Collections

Efficiently store, access, and manage data in smart contracts.

When deciding on data structures it is important to understand their tradeoffs. Choosing the wrong structure can create a bottleneck as the application scales, and migrating the state to the new data structures will come at a cost.

You can choose between two types of collections:

1. Native collections (e.g. Array, Map, Set), provided by the language
2. SDK collections (e.g. IterableMap, Vector), provided by the NEAR SDK

Native vs SDK Collections

Use native collections for small amounts of data that need to be accessed altogether, and SDK collections for large amounts of data that do not need to be accessed altogether.

If your collection has up to 100 entries, it’s acceptable to use the native collection. For larger ones, prefer to use SDK collection. For comparison please refer to this benchmark.

---

Storage Management

Each time the contract is executed, the first thing it will do is to read the values and deserialize them into memory, and after the function finishes, it will serialize and write the values back to the database.

For native collections, the contract will fully load the collection into memory before any method executes. This happens even if the method you invoke does not use the collection. Know that this will have impact on GAS you spend for methods in your contract.

Storage Cost

Your contract needs to lock a portion of their balance proportional to the amount of data they stored in the blockchain. This means that:

• If more data is added the storage increases ↑, and your contract’s balance decreases ↓.
• If data is deleted the storage decreases ↓, and your contract’s balance increases ↑.

Currently, it costs approximately 1 Ⓝ to store 100kb of data.

Storage Constraints on NEAR

For storing data on-chain it’s important to keep in mind the following:

• There is a 4mb limit on how much you can upload at once

Let’s say for example, someone wants to put an NFT purely on-chain (rather than IPFS or some other decentralized storage solution) you’ll have almost an unlimited amount of storage but will have to pay 1 $NEAR per 100kb of storage used.

Users will be limited to 4MB per contract call upload due to MAX_GAS constraints. The maximum amount of gas one can attach to a given functionCall is 300TGas.

Your contract will panic if you try to store data but don’t have NEAR to cover its storage cost

Be mindful of potential small deposit attacks

---

Native Collections

Native collections are those provided by the language, such as Array, Map, Set in Javascript, or Vec, HashMap, HashSet in Rust.

All entries in a native collection are serialized into a single value and stored together into the state. This means that every time a function execute, the SDK will read and deserialize all entries in the native collection.

Serialization & Storage Example

The array [1,2,3,4] will be serialized into the JSON string "[1,2,3,4]" in Javascript, and the Borsh byte-stream [0,0,0,4,1,2,3,4] in Rust before being stored

When to use them

Native collections are useful if you are planning to store smalls amounts of data that need to be accessed all together

Keep Native Collections Small

As the native collection grows, deserializing it from memory will cost more and more gas. If the collections grows too large, your contract might expend all the gas trying to read its state, making it fail on each function call

---

SDK Collections

The NEAR SDKs expose collections that are optimized for random access of large amounts of data. SDK collections are instantiated using a “prefix”, which is used as an index to split the data into chunks. This way, SDK collections can defer reading and writing to the store until needed.

Serialization & Storage Example

The sdk array [1,2,3,4] with prefix "p" will be stored as the string "p" in the contract’s attribute, and create four entries in the contract’s storage: p-0:1, p-1:2…

SDK Collections' Features

Type	SDK Module	Iterable	Clear All Values	Preserves Insertion Order	Range Selection
Vector	near_sdk::store	✅	✅	✅	✅
LookupSet	near_sdk::store
UnorderedSet	near_sdk::collections ⚠️	✅	✅		✅
IterableSet	near_sdk::store	✅	✅		✅
LookupMap	near_sdk::store
UnorderedMap	near_sdk::collections ⚠️	✅	✅		✅
IterableMap	near_sdk::store	✅	✅		✅
TreeMap	near_sdk::collections ⚠️	✅	✅	✅	✅

⚠️ Legacy collections from near_sdk::collections. Prefer near_sdk::store equivalents for new contracts.

