X API v2 and External Database: Synchronization Strategy for Zero-Downtime Migration

Answer

To close the gap, fetch a small overlap window after the final next_token (e.g., re‑request the last N tweets using since_id set to the checkpoint) and start the Filtered Stream at the same point. Deduplicate any overlapping records by storing tweet data with a unique constraint on tweet_id (or using an upsert that ignores duplicates).

Likely explanation (assumptions)

• The X API v2 assigns monotonically increasing tweet_id values, so newer tweets always have higher IDs.
• The Filtered Stream delivers events in near‑real‑time order and may replay a few events after a reconnection.
• Your service can persist a checkpoint (the highest tweet_id seen) durably.

Confirmed facts (platform behavior)

• REST endpoints return a next_token that can be used to continue pagination exactly where the previous request left off.
• A unique index on tweet_id prevents duplicate inserts; an upsert (INSERT … ON CONFLICT DO NOTHING) will safely ignore any duplicate that arrives via either REST or stream.

Steps needed for this case

1. Persist a checkpoint: query the local DB for the maximum tweet_id (or latest created_at) and store it.
2. After the REST pagination ends (no next_token), re‑fetch the last N tweets (e.g., N = 100) using since_id set to the checkpoint value.
3. Start the Filtered Stream, filtering locally to accept only tweets with tweet_id greater than the checkpoint.
4. Ingest both the overlap fetch and the stream into the new storage using an upsert on tweet_id; the unique constraint removes duplicates.
5. Update the checkpoint after each successful upsert to the highest tweet_id seen.

Missing diagnostic detail

To size the overlap window optimally we need the exact tweet_id (or timestamp) of the last record returned by the REST endpoint. Knowing this value determines how many recent tweets must be re‑fetched to cover the gap.