FIFO vs LIFO vs Priority Queue vs Deque: How Records Are Added and Removed in Automation

A practical field guide from Automation Ace.

The short answer

When records wait in a database, list, or queue, the order you remove them in decides how your automation behaves. FIFO (First In, First Out) processes the oldest item first, like a line at a store. LIFO (Last In, First Out) processes the newest item first, like a stack of plates. LILO is just another name for FIFO, and FILO another name for LIFO. A priority queue processes by importance instead of arrival time, and a deque (double-ended queue) lets you add or remove items at either end. Most business automations want FIFO, some need priority, and a few benefit from LIFO or a deque.

These ideas power real workflows: processing orders in sequence, handling urgent tickets first, retrying failures, and avoiding race conditions. See sequential queues with Zapier Tables for a hands-on build.

The six orderings at a glance

How records are added and removed

Every queue-like structure has two operations: add (also called enqueue or push) and remove (dequeue or pop). In automation, “remove” usually means claiming a record for processing and then marking it done, rather than deleting it, so you keep a history. The difference between FIFO, LIFO, priority, and deque is simply which record you claim next.

// The same list, four behaviors (JavaScript arrays)
const queue = [];
queue.push('A'); queue.push('B'); queue.push('C');   // add to the end

queue.shift();     // FIFO / LILO: removes 'A' (oldest)
queue.pop();       // LIFO / FILO: removes 'C' (newest)

// Deque: add or remove at either end
queue.unshift('X'); // add to the front
queue.push('Y');    // add to the back

// Priority queue: sort by priority, then by arrival time
const jobs = [
  { id: 1, priority: 2, created: '2026-10-12T09:00Z' },
  { id: 2, priority: 1, created: '2026-10-12T09:05Z' },  // 1 = most urgent
  { id: 3, priority: 1, created: '2026-10-12T09:01Z' },
];
jobs.sort((a, b) => a.priority - b.priority || a.created.localeCompare(b.created));
const next = jobs[0];  // id 3: most urgent, then oldest

FIFO (and LILO): first in, first out

FIFO processes items in the order they arrived. The first record added is the first one processed, and the last one added waits its turn, which is why it is also called LILO (Last In, Last Out). It is fair, predictable, and the default for most business processes.

• Order fulfillment: ship orders in the sequence they were placed.
• Sequential API updates: apply changes to the same record in order so a later update is not overwritten by an earlier one arriving late. See preventing concurrent updates.
• Rate-limited syncs: drain a backlog one item at a time within an API's limits. See 429 rate limit errors.
• Support queues: first-come, first-served tickets. See ticket triage.

How to implement: sort pending records by created time ascending and take the first. Many managed queues offer FIFO guarantees as an option, for example Amazon SQS FIFO queues, while standard queues often provide only best-effort ordering, so check what your tool promises.

LIFO (and FILO): last in, first out

LIFO processes the newest item first. The first record added is the last one processed, which is why it is also called FILO (First In, Last Out). In software it is a stack.

• Latest-wins updates: when a status changes five times in a minute, only the newest value matters; process the latest and discard older ones.
• Recent activity feeds: show or act on the most recent events first.
• Undo and rollback: reverse the most recent change first.
• Nested work: finish the most recently started subtask before returning to its parent.

Watch out: under steady load, LIFO can starve old items forever. Use it only when older items are genuinely less valuable, or add a cleanup job that expires stale items.

Priority queue: most important first

A priority queue ignores arrival order and processes the most important item first, usually breaking ties by age (so it is FIFO within each priority level).

• VIP or high-value customers ahead of the general queue.
• Urgent alerts (payment failed, site down) ahead of routine notices.
• SLA-driven work: priority based on time remaining before a deadline.
• AI-scored leads: work hot leads first. See AI lead qualification.

Watch out for starvation: if urgent items keep arriving, low-priority items may never run. Add aging: raise an item's priority the longer it waits.

Deque: add or remove at either end

A deque (pronounced “deck”) is a double-ended queue. You can add to or remove from the front or the back, so it can act as a FIFO queue, a LIFO stack, or a mix.

• Retry to the front: normal work joins the back; a failed item is pushed back to the front to retry before anything new.
• Last N items: add new items to the front and trim the back to keep only the most recent N, for example a “recent orders” widget.
• Work stealing: one worker takes from the front while another takes from the back to balance load.