SDK Collections' Time Complexities

Type	Access	Insert	Delete	Search	Traverse	Clear
Vector	O(1)	O(1)*	O(1)**	O(n)	O(n)	O(n)
LookupSet	O(1)	O(1)	O(1)	O(1)	N/A	N/A
UnorderedSet	O(1)	O(1)	O(1)	O(1)	O(n)	O(n)
IterableSet	O(1)	O(1)	O(1)	O(1)	O(n)	O(n)
LookupMap	O(1)	O(1)	O(1)	O(1)	N/A	N/A
IterableMap	O(1)	O(1)	O(1)	O(1)	O(n)	O(n)
TreeMap	O(1)	O(log n)	O(log n)	O(log n)	O(n)	O(n)

* - to insert at the end of the vector using push_back (or push_front for deque) ** - to delete from the end of the vector using pop (or pop_front for deque), or delete using swap_remove which swaps the element with the last element of the vector and then removes it.

These collections are built to have an interface similar to native collections.

when to use them

SDK collections are useful when you are planning to store large amounts of data that do not need to be accessed all together

Instantiation

All structures need to be initialized using a unique prefix, which will be used to index the collection’s values in the account’s state

🦀 Rust

Notice how we use enums to ensure all collections have a different prefix. Another advantage of using enums is that they are serialized into a single byte prefix.

If you see a unresolved import near_sdk::BorshIntoStorageKey compiler error, your code is following an outdated pattern from near-sdk < 4.0.

To fix it, derive BorshStorageKey on your prefix enum.

🌐 JavaScript

Do not forget to use the schema to define how your contract’s state is structured

🐍 Python

from near_sdk_py import view, call, init
from near_sdk_py.collections import Vector, LookupMap, UnorderedMap, LookupSet, UnorderedSet

class MyContract:
@init
def new(self): # Create a Vector with prefix "v"
self.my_vector = Vector("v")

        # Create a LookupMap with prefix "m"
        self.my_lookup_map = LookupMap("m")

        # Create an UnorderedMap with prefix "um"
        self.my_unordered_map = UnorderedMap("um")

        # Create a LookupSet with prefix "s"
        self.my_lookup_set = LookupSet("s")

        # Create an UnorderedSet with prefix "us"
        self.my_unordered_set = UnorderedSet("us")

        # For nested collections, use different prefixes
        self.nested_maps = UnorderedMap("nested")

        return True

    @call
    def create_nested_map(self, key: str):
        # Create a new map that will be stored inside another map
        inner_map = UnorderedMap(f"inner_{key}")
        self.nested_maps[key] = inner_map
        return {"success": True}

🐹 GO

Be careful of not using the same prefix in two collections, otherwise, their storage space will collide, and you might overwrite information from one collection when writing in the other

---

Vector

Implements a vector/array which persists in the contract’s storage. Please refer to the Rust and JS SDK’s for a full reference on their interfaces.

🦀 Rust

🌐 JavaScript

🐍 Python

from near_sdk_py import view, call, init
from near_sdk_py.collections import Vector

class VectorExample:
    @init
    def new(self):
        # Create a Vector with prefix "v"
        self.my_vector = Vector("v")

    @call
    def add_number(self, number):
        # Append a value to the vector
        self.my_vector.append(number)
        return len(self.my_vector)

    @view
    def get_number(self, index):
        # Get a value at specific index
        try:
            return self.my_vector[index]
        except Exception:
            return None

    @view
    def get_all_numbers(self):
        # Convert entire vector to a list
        return [num for num in self.my_vector]

🐹 GO

---

LookupMap

Implements a map/dictionary which persists in the contract’s storage. Please refer to the Rust and JS SDK’s for a full reference on their interfaces.

🦀 Rust

🌐 JavaScript

🐍 Python

from near_sdk_py import view, call, init
from near_sdk_py.collections import LookupMap

class LookupMapExample:
    @init
    def new(self):
        # Create a LookupMap with prefix "m"
        self.balances = LookupMap("m")

    @call
    def set_balance(self, account_id, amount):
        # Set a value for a key
        self.balances[account_id] = amount
        return True

    @view
    def get_balance(self, account_id):
        # Get a value for a key with a default
        return self.balances.get(account_id, 0)

    @call
    def remove_balance(self, account_id):
        # Remove a key
        if account_id in self.balances:
            del self.balances[account_id]
            return True
        return False

🐹 GO

---

UnorderedMap / IterableMap

Implements a map/dictionary which persists in the contract’s storage. Please refer to the Rust and JS SDK’s for a full reference on their interfaces.

