Reconcile by key, not by position. Treat the job as two steps: first decide which ePOS record corresponds to which ERP record, then apply field-level changes to matched pairs. A JSON diff or patch only does the second step. It cannot know that an ePOS line item and an ERP line item describe the same sale when they sit at different array positions or carry different identifiers. This guide uses plain browser JavaScript, with no libraries and no vendor-specific assumptions. All payloads below are illustrative, because no ePOS or ERP vendor, schema or policy is specified.
Why positional diffing fails on business arrays
RFC 6902 (JSON Patch) defines a patch as an ordered list of operations applied sequentially, each addressing a location with a JSON Pointer path. Under its equality rules, arrays are equal only if they hold equal values at corresponding positions, while object member order does not matter (RFC 6902). So if the ERP returns the same three order lines in a different order, a purely structural diff reports changes at every index, even though nothing changed in business terms.
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The standard says nothing about ePOS or ERP keys. Aligning records by stable domain identifiers is therefore your responsibility. It is a sound consequence of positional array semantics, not a rule the standard prescribes.
Do not confuse this with the W3C Entity Reconciliation Service API draft. That specification defines a service protocol for matching entities against a data source (W3C draft). It does not merge nested JSON arrays.
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Decide the rules before writing code
Settle these with whoever owns the integration. The code is trivial once the policy exists.
| Decision | Options | Why it matters |
|---|---|---|
| Identity | Positional index, or stable business key (for example order ID plus line ID, if both systems guarantee them) | Index matching breaks on any reorder, insert or deletion. |
| Ordering | Preserve source order, ignore it, or apply a domain sort | Determines whether a reorder is a change at all. |
| Conflict policy | Source precedence, per-field ownership, reject and review, manual choice | Decides who wins when values differ. |
| Auditability | Keep originals, log generated operations, surface unresolved keys | Lets you explain every change later. |
| Execution location | Browser memory, browser IndexedDB, or a server-side service | Browser APIs alone give no access to vendor systems. |
A hypothetical example of per-field ownership: the ePOS owns till-transaction facts such as tendered amount and time of sale, while the ERP owns accounting classifications such as ledger code. That is an example policy, not a fact about any product. Apply it only if the integration owner confirms it.
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Step-by-step implementation
1. Parse and validate shape
Parse both payloads with JSON.parse and check the shape you depend on. Use your systems’ real API documentation to confirm field names, types, nullability, currency units (major units versus minor units), timestamp formats and status codes. Nothing here can be inferred without that documentation.
2. Normalize only what is known to be equivalent
Convert fields whose equivalence is certain, such as ISO timestamps to a common form or amounts to a single unit. Keep the raw source value beside the normalized one for audit. Do not silently coerce ambiguous values; flag them instead.
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function normalizeLine(src, raw) {
return {
key: `${raw.orderId}:${raw.lineId}`, // assumes both systems guarantee these
sku: raw.sku,
qty: Number(raw.qty),
amountMinor: raw.amountMinor, // confirm units per system
_src: src,
_raw: raw
};
}3. Index by business key and catch bad keys
Build a Map per source. Missing and duplicate keys must go to an exceptions list, not be overwritten.
function indexByKey(lines) {
const map = new Map(), missing = [], duplicates = [];
for (const l of lines) {
if (!l.key || l.key.includes('undefined')) { missing.push(l); continue; }
if (map.has(l.key)) { duplicates.push(l); continue; }
map.set(l.key, l);
}
return { map, missing, duplicates };
}4. Align and compare field by field
Walk the union of keys. Records present on one side only are additions or omissions for review. Matched pairs get field comparison under the declared precedence.
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const OWNER = { qty: 'epos', amountMinor: 'epos', ledgerCode: 'erp' }; // hypothetical policy
function reconcile(epos, erp) {
const result = { matched: [], onlyEpos: [], onlyErp: [], conflicts: [] };
for (const [k, e] of epos.map) {
const r = erp.map.get(k);
if (!r) { result.onlyEpos.push(e); continue; }
const merged = structuredClone(r._raw);
for (const [field, owner] of Object.entries(OWNER)) {
const ev = e._raw[field], rv = r._raw[field];
if (ev !== rv) {
if (owner === 'epos') merged[field] = ev;
result.conflicts.push({ key: k, field, epos: ev, erp: rv, owner });
}
}
result.matched.push({ key: k, merged });
}
for (const [k, r] of erp.map) if (!epos.map.has(k)) result.onlyErp.push(r);
return result;
}For nested arrays, such as modifiers or tax lines inside a line item, repeat the same pattern recursively with a key appropriate to that level. If a nested array has no stable key, decide explicitly whether to compare it as an unordered set (for example after sorting on a canonical string) or as an opaque value that is replaced whole.
5. Generate patches only after alignment
Once records are paired, produce either a domain-specific change list or an RFC 6902 patch against the target document. The patch format supports add, remove, replace, move, copy and test operations, applied in order (RFC 6902). Because paths are index-based, compute them from the current position of each matched record. Operations that remove array elements shift later indexes, so emit removals from highest index to lowest, or recompute paths between steps. Adding test operations before replace guards against stale data.
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const patch = [
{ op: 'test', path: '/lines/2/qty', value: 3 },
{ op: 'replace', path: '/lines/2/qty', value: 4 }
];Browsers have no built-in JSON Patch applier, so either write a small one for the operations you actually use or apply the changes directly to your working copy. Dry-run on a copy and review destructive operations (remove, replace of whole subtrees) before anything is written back.
6. Use browser APIs for the working copy and local state
structuredClone() makes an independent deep copy of supported values, which is handy for a scratch copy you can patch safely. It is not a merger or validator, and unsupported values such as functions throw DataCloneError (MDN structuredClone). Parsed JSON is always cloneable.
IndexedDB can persist structured data asynchronously, with transactions and same-origin access (MDN IndexedDB). Use it for things like saving the original payloads and a reconciliation log between sessions. Quotas and eviction vary by browser, so it is not durable integration storage; the system of record must live server-side.
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- Missing key: quarantine the record and show it to the reviewer; never guess a match.
- Duplicate key: keep all copies in the exceptions list. Merging them silently can double-count or drop sales.
- Present on one side only: report as unmatched, and do not delete it from the target automatically.
- Unit or timestamp ambiguity: leave raw values intact and flag the field.
- Conflict where neither side is the declared owner: route to manual selection.
Limits of a browser-only approach
This pattern covers the comparison logic only. It does not establish how to authenticate to any vendor, what the schemas look like, which system is the source of truth, or what retention and legal rules apply to transaction data. Browser code also cannot reach vendor APIs unless they permit cross-origin requests or you supply exported files, so confirm that access path with your actual systems first.
Quick Recap
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