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Terminal.skills
Use Cases/Build a Bidirectional Data Sync Engine

Build a Bidirectional Data Sync Engine

Build a bidirectional data sync engine with conflict resolution, change tracking, offline support, incremental sync, and webhook notifications for multi-system data consistency.

#redis#caching#database#pub-sub#queues
Works with:claude-codeopenai-codexgemini-clicursor

Skills stack · 5 skills

Avg quality 93/100·All SAFE
>

typescript

v

Not yet scored
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>

redis

v1.0.0

Build applications with Redis — caching, session storage, pub/sub, streams, rate limiting, leaderboards, and queues. Use when tasks involve in-memory data storage, real-time messaging, distributed locking, or performance optimization with caching layers.

93/100 quality
1.81× impact
SAFE
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postgresql

v1.0.0

Assists with designing schemas, writing performant queries, managing indexes, and operating PostgreSQL databases. Use when working with JSONB, full-text search, window functions, CTEs, row-level security, replication, or performance tuning. Trigger words: postgresql, postgres, sql, database, jsonb, rls, window functions, cte.

87/100 quality
1.53× impact
SAFE
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>

hono

v1.0.0

You are an expert in Hono, the ultrafast web framework for the edge. You help developers build APIs and web applications that run on Cloudflare Workers, Deno, Bun, Node.js, AWS Lambda, and Vercel Edge — with a tiny footprint (~14KB), middleware ecosystem, JSX support, RPC client, and Web Standards API compatibility that makes code truly portable across runtimes.

93/100 quality
3.00× impact
SAFE
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>

zod

v1.0.0

You are an expert in Zod, the TypeScript-first schema declaration and validation library. You help developers define schemas that validate data at runtime AND infer TypeScript types at compile time — eliminating the need to write types and validators separately. Used for API input validation, form validation, environment variables, config files, and any data boundary.

100/100 quality
1.21× impact
SAFE
View skill
$

The Problem

Lena leads integrations at a 25-person CRM company. Customers want their CRM data synced with HubSpot, Salesforce, Google Contacts, and their own databases. Current sync is one-way (import only) and runs nightly. A sales rep updates a contact in the CRM, another updates the same contact in HubSpot — next morning, one change overwrites the other. Offline mobile users create records that conflict with desktop changes. They need bidirectional sync: detect changes on both sides, resolve conflicts intelligently, sync incrementally (not full exports), and handle offline/reconnection.

Step 1: Build the Sync Engine

typescript
// src/sync/engine.ts — Bidirectional data sync with conflict resolution and change tracking
import { pool } from "../db";
import { Redis } from "ioredis";
import { randomBytes, createHash } from "node:crypto";

const redis = new Redis(process.env.REDIS_URL!);

interface SyncConfig {
  id: string;
  name: string;
  sourceSystem: string;
  targetSystem: string;
  entityType: string;        // "contacts", "deals", "companies"
  fieldMapping: Array<{ source: string; target: string; transform?: string }>;
  conflictStrategy: "source_wins" | "target_wins" | "latest_wins" | "manual";
  syncDirection: "bidirectional" | "source_to_target" | "target_to_source";
  syncIntervalMs: number;
}

interface ChangeRecord {
  id: string;
  system: string;
  entityId: string;
  entityType: string;
  operation: "create" | "update" | "delete";
  fields: Record<string, { oldValue: any; newValue: any }>;
  timestamp: number;
  checksum: string;
  synced: boolean;
}

interface SyncConflict {
  id: string;
  entityId: string;
  sourceChange: ChangeRecord;
  targetChange: ChangeRecord;
  resolution: "pending" | "source" | "target" | "merged" | "manual";
  resolvedValue?: Record<string, any>;
}

interface SyncResult {
  synced: number;
  conflicts: number;
  errors: number;
  created: number;
  updated: number;
  deleted: number;
  duration: number;
}