UnorderedMap vs IterableMap (Rust)

UnorderedMap belongs to the legacy near_sdk::collections module. IterableMap is its modern replacement in near_sdk::store, and should be preferred for new contracts. The store collections cache reads and writes within a single transaction, making them more gas-efficient when the same key is accessed multiple times.

🦀 Rust

🌐 JavaScript

🐍 Python

from near_sdk_py import view, call, init
from near_sdk_py.collections import UnorderedMap

class UnorderedMapExample:
    @init
    def new(self):
        # Create an UnorderedMap with prefix "um"
        self.user_data = UnorderedMap("um")

    @call
    def set_user_data(self, account_id, data):
        # Set a value for a key
        self.user_data[account_id] = data
        return True

    @view
    def get_user_data(self, account_id):
        # Get a value for a key
        try:
            return self.user_data[account_id]
        except Exception:
            return None

    @view
    def list_all_users(self):
        # Iterate through keys and values
        return {
            "keys": self.user_data.keys(),
            "values": self.user_data.values(),
            "items": self.user_data.items()
        }

🐹 GO

---

LookupSet

Implements a set which persists in the contract’s storage. Please refer to the Rust and JS SDK’s for a full reference on their interfaces.

🦀 Rust

🌐 JavaScript

🐍 Python

from near_sdk_py import view, call, init
from near_sdk_py.collections import LookupSet

class LookupSetExample:
    @init
    def new(self):
        # Create a LookupSet with prefix "s"
        self.whitelist = LookupSet("s")

    @call
    def add_to_whitelist(self, account_id):
        # Add a value to the set
        self.whitelist.add(account_id)
        return True

    @view
    def is_whitelisted(self, account_id):
        # Check if a value exists in the set
        return account_id in self.whitelist

    @call
    def remove_from_whitelist(self, account_id):
        # Remove a value from the set
        try:
            self.whitelist.remove(account_id)
            return True
        except Exception:
            return False

🐹 GO

---

UnorderedSet / IterableSet

Implements a set which persists in the contract’s storage. Please refer to the Rust and JS SDK’s for a full reference on their interfaces.

🦀 Rust

UnorderedSet vs IterableSet

UnorderedSet belongs to the legacy near_sdk::collections module. IterableSet is its modern replacement in near_sdk::store, and should be preferred for new contracts. The store collections cache reads and writes within a single transaction, making them more gas-efficient when the same key is accessed multiple times.

🌐 JavaScript

🐍 Python

from near_sdk_py import view, call, init
from near_sdk_py.collections import UnorderedSet

class UnorderedSetExample:
    @init
    def new(self):
        # Create an UnorderedSet with prefix "us"
        self.owners = UnorderedSet("us")

    @call
    def register_owner(self, account_id):
        # Add a value to the set
        self.owners.add(account_id)
        return True

    @view
    def is_owner(self, account_id):
        # Check if a value exists in the set
        return account_id in self.owners

    @view
    def list_all_owners(self):
        # Get all values as a list
        return self.owners.values()

    @call
    def remove_owner(self, account_id):
        # Try to remove a value if it exists
        self.owners.discard(account_id)
        return True

🐹 GO

---

Tree

An ordered equivalent of Map. The underlying implementation is based on an AVL. You should use this structure when you need to: have a consistent order, or access the min/max keys.

🦀 Rust

🐍 Python

from near_sdk_py import view, call, init
from near_sdk_py.collections import TreeMap

class TreeMapExample:
    @init
    def new(self):
        # Create a TreeMap with prefix "tm"
        self.scores = TreeMap("tm")

    @call
    def add_score(self, user_id, score):
        # Set score for a user
        self.scores[user_id] = score
        return True

    @view
    def get_top_scores(self, limit=10):
        # Get top scores using ordered keys
        top_users = []
        max_key = self.scores.max_key()
        current_key = max_key
        count = 0

        while current_key is not None and count < limit:
            top_users.append({
                "user": current_key,
                "score": self.scores[current_key]
            })
            current_key = self.scores.floor_key(current_key - 1)
            count += 1

        return top_users

🐹 GO

---

Nesting Collections

When nesting SDK collections, be careful to use different prefixes for all collections, including the nested ones.