Implementing queues in databases and tables

You rarely need a special queue product. A table with a status, a timestamp, and optionally a priority column can behave like any of these structures:

QUEUE TABLE (Zapier Tables, Airtable, Google Sheets, or a database)
id | payload_ref | priority | status      | created_at (UTC)     | attempts | locked_by | done_at
1  | ORD-1001    | 2        | done        | 2026-10-12 09:00:03  | 1        |           | 09:00:41
2  | ORD-1002    | 1        | processing  | 2026-10-12 09:01:10  | 1        | run-88    |
3  | ORD-1003    | 2        | pending     | 2026-10-12 09:02:55  | 0        |           |

FIFO:     filter status = pending, sort created_at ascending, take 1
LIFO:     filter status = pending, sort created_at descending, take 1
Priority: filter status = pending, sort priority ascending, then created_at ascending, take 1

In SQL databases, a single statement can claim the next record safely even when several workers run at once:

-- FIFO: claim the oldest pending job (PostgreSQL)
UPDATE jobs SET status = 'processing', claimed_at = now()
WHERE id = (
  SELECT id FROM jobs
  WHERE status = 'pending'
  ORDER BY created_at ASC          -- DESC for LIFO
  LIMIT 1
  FOR UPDATE SKIP LOCKED           -- two workers never claim the same row
)
RETURNING *;

-- Priority queue: most urgent first, oldest within the same priority
-- ORDER BY priority ASC, created_at ASC

In no-code tables, sort and filter on the same columns, and have only one Zap or scenario process the queue at a time if your tool cannot lock rows. The full pattern is in sequential queues with webhooks and Zapier Tables. To pick where the queue lives, see Storage vs Tables vs external databases.

Where these show up in automation tools

• Zapier: Delay After Queue spaces out runs one after another; Looping processes line items in order; Zapier Tables can hold a queue table. See built-in tools and looping.
• Storage by Zapier: list actions let you push values onto and pop values from a stored list, useful for small queues. See Storage vs Tables.
• Code steps and functions: arrays with push, shift, pop, and unshift, or sorting by priority. See JavaScript array methods.
• Redis and key-value stores: list operations at both ends (deque), and sorted sets for priority. See key-value vs tables.
• Message queues and durable engines: Cloudflare Queues, Amazon SQS, and workflow engines manage delivery, retries, and sometimes ordering for you. See durable workflows.
• Assignment rotation: round-robin is a FIFO queue of people. See round-robin assignment.

Which ordering should your automation use?

Reliability rules for any queue

1. Claim before you process: mark a record “processing” with a run ID so two runs do not grab it.
2. Make processing idempotent: retries and duplicates must be harmless. See idempotency and deduplication.
3. Handle stuck items: reset records stuck in “processing” longer than a timeout.
4. Cap retries: after N attempts, move the item to a failed state (a “dead-letter” list) and alert a person. See the error handling playbook.
5. Keep history: mark items done instead of deleting them, and archive old rows. See run logs.
6. Use UTC timestamps for ordering, and a tie-breaker such as an auto-increment ID when timestamps match.

Frequently asked questions

What is the difference between FIFO and LIFO?

FIFO (First In, First Out) processes the oldest item first, like a line. LIFO (Last In, First Out) processes the newest item first, like a stack of plates.

Is LILO the same as FIFO?

Yes. Last In, Last Out describes the same behavior as First In, First Out: items leave in the order they arrived.

Is FILO the same as LIFO?

Yes. First In, Last Out describes the same behavior as Last In, First Out: the newest item is removed first, so the first item added is removed last.

What is a priority queue?

A queue that processes items by priority instead of arrival order, usually breaking ties by age. It is used for urgent alerts, VIP customers, and SLA-driven work.

What is a deque?

A double-ended queue, where items can be added or removed at either the front or the back. It can behave like a FIFO queue, a LIFO stack, or both.

How do I build a FIFO queue in Zapier or Airtable?

Store items in a table with a status and created time, filter for pending items, sort by created time ascending, claim one item by marking it processing, process it, then mark it done. Process the queue with one run at a time unless your tool can lock records.

Which queue type should most business automations use?

FIFO, because it is fair and predictable. Use a priority queue when some items are more urgent, LIFO when only the latest state matters, and a deque when failed items should retry before new work.