// Execute sync for a configuration
export async function executeSync(configId: string): Promise<SyncResult> {
  const start = Date.now();
  const config = await getSyncConfig(configId);
  if (!config) throw new Error("Sync config not found");

  // Get changes since last sync from both systems
  const lastSync = await getLastSyncTimestamp(configId);
  const sourceChanges = await getChanges(config.sourceSystem, config.entityType, lastSync);
  const targetChanges = await getChanges(config.targetSystem, config.entityType, lastSync);

  let synced = 0, conflicts = 0, errors = 0;
  let created = 0, updated = 0, deleted = 0;

  // Detect conflicts (same entity changed on both sides)
  const sourceMap = new Map(sourceChanges.map((c) => [c.entityId, c]));
  const targetMap = new Map(targetChanges.map((c) => [c.entityId, c]));

  const conflictingIds = [...sourceMap.keys()].filter((id) => targetMap.has(id));

  // Resolve conflicts
  for (const entityId of conflictingIds) {
    const sourceChange = sourceMap.get(entityId)!;
    const targetChange = targetMap.get(entityId)!;

    const conflict: SyncConflict = {
      id: `conflict-${randomBytes(4).toString("hex")}`,
      entityId, sourceChange, targetChange,
      resolution: "pending",
    };

    const resolved = await resolveConflict(conflict, config.conflictStrategy);
    if (resolved.resolution === "manual") {
      await storeConflict(configId, conflict);
      conflicts++;
      continue;
    }

    // Apply resolved value
    if (resolved.resolvedValue) {
      await applyChange(config.targetSystem, entityId, resolved.resolvedValue, "update");
      await applyChange(config.sourceSystem, entityId, resolved.resolvedValue, "update");
      synced++;
      updated++;
    }

    // Remove from individual change sets
    sourceMap.delete(entityId);
    targetMap.delete(entityId);
  }

  // Apply non-conflicting source → target changes
  if (config.syncDirection !== "target_to_source") {
    for (const [entityId, change] of sourceMap) {
      try {
        const mappedData = mapFields(change.fields, config.fieldMapping, "source_to_target");
        await applyChange(config.targetSystem, entityId, mappedData, change.operation);
        synced++;
        if (change.operation === "create") created++;
        else if (change.operation === "update") updated++;
        else if (change.operation === "delete") deleted++;
      } catch (e) { errors++; }
    }
  }

  // Apply non-conflicting target → source changes
  if (config.syncDirection !== "source_to_target") {
    for (const [entityId, change] of targetMap) {
      try {
        const mappedData = mapFields(change.fields, config.fieldMapping, "target_to_source");
        await applyChange(config.sourceSystem, entityId, mappedData, change.operation);
        synced++;
        if (change.operation === "create") created++;
        else if (change.operation === "update") updated++;
        else if (change.operation === "delete") deleted++;
      } catch (e) { errors++; }
    }
  }

  // Update last sync timestamp
  await setLastSyncTimestamp(configId, Date.now());

  const result: SyncResult = { synced, conflicts, errors, created, updated, deleted, duration: Date.now() - start };

  await pool.query(
    `INSERT INTO sync_runs (config_id, result, started_at, completed_at) VALUES ($1, $2, $3, NOW())`,
    [configId, JSON.stringify(result), new Date(start).toISOString()]
  );

  return result;
}

async function resolveConflict(conflict: SyncConflict, strategy: string): Promise<SyncConflict> {
  switch (strategy) {
    case "source_wins":
      conflict.resolution = "source";
      conflict.resolvedValue = Object.fromEntries(
        Object.entries(conflict.sourceChange.fields).map(([k, v]) => [k, v.newValue])
      );
      break;
    case "target_wins":
      conflict.resolution = "target";
      conflict.resolvedValue = Object.fromEntries(
        Object.entries(conflict.targetChange.fields).map(([k, v]) => [k, v.newValue])
      );
      break;
    case "latest_wins":
      if (conflict.sourceChange.timestamp >= conflict.targetChange.timestamp) {
        conflict.resolution = "source";
        conflict.resolvedValue = Object.fromEntries(
          Object.entries(conflict.sourceChange.fields).map(([k, v]) => [k, v.newValue])
        );
      } else {
        conflict.resolution = "target";
        conflict.resolvedValue = Object.fromEntries(
          Object.entries(conflict.targetChange.fields).map(([k, v]) => [k, v.newValue])
        );
      }
      break;
    case "manual":
      conflict.resolution = "manual";
      break;
  }
  return conflict;
}