🦀 Rust

Notice how we use enums that take a String argument to ensure all collections have a different prefix

🌐 JavaScript

🐍 Python

from near_sdk_py import view, call, init
from near_sdk_py.collections import UnorderedMap, Vector
from near_sdk_py.collections import create_prefix_guard

class NestedCollectionsExample:
    @init
    def new(self):
        # Main map of users to their assets
        self.user_assets = UnorderedMap("users")

    @call
    def add_asset(self, user_id, asset_id, metadata):
        # Get or create the user's assets vector with a unique prefix
        if user_id not in self.user_assets:
            # Create a prefix guard to ensure unique prefixes for this user
            prefix = f"assets:{user_id}"
            # Create a new vector for this user's assets
            self.user_assets[user_id] = Vector(prefix)

        # Add the asset to the user's assets vector
        user_assets = self.user_assets[user_id]
        user_assets.append({
            "asset_id": asset_id,
            "metadata": metadata
        })

        # Update the vector in the map
        self.user_assets[user_id] = user_assets
        return True

    @view
    def get_user_assets(self, user_id):
        if user_id not in self.user_assets:
            return []

        # Get all assets for the user
        user_assets = self.user_assets[user_id]
        return [asset for asset in user_assets]

In Python, we create unique prefixes for nested collections by including the parent’s identifier in the prefix string. The SDK also provides a create_prefix_guard utility to help manage prefixes.

🐹 GO

In Go, nested Vector collections must have their Len persisted separately (e.g., in a LookupMap[string, uint64]). When reconstructing a vector, pass the saved length via &collections.Vector[string]{Prefix: prefix, Len: savedLen}. Always use unique prefixes across all collections.

---

Error prone patterns

Because the values are not kept in memory and are lazily loaded from storage, it’s important to make sure if a collection is replaced or removed, that the storage is cleared. In addition, it is important that if the collection is modified, the collection itself is updated in state because most collections will store some metadata.

Some error-prone patterns to avoid that cannot be restricted at the type level are:

🦀 Rust

use near_sdk::store::UnorderedMap;

let mut m = UnorderedMap::<u8, String>::new(b"m");
m.insert(1, "test".to_string());
assert_eq!(m.len(), 1);
assert_eq!(m.get(&1), Some(&"test".to_string()));

// Bug 1: Should not replace any collections without clearing state, this will reset any
// metadata, such as the number of elements, leading to bugs. If you replace the collection
// with something with a different prefix, it will be functional, but you will lose any
// previous data and the old values will not be removed from storage.
m = UnorderedMap::new(b"m");
assert!(m.is_empty());
assert_eq!(m.get(&1), Some(&"test".to_string()));

// Bug 2: Should not use the same prefix as another collection
// or there will be unexpected side effects.
let m2 = UnorderedMap::<u8, String>::new(b"m");
assert!(m2.is_empty());
assert_eq!(m2.get(&1), Some(&"test".to_string()));

// Bug 3: forgetting to save the collection in storage. When the collection is attached to
// the contract state (`self` in `#[near]`) this will be done automatically, but if
// interacting with storage manually or working with nested collections, this is relevant.
use near_sdk::store::Vector;

// Simulate roughly what happens during a function call that initializes state.
{
    let v = Vector::<u8>::new(b"v");
    near_sdk::env::state_write(&v);
}

// Simulate what happens during a function call that just modifies the collection
// but does not store the collection itself.
{
    let mut v: Vector<u8> = near_sdk::env::state_read().unwrap();
    v.push(1);
    // The bug is here that the collection itself if not written back
}

let v: Vector<u8> = near_sdk::env::state_read().unwrap();
// This will report as if the collection is empty, even though the element exists
assert!(v.get(0).is_none());
assert!(
    near_sdk::env::storage_read(&[b"v".as_slice(), &0u32.to_le_bytes()].concat()).is_some()
);

