hubspot-performance-tuning

HubSpot Performance Tuning

Overview

Optimize HubSpot API performance through batch operations, caching, search optimization, and request minimization.

Prerequisites

• @hubspot/api-client installed
• Understanding of your access patterns (read-heavy vs write-heavy)
• Optional: Redis for distributed caching

Instructions

Step 1: Use Batch APIs Everywhere

The single biggest performance win: batch operations reduce API calls by up to 100x.

import * as hubspot from '@hubspot/api-client';

const client = new hubspot.Client({
  accessToken: process.env.HUBSPOT_ACCESS_TOKEN!,
  numberOfApiCallRetries: 3,
});

// BAD: 100 API calls for 100 contacts
async function getContactsSlow(ids: string[]) {
  return Promise.all(ids.map(id =>
    client.crm.contacts.basicApi.getById(id, ['email', 'firstname'])
  ));
}

// GOOD: 1 API call for 100 contacts
async function getContactsFast(ids: string[], properties: string[]) {
  // POST /crm/v3/objects/contacts/batch/read
  const result = await client.crm.contacts.batchApi.read({
    inputs: ids.map(id => ({ id })),
    properties,
    propertiesWithHistory: [],
  });
  return result.results;
}

// For more than 100 records, chunk:
async function getContactsChunked(ids: string[], properties: string[]) {
  const results = [];
  for (let i = 0; i < ids.length; i += 100) {
    const chunk = ids.slice(i, i + 100);
    const batch = await getContactsFast(chunk, properties);
    results.push(...batch);
  }
  return results;
}

Step 2: Request Only Needed Properties

// BAD: Returns ALL default properties (slow, large payload)
const contact = await client.crm.contacts.basicApi.getById(id);

// GOOD: Only request what you need (fast, small payload)
const contact = await client.crm.contacts.basicApi.getById(
  id,
  ['email', 'firstname', 'lastname', 'lifecyclestage'] // specific properties
);

Step 3: Cache Frequently Accessed Data

import { LRUCache } from 'lru-cache';

const contactCache = new LRUCache<string, any>({
  max: 5000,              // max entries
  ttl: 5 * 60 * 1000,     // 5 minute TTL
  updateAgeOnGet: true,
});

async function getCachedContact(id: string, properties: string[]) {
  const cacheKey = `contact:${id}`;
  const cached = contactCache.get(cacheKey);
  if (cached) return cached;

  const contact = await client.crm.contacts.basicApi.getById(id, properties);
  contactCache.set(cacheKey, contact);
  return contact;
}

// Invalidate on webhook events
function invalidateContactCache(contactId: string): void {
  contactCache.delete(`contact:${contactId}`);
}

Step 4: Optimize Search Queries

// BAD: Overly broad search, returns too much data
const bad = await client.crm.contacts.searchApi.doSearch({
  filterGroups: [],  // no filters = scan entire DB
  properties: [],    // returns default properties
  limit: 100,
  after: 0,
  sorts: [],
});

// GOOD: Specific filters, minimal properties, sorted
const good = await client.crm.contacts.searchApi.doSearch({
  filterGroups: [{
    filters: [
      { propertyName: 'lifecyclestage', operator: 'EQ', value: 'customer' },
      { propertyName: 'createdate', operator: 'GTE', value: String(Date.now() - 86400000) },
    ],
  }],
  properties: ['email', 'firstname'],  // only what you need
  limit: 50,
  after: 0,
  sorts: [{ propertyName: 'createdate', direction: 'DESCENDING' }],
});

// Search limits: max 5 filterGroups, 6 filters per group, 18 filters total
// Search returns max 10,000 results total (pagination limit)

Step 5: Pipeline and Property Caching

Pipeline stages and custom properties rarely change -- cache them aggressively:

let pipelineCache: Map<string, any> | null = null;
let pipelineCacheExpiry = 0;

async function getCachedPipelines(objectType: 'deals' | 'tickets') {
  if (pipelineCache && Date.now() < pipelineCacheExpiry) {
    return pipelineCache.get(objectType);
  }

  const pipelines = await client.crm.pipelines.pipelinesApi.getAll(objectType);
  if (!pipelineCache) pipelineCache = new Map();
  pipelineCache.set(objectType, pipelines.results);
  pipelineCacheExpiry = Date.now() + 3600000; // 1 hour cache
  return pipelines.results;
}

// Same pattern for properties
let propertyCache: Map<string, any> | null = null;

async function getCachedProperties(objectType: string) {
  if (propertyCache?.has(objectType)) {
    return propertyCache.get(objectType);
  }
  const props = await client.crm.properties.coreApi.getAll(objectType);
  if (!propertyCache) propertyCache = new Map();
  propertyCache.set(objectType, props.results);
  return props.results;
}

Step 6: Pagination with Async Generators

// Memory-efficient streaming for large exports
async function* streamAllContacts(properties: string[]) {
  let after: string | undefined;
  do {
    const page = await client.crm.contacts.basicApi.getPage(
      100,    // max page size
      after,
      properties
    );
    yield* page.results;
    after = page.paging?.next?.after;
  } while (after);
}

// Process millions of records without running out of memory
let count = 0;
for await (const contact of streamAllContacts(['email', 'firstname'])) {
  await processContact(contact);
  count++;
  if (count % 1000 === 0) console.log(`Processed ${count} contacts`);
}

Output

• Batch operations reducing API calls by 100x
• Property-specific requests reducing payload size
• LRU caching for frequently accessed records
• Optimized search queries with proper filters
• Streaming pagination for large datasets

Error Handling

Issue	Cause	Solution
Batch returns 207 Multi-Status	Some records failed	Check individual status in response
Cache stale data	TTL too long	Invalidate on webhook events
Search returns max 10,000	HubSpot search limit	Use getPage pagination instead
Memory pressure	Caching too much	Set max entries on LRU cache

Resources

• Batch Operations Guide
• CRM Search Guide
• lru-cache npm

Next Steps

For cost optimization, see hubspot-cost-tuning.