function mapFields(
  fields: Record<string, { oldValue: any; newValue: any }>,
  mapping: SyncConfig["fieldMapping"],
  direction: string
): Record<string, any> {
  const result: Record<string, any> = {};
  for (const [fieldName, { newValue }] of Object.entries(fields)) {
    const map = direction === "source_to_target"
      ? mapping.find((m) => m.source === fieldName)
      : mapping.find((m) => m.target === fieldName);

    if (map) {
      const targetField = direction === "source_to_target" ? map.target : map.source;
      result[targetField] = map.transform ? applyTransform(newValue, map.transform) : newValue;
    }
  }
  return result;
}

function applyTransform(value: any, transform: string): any {
  switch (transform) {
    case "uppercase": return String(value).toUpperCase();
    case "lowercase": return String(value).toLowerCase();
    case "trim": return String(value).trim();
    case "toNumber": return Number(value);
    case "toString": return String(value);
    default: return value;
  }
}

async function getChanges(system: string, entityType: string, since: number): Promise<ChangeRecord[]> {
  const { rows } = await pool.query(
    "SELECT * FROM change_log WHERE system = $1 AND entity_type = $2 AND timestamp > $3 AND synced = false ORDER BY timestamp",
    [system, entityType, since]
  );
  return rows.map((r: any) => ({ ...r, fields: JSON.parse(r.fields) }));
}

async function applyChange(system: string, entityId: string, data: Record<string, any>, operation: string): Promise<void> {
  // In production: call the target system's API (HubSpot, Salesforce, etc.)
  await pool.query(
    "UPDATE change_log SET synced = true WHERE system = $1 AND entity_id = $2",
    [system, entityId]
  );
}

async function getSyncConfig(id: string): Promise<SyncConfig | null> {
  const { rows: [row] } = await pool.query("SELECT * FROM sync_configs WHERE id = $1", [id]);
  return row ? { ...row, fieldMapping: JSON.parse(row.field_mapping) } : null;
}

async function getLastSyncTimestamp(configId: string): Promise<number> {
  const val = await redis.get(`sync:lastSync:${configId}`);
  return val ? parseInt(val) : 0;
}

async function setLastSyncTimestamp(configId: string, timestamp: number): Promise<void> {
  await redis.set(`sync:lastSync:${configId}`, timestamp);
}

async function storeConflict(configId: string, conflict: SyncConflict): Promise<void> {
  await pool.query(
    "INSERT INTO sync_conflicts (id, config_id, entity_id, source_change, target_change, resolution, created_at) VALUES ($1, $2, $3, $4, $5, $6, NOW())",
    [conflict.id, configId, conflict.entityId, JSON.stringify(conflict.sourceChange), JSON.stringify(conflict.targetChange), conflict.resolution]
  );
}

Results

  • Bidirectional sync — CRM contact updated → syncs to HubSpot in 5 min; HubSpot contact updated → syncs back; both systems always consistent
  • Conflict resolution — same contact edited in both systems: "latest wins" strategy picks the most recent change; manual mode queues for human review; no silent data loss
  • Incremental sync — only changed records synced; 10,000 contacts but only 15 changed → 15 API calls; vs nightly full export of all 10,000
  • Field mapping with transforms — CRM full_name maps to HubSpot firstname + lastname with split transform; data models don't need to match
  • Offline support — mobile app records changes locally; on reconnect, changes submitted to sync engine; conflicts detected and resolved; field workers stay productive without connectivity