// Bug 4 (only relevant for `near_sdk::store`): These collections will cache writes as well
// as reads, and the writes are performed on [`Drop`](https://doc.rust-lang.org/std/ops/trait.Drop.html)
// so if the collection is kept in static memory or something like `std::mem::forget` is used,
// the changes will not be persisted.
use near_sdk::store::IterableSet;

let mut m: IterableSet<u8> = IterableSet::new(b"l");
m.insert(1);
assert!(m.contains(&1));

// This would be the fix, manually flushing the intermediate changes to storage.
// m.flush();
std::mem::forget(m);

m = IterableSet::new(b"l");
assert!(!m.contains(&1));

🌐 JavaScript

import { UnorderedMap, Vector } from "near-sdk-js";

const m = new UnorderedMap<string>("m");
m.set("1", "test");

// Bug 1: Don't replace a collection without clearing it first. The new object
// resets its metadata (length, keys), but the old elements stay in storage,
// leaving the collection inconsistent and orphaning the previous values.
// Fix: call `m.clear()` before reusing the prefix.
const m2 = new UnorderedMap<string>("m");
// m2.length is 0, but the "1" -> "test" entry is still in storage under prefix "m"

// Bug 2: Don't use the same prefix for two different collections, or they will
// read and write the same keys and corrupt each other. Note that `UnorderedMap`
// internally creates sub-collections at `prefix + "u"` and `prefix + "m"`, so
// even prefixes that merely overlap can collide.
const v = new Vector<string>("m"); // collides with the maps above

// Bug 3: With nested collections, mutating the inner collection writes its
// elements immediately, but you must still write the inner collection back into
// the outer one so its metadata entry is persisted.
const outer = new UnorderedMap<UnorderedMap<string>>("o");
const inner = outer.get("id", {
  reconstructor: UnorderedMap.reconstruct,
  defaultValue: new UnorderedMap<string>("i_id_"),
});
inner.set("key", "value");
outer.set("id", inner); // <- forgetting this loses the inner collection's metadata

Unlike Rust’s near_sdk::store, near-sdk-js collections are not write-cached: every mutation writes to storage immediately, so there is no flush() to forget. Just don’t mutate collections inside a @view method, since the contract state is only persisted after @call methods.

🐹 GO

---

Pagination

Persistent collections such as IterableMap/UnorderedMap, IterableSet/UnorderedSet and Vector may contain more elements than the amount of gas available to read them all. In order to expose them all through view calls, we can use pagination.

🦀 Rust

With Rust this can be done using iterators with Skip and Take. This will only load elements from storage within the range.

  #[near(contract_state)]
  #[derive(PanicOnDefault)]
  pub struct Contract {
      pub status_updates: IterableMap<AccountId, String>,
  }

  #[near]
  impl Contract {
      /// Retrieves multiple elements from the `IterableMap`.
      /// - `from_index` is the index to start from.
      /// - `limit` is the maximum number of elements to return.
      pub fn get_updates(&self, from_index: usize, limit: usize) -> Vec<(AccountId, String)> {
          self.status_updates
              .iter()
              .skip(from_index)
              .take(limit)
              .collect()
      }
  }

🌐 JavaScript

With JavaScript this can be done using iterators with toArray and slice.

  /// Returns multiple elements from the `UnorderedMap`.
  /// - `from_index` is the index to start from.
  /// - `limit` is the maximum number of elements to return.
  @view({})
  get_updates({ from_index, limit }: { from_index: number, limit:number }) {
    return this.status_updates.toArray().slice(from_index, limit);
  }

🐍 Python

# With Python this can be done using standard list slicing.

@view
def get_updates(self, from_index: int = 0, limit: int = 50) -> list:
    """Returns multiple elements from the collection with pagination."""
    all_items = self.status_updates.values()
    start = min(from_index, len(all_items))
    end = min(start + limit, len(all_items))
    return all_items[start:end]

🐹 GO

With Go this can be done using index-based iteration over a Vector, loading only the elements within the requested range.