---

name: maintainx-data-handling description: 'Data synchronization, ETL patterns, and data management for MaintainX.

Use when syncing data between MaintainX and other systems,

building ETL pipelines, or managing data consistency.

Trigger with phrases like "maintainx data sync", "maintainx etl",

"maintainx export", "maintainx data migration", "maintainx data pipeline".

' allowed-tools: Read, Write, Edit, Bash(npm:*) version: 1.11.0 license: MIT author: Jeremy Longshore jeremy@intentsolutions.io tags:

• saas
• maintainx
• migration
• data-pipeline
• etl compatibility: Designed for Claude Code

---

MaintainX Data Handling

Overview

Patterns for synchronizing, transforming, and exporting data between MaintainX and external systems (databases, data warehouses, ERPs).

Prerequisites

• MaintainX API access configured
• Node.js 18+ with axios
• Target database or data warehouse available

Instructions

Step 1: Incremental Sync with Cursor Pagination

import { MaintainXClient } from './client';
import { writeFileSync, existsSync, readFileSync } from 'fs';

const SYNC_STATE_FILE = '.maintainx-sync-state.json';

interface SyncState {
  lastSyncAt: string;
  workOrderCursor?: string;
  assetCursor?: string;
}

function loadSyncState(): SyncState {
  if (existsSync(SYNC_STATE_FILE)) {
    return JSON.parse(readFileSync(SYNC_STATE_FILE, 'utf-8'));
  }
  return { lastSyncAt: new Date(0).toISOString() };
}

function saveSyncState(state: SyncState) {
  writeFileSync(SYNC_STATE_FILE, JSON.stringify(state, null, 2));
}

async function incrementalSync(client: MaintainXClient) {
  const state = loadSyncState();
  const syncStart = new Date().toISOString();

  console.log(`Syncing changes since ${state.lastSyncAt}`);

  // Sync work orders updated since last run
  let cursor: string | undefined;
  let totalWOs = 0;
  do {
    const response = await client.getWorkOrders({
      updatedAtGte: state.lastSyncAt,
      limit: 100,
      cursor,
    });
    for (const wo of response.workOrders) {
      await upsertWorkOrder(wo);  // Your DB write function
      totalWOs++;
    }
    cursor = response.cursor ?? undefined;
  } while (cursor);

  // Sync assets updated since last run
  let assetCursor: string | undefined;
  let totalAssets = 0;
  do {
    const response = await client.getAssets({
      updatedAtGte: state.lastSyncAt,
      limit: 100,
      cursor: assetCursor,
    });
    for (const asset of response.assets) {
      await upsertAsset(asset);  // Your DB write function
      totalAssets++;
    }
    assetCursor = response.cursor ?? undefined;
  } while (assetCursor);

  saveSyncState({ lastSyncAt: syncStart });
  console.log(`Synced ${totalWOs} work orders, ${totalAssets} assets`);
}

Step 2: Export to CSV

import { createWriteStream } from 'fs';

async function exportWorkOrdersToCSV(client: MaintainXClient, outputPath: string) {
  const stream = createWriteStream(outputPath);
  stream.write('id,title,status,priority,assignee,asset,location,created_at,completed_at\n');

  let cursor: string | undefined;
  let count = 0;

  do {
    const response = await client.getWorkOrders({ limit: 100, cursor });
    for (const wo of response.workOrders) {
      const row = [
        wo.id,
        `"${(wo.title || '').replace(/"/g, '""')}"`,
        wo.status,
        wo.priority,
        wo.assignees?.map((a: any) => a.id).join(';') || '',
        wo.assetId || '',
        wo.locationId || '',
        wo.createdAt,
        wo.completedAt || '',
      ].join(',');
      stream.write(row + '\n');
      count++;
    }
    cursor = response.cursor ?? undefined;
  } while (cursor);

  stream.end();
  console.log(`Exported ${count} work orders to ${outputPath}`);
}

// Usage
await exportWorkOrdersToCSV(client, 'work-orders-export.csv');

Step 3: Export to BigQuery

import { BigQuery } from '@google-cloud/bigquery';

const bq = new BigQuery({ projectId: 'your-project' });
const dataset = bq.dataset('maintenance');
const table = dataset.table('work_orders');

async function syncToBigQuery(client: MaintainXClient) {
  let cursor: string | undefined;
  const batch: any[] = [];

  do {
    const response = await client.getWorkOrders({ limit: 100, cursor });
    for (const wo of response.workOrders) {
      batch.push({
        id: wo.id,
        title: wo.title,
        status: wo.status,
        priority: wo.priority,
        asset_id: wo.assetId,
        location_id: wo.locationId,
        created_at: wo.createdAt,
        completed_at: wo.completedAt,
        synced_at: new Date().toISOString(),
      });
    }
    cursor = response.cursor ?? undefined;
  } while (cursor);

  if (batch.length > 0) {
    await table.insert(batch);
    console.log(`Inserted ${batch.length} rows into BigQuery`);
  }
}

Step 4: Data Reconciliation

async function reconcile(client: MaintainXClient, localDb: any) {
  const remoteOrders = await paginate(
    (cursor) => client.getWorkOrders({ limit: 100, cursor }),
    'workOrders',
  );
  const localOrders = await localDb.query('SELECT id, updated_at FROM work_orders');

  const remoteMap = new Map(remoteOrders.map((wo: any) => [wo.id, wo.updatedAt]));
  const localMap = new Map(localOrders.map((row: any) => [row.id, row.updated_at]));

  const missing = remoteOrders.filter((wo: any) => !localMap.has(wo.id));
  const stale = remoteOrders.filter(
    (wo: any) => localMap.has(wo.id) && localMap.get(wo.id) < remoteMap.get(wo.id),
  );
  const orphaned = localOrders.filter((row: any) => !remoteMap.has(row.id));

  console.log(`Missing locally: ${missing.length}`);
  console.log(`Stale locally: ${stale.length}`);
  console.log(`Orphaned locally: ${orphaned.length}`);

  return { missing, stale, orphaned };
}

Output

• Incremental sync with persistent cursor state
• CSV export of work orders with proper quoting
• BigQuery streaming insert pipeline
• Data reconciliation report (missing, stale, orphaned records)

Error Handling

Issue	Cause	Solution
429 Rate Limited	Too many requests during sync	Add delays between pages, use p-queue
Partial sync failure	Network error mid-pagination	Save cursor state, resume from last position
Duplicate rows in BigQuery	Re-running without dedup	Use MERGE or dedup on (id, updated_at)
Stale local data	Missed webhook or sync gap	Run full reconciliation, then incremental

Resources

• MaintainX API Reference
• BigQuery Node.js Client
• csv-parse -- CSV parsing for imports

Next Steps

For enterprise access control, see maintainx-enterprise-rbac.

Examples

Scheduled sync with cron:

// Run every 15 minutes via cron or node-schedule
import cron from 'node-cron';

cron.schedule('*/15 * * * *', async () => {
  console.log('Starting incremental sync...');
  await incrementalSync(new MaintainXClient());
});

Import work orders from a legacy CMMS CSV:

import { parse } from 'csv-parse/sync';
import { readFileSync } from 'fs';

const rows = parse(readFileSync('legacy-export.csv'), { columns: true });
for (const row of rows) {
  await client.createWorkOrder({
    title: row['Work Order Name'],
    description: row['Description'],
    priority: row['Priority'].toUpperCase(),
    categories: [row['Type'].toUpperCase()],
  });
}