot with Amazon OpenSearch and implement enterprise search functionality.

Learning Objectives

After completing this article, you will understand:

  • What is OpenSearch?
  • Why use a search engine?
  • OpenSearch Architecture
  • Documents
  • Indexes
  • Shards
  • Replicas
  • Full-Text Search
  • REST APIs
  • Spring Boot Integration
  • Search Queries
  • Production Best Practices

What is Amazon OpenSearch?

Amazon OpenSearch Service is a managed search and analytics service.

It allows applications to:

  • Store searchable documents
  • Perform full-text search
  • Filter results
  • Aggregate data
  • Analyze logs
  • Build dashboards

OpenSearch is commonly used alongside relational databases rather than replacing them.

Why OpenSearch?

Suppose an e-commerce application stores one million products.

Searching by SQL:

SELECT *
FROM products
WHERE name LIKE '%laptop%'

Problems:

  • Slow for large datasets
  • Limited ranking capabilities
  • No typo tolerance
  • Poor full-text search

OpenSearch solves these challenges with optimized indexing and search algorithms.

OpenSearch Architecture

flowchart LR
    USER[Client]

    API[Spring Boot]

    OS[(Amazon OpenSearch)]

    RDS[(Amazon Aurora)]

    USER --> API
    API --> OS
    API --> RDS

Enterprise Architecture

flowchart TD

Users

ALB

SpringBoot

OpenSearch

Aurora

CloudWatch

Users --> ALB
ALB --> SpringBoot
SpringBoot --> OpenSearch
SpringBoot --> Aurora
SpringBoot --> CloudWatch

Core Components

Component Description
Domain OpenSearch Cluster
Index Collection of Documents
Document JSON Record
Field JSON Attribute
Node Server
Shard Data Partition
Replica Copy of Shard

Real-Time Use Cases

Amazon OpenSearch is widely used for:

  • Product Search
  • Blog Search
  • Resume Search
  • Banking Transactions
  • Fraud Detection
  • Application Logs
  • Security Analytics
  • AI Knowledge Search
  • Customer Support Search
  • Recommendation Systems

OpenSearch Concepts

Index

Equivalent to a table.

Example

employees

Document

Equivalent to a row.

{
  "id":1,
  "name":"Venu",
  "department":"Architecture"
}

Field

Equivalent to a column.

Example:

name

department

designation

High-Level Flow

flowchart LR

Browser

SpringBoot

OpenSearch

Browser --> SpringBoot
SpringBoot --> OpenSearch

Search Workflow

flowchart LR

User

API

OpenSearch

Results

User --> API
API --> OpenSearch
OpenSearch --> Results

Database vs OpenSearch

Database OpenSearch
CRUD Search
ACID Eventually Consistent
Joins No Joins
Primary Storage Search Index
SQL Query DSL

Step 1 Create OpenSearch Domain

AWS Console

↓

Amazon OpenSearch Service

↓

Create Domain

Choose

Development and Testing

Learning purpose.

Production:

Production

Domain Configuration

Domain Name

codewithvenu-search

Engine Version

Latest available OpenSearch version.

Instance Type

Learning

t3.small.search

Production

m6g.large.search

or larger.

Storage

Enable

EBS GP3

20 GB

Network

Learning

Public Access

Production

VPC Only

Security

Enable

  • Fine-Grained Access Control
  • HTTPS
  • Encryption at Rest
  • Node-to-Node Encryption

Verify Domain

Status

Active

Step 2 Create Spring Boot Project

Dependencies

  • Spring Web
  • Validation
  • OpenSearch Java Client

Maven Dependencies

<dependency>
    <groupId>org.opensearch.client</groupId>
    <artifactId>opensearch-java</artifactId>
    <version>2.13.0</version>
</dependency>

<dependency>
    <groupId>org.apache.httpcomponents.client5</groupId>
    <artifactId>httpclient5</artifactId>
</dependency>

application.yml

opensearch:

  host: https://search-codewithvenu.us-east-1.es.amazonaws.com

  port: 443

Configure Client

@Configuration
public class OpenSearchConfig {

    @Bean
    public OpenSearchClient openSearchClient() {

        // Configure transport and authentication

        return null;

