---
title: "Can you separate concerns using multiple object stores efficiently? When would you avoid that?"  
description: "Can you separate concerns using multiple object stores efficiently? When would you avoid that?"  
author: "Ponu Maurya"  
published: 2025-07-06  
updated: 2025-07-06  
canonical: https://www.mindstick.com/interview/34321/can-you-separate-concerns-using-multiple-object-stores-efficiently-when-would-you-avoid-that  
category: "database"  
tags: ["database", "indexeddb"]  
reading_time: 5 minutes  

---

# Can you separate concerns using multiple object stores efficiently? When would you avoid that?

Yes, you **can and should separate concerns using multiple object stores** in IndexedDB — but it depends on your app’s complexity and access patterns.

Here’s when to do it, when not to, and how to do it **efficiently**.

## When You Should Use Multiple Object Stores

### Use Case: Clearly Different Entities

If your app has **different types of data** (e.g., users, notes, settings), each should live in its own store.

#### Example:

```plaintext
db.createObjectStore("users", { keyPath: "id" });
db.createObjectStore("notes", { keyPath: "id" });
db.createObjectStore("settings", { keyPath: "key" });
```

### Benefits:

| Benefit | Why It Helps |
| --- | --- |
| **Separation of concerns** | Easier to maintain and reason about data |
| **Targeted queries** | You query only what you need (e.g., only `notes`) |
| **Custom keyPath per store** | `users` may use `id`, `settings` use `key` |
| **Easier migrations** | You can upgrade one store without affecting others |

## When to Avoid Too Many Object Stores

Too many stores can be overkill and inefficient.

### Avoid if:

- You just want to categorize similar items (use a `type` field instead).
- You plan to **query across** multiple stores (joins are hard in IndexedDB).
- Your entities are tightly coupled and always used together.

#### Example:

If you're storing:

```plaintext
{ id: "1", type: "note", content: "..." }
{ id: "2", type: "task", content: "..." }
```

You could use a single `items` store with a `type` field and index on `type`.

## Efficient Multi-Store Use Tips

### 1. Use Indexes Instead of Separate Stores for Categories

```javascript
store.createIndex("type", "type");
```

Then:

```javascript
store.index("type").getAll("note");
```

### 2. Avoid Unnecessary Transactions

Only open a transaction for the store(s) you need:

```javascript
const tx = db.transaction(["users", "notes"], "readonly");
```

### 3. Batch Related Data Together (if tightly coupled)

If you always access a `note` and its `tags` together, maybe they should be stored together.

## Rule of Thumb

| Decision Point | Recommendation |
| --- | --- |
| Clearly different data types | Use multiple stores |
| Same structure, just different categories | Use one store with a `type` field & index |
| Need to query across stores | Use a single store or denormalize |
| Need to version or migrate independently | Use separate stores |

## Example Design: Multi-Store

```plaintext
users/
  - userId (key)
  - name, email

notes/
  - noteId (key)
  - userId (FK), content, tags, updatedAt

settings/
  - key (key)
  - value
```

Each store handles a single responsibility — making updates, queries, and migrations clean and isolated.

## Conclusion

## Multiple object stores are efficient when:

- Data types are unrelated
- You want better organization
- You avoid cross-store joins

## Avoid them when:

- Data is tightly coupled
- You’d need complex joins
- It leads to excessive schema complexity

## Answers

### Answer by Ponu Maurya

Yes, you **can and should separate concerns using multiple object stores** in IndexedDB — but it depends on your app’s complexity and access patterns.

Here’s when to do it, when not to, and how to do it **efficiently**.

## When You Should Use Multiple Object Stores

### Use Case: Clearly Different Entities

If your app has **different types of data** (e.g., users, notes, settings), each should live in its own store.

#### Example:

```plaintext
db.createObjectStore("users", { keyPath: "id" });
db.createObjectStore("notes", { keyPath: "id" });
db.createObjectStore("settings", { keyPath: "key" });
```

### Benefits:

| Benefit | Why It Helps |
| --- | --- |
| **Separation of concerns** | Easier to maintain and reason about data |
| **Targeted queries** | You query only what you need (e.g., only `notes`) |
| **Custom keyPath per store** | `users` may use `id`, `settings` use `key` |
| **Easier migrations** | You can upgrade one store without affecting others |

## When to Avoid Too Many Object Stores

Too many stores can be overkill and inefficient.

### Avoid if:

- You just want to categorize similar items (use a `type` field instead).
- You plan to **query across** multiple stores (joins are hard in IndexedDB).
- Your entities are tightly coupled and always used together.

#### Example:

If you're storing:

```plaintext
{ id: "1", type: "note", content: "..." }
{ id: "2", type: "task", content: "..." }
```

You could use a single `items` store with a `type` field and index on `type`.

## Efficient Multi-Store Use Tips

### 1. Use Indexes Instead of Separate Stores for Categories

```javascript
store.createIndex("type", "type");
```

Then:

```javascript
store.index("type").getAll("note");
```

### 2. Avoid Unnecessary Transactions

Only open a transaction for the store(s) you need:

```javascript
const tx = db.transaction(["users", "notes"], "readonly");
```

### 3. Batch Related Data Together (if tightly coupled)

If you always access a `note` and its `tags` together, maybe they should be stored together.

## Rule of Thumb

| Decision Point | Recommendation |
| --- | --- |
| Clearly different data types | Use multiple stores |
| Same structure, just different categories | Use one store with a `type` field & index |
| Need to query across stores | Use a single store or denormalize |
| Need to version or migrate independently | Use separate stores |

## Example Design: Multi-Store

```plaintext
users/
  - userId (key)
  - name, email

notes/
  - noteId (key)
  - userId (FK), content, tags, updatedAt

settings/
  - key (key)
  - value
```

Each store handles a single responsibility — making updates, queries, and migrations clean and isolated.

## Conclusion

## Multiple object stores are efficient when:

- Data types are unrelated
- You want better organization
- You avoid cross-store joins

## Avoid them when:

- Data is tightly coupled
- You’d need complex joins
- It leads to excessive schema complexity


---

Original Source: https://www.mindstick.com/interview/34321/can-you-separate-concerns-using-multiple-object-stores-efficiently-when-would-you-avoid-that

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