    }

}

Document Example

{
"id":1,
"name":"Venu",
"department":"Architecture",
"experience":13
}

Create Index

Index Name

employees

Indexing Flow

flowchart LR
    A["Spring Boot"]
    B["Index API"]
    C["OpenSearch"]

    A --> B
    B --> C

Create Document

REST API

POST

/employees

Input

{
"name":"Venu",
"department":"Architecture"
}

Search API

GET

/employees/search?q=venu

Output

[
{
"name":"Venu",
"department":"Architecture"
}
]

Update Document

PUT

/employees/1

Delete Document

DELETE

/employees/1

CRUD Flow

flowchart LR

Client

Controller

Service

OpenSearch

Client --> Controller
Controller --> Service
Service --> OpenSearch

Full-Text Search

Supports:

  • Exact Match
  • Partial Match
  • Phrase Search
  • Wildcards
  • Prefix Search
  • Fuzzy Search

Example Search

Search

Architecture

Returns

Architecture Lead

Solution Architect

Architecture Manager

Fuzzy Search

User types

Sprng Boot

OpenSearch returns

Spring Boot

Automatically.

Auto Complete

User types

jav

Suggestions

Java

Java Spring

Java AWS

Filters

Search

Department=Cloud

Experience>10

Aggregations

Examples

  • Employee Count
  • Salary Average
  • Orders Per Day
  • Revenue Per Month

Log Analytics

Applications send logs.

↓

OpenSearch

↓

Dashboards

↓

Visualization

OpenSearch Dashboards

Supports

  • Graphs
  • Charts
  • Tables
  • Monitoring
  • Alerts

Monitoring

CloudWatch Metrics

Monitor

  • CPU
  • JVM Memory
  • Storage
  • Search Latency
  • Index Latency
  • Thread Pools

Security

Enable

  • IAM Authentication
  • HTTPS
  • Encryption
  • Fine-Grained Access
  • VPC Access

Never expose your domain publicly in production.

Scaling

Increase

  • Data Nodes
  • Storage
  • Replicas

OpenSearch supports horizontal scaling.

Production Architecture

flowchart TD

Users

ALB

SpringBoot

OpenSearch

Aurora

CloudWatch

Users --> ALB
ALB --> SpringBoot
SpringBoot --> OpenSearch
SpringBoot --> Aurora
SpringBoot --> CloudWatch

Common Errors

Connection Refused

Check:

  • Security Group
  • Domain Endpoint
  • HTTPS

Authentication Failed

Verify IAM permissions.

Index Not Found

Create index before indexing documents.

Slow Search

Review:

  • Shard count
  • Query complexity
  • Mappings
  • Cluster health

Best Practices

  • Use OpenSearch only for search workloads
  • Keep relational data in Aurora or RDS
  • Use bulk indexing
  • Design index mappings carefully
  • Avoid very large documents
  • Enable snapshots
  • Monitor cluster health
  • Use VPC deployment
  • Enable encryption
  • Configure IAM access
  • Use aliases for index versioning
  • Monitor slow queries

OpenSearch vs Aurora

Feature Aurora OpenSearch
Purpose Database Search Engine
CRUD Yes Limited
SQL Yes No
Full Text Search Basic Excellent
Analytics Limited Advanced
Ranking No Yes

Interview Questions

What is Amazon OpenSearch?

A managed search and analytics service used for full-text search, log analytics, and real-time data exploration.

What is an Index?

A logical collection of documents, similar to a table in a relational database.

What is a Document?

A JSON object stored inside an index.

Difference between Aurora and OpenSearch?

Aurora is the system of record for transactional data, while OpenSearch is optimized for fast searching and analytics.

Why not use SQL LIKE instead of OpenSearch?

LIKE queries become slow on large datasets and lack advanced search capabilities such as relevance scoring, typo tolerance, stemming, and fuzzy matching.

What are Shards?

Shards partition an index across multiple nodes to improve scalability and parallel search performance.

Summary

In this article, we integrated Spring Boot with Amazon OpenSearch.

We covered:

  • OpenSearch fundamentals
  • Indexes and documents
  • Search architecture
  • Full-text search
  • CRUD operations
  • Query concepts
  • Monitoring
  • Security
  • Scaling
  • Production best practices

Amazon OpenSearch is an excellent choice for enterprise Spring Boot applications that require fast, scalable search, analytics, and log exploration while keeping transactional data in Amazon Aurora or Amazon RDS.

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