𝗕𝘂𝗶𝗹𝗱𝗶𝗻𝗴 𝗿𝗲𝗮𝗹-𝘁𝗶𝗺𝗲 𝗰𝗼𝗹𝗹𝗮𝗯𝗼𝗿𝗮𝘁𝗶𝗼𝗻 𝘀𝗼𝘂𝗻𝗱𝘀 𝘀𝗶𝗺𝗽𝗹𝗲, 𝘂𝗻𝘁𝗶𝗹 𝘆𝗼𝘂 𝘁𝗿𝘆 𝘁𝗼 𝗺𝗮𝗸𝗲 𝗺𝘂𝗹𝘁𝗶𝗽𝗹𝗲 𝘂𝘀𝗲𝗿𝘀 𝗲𝗱𝗶𝘁 𝘁𝗵𝗲 𝘀𝗮𝗺𝗲 𝗱𝗼𝗰𝘂𝗺𝗲𝗻𝘁 𝗮𝘁 𝗼𝗻𝗰𝗲, 𝘄𝗶𝘁𝗵 𝘇𝗲𝗿𝗼 𝗰𝗼𝗻𝗳𝗹𝗶𝗰𝘁𝘀 𝗮𝗻𝗱 𝗻𝗼 𝗱𝗮𝘁𝗮 𝗹𝗼𝘀𝘀.
That’s when you realize how hard it is to keep distributed systems consistent.
Recently, I built a 𝙧𝙚𝙖𝙡-𝙩𝙞𝙢𝙚 𝙘𝙤𝙡𝙡𝙖𝙗𝙤𝙧𝙖𝙩𝙞𝙤𝙣 𝙗𝙖𝙘𝙠𝙚𝙣𝙙 𝙪𝙨𝙞𝙣𝙜 𝘾𝙍𝘿𝙏𝙨 (𝙔𝙟𝙨) —the same principle used by tools like Figma or Notion to synchronize changes across clients, even offline.
Along the way, I discovered a few challenges that completely changed how I think about distributed state and synchronization.
Here are five common traps to avoid when implementing real-time collaboration with CRDTs:
→ 𝙈𝙚𝙧𝙜𝙞𝙣𝙜 𝙞𝙨 𝙚𝙖𝙨𝙮… 𝙪𝙣𝙩𝙞𝙡 𝙞𝙩 𝙞𝙨𝙣’𝙩
CRDTs promise conflict-free merges, but not all data fits this model.
Use them only for collaborative entities (text, shapes, cursors), not for transactional data where order or atomicity really matters.
→ 𝙎𝙩𝙖𝙩𝙚 𝙥𝙚𝙧𝙨𝙞𝙨𝙩𝙚𝙣𝙘𝙚 𝙞𝙨 𝙖 𝙝𝙞𝙙𝙙𝙚𝙣 𝙘𝙤𝙢𝙥𝙡𝙚𝙭𝙞𝙩𝙮
Yjs stores updates in memory using binary diffs.
If you don’t persist both snapshots and incremental updates, your documents will take forever to reload as updates accumulate.
→ 𝙏𝙝𝙚 𝙒𝙚𝙗𝙎𝙤𝙘𝙠𝙚𝙩 𝙡𝙖𝙮𝙚𝙧 𝙙𝙚𝙛𝙞𝙣𝙚𝙨 𝙩𝙝𝙚 𝙚𝙭𝙥𝙚𝙧𝙞𝙚𝙣𝙘𝙚
Real-time means constant connectivity.
If your WebSocket doesn’t handle disconnects and re-syncs gracefully, users will end up editing different versions without even noticing.
→ 𝘽𝙧𝙤𝙖𝙙𝙘𝙖𝙨𝙩𝙞𝙣𝙜 𝙘𝙖𝙣 𝙠𝙞𝙡𝙡 𝙨𝙘𝙖𝙡𝙖𝙗𝙞𝙡𝙞𝙩𝙮
Sending every update to every connected user is easy to implement, but it doesn’t scale.
Segment your traffic by room or context, and avoid broadcasting awareness data unnecessarily.
→ 𝙇𝙖𝙩𝙚𝙣𝙘𝙮 𝙞𝙨 𝙥𝙖𝙧𝙩 𝙤𝙛 𝙩𝙝𝙚 𝙪𝙨𝙚𝙧 𝙚𝙭𝙥𝙚𝙧𝙞𝙚𝙣𝙘𝙚
Even a perfectly correct system feels broken if it’s slow.
Track synchronization latency (p95/p99) and compress updates —because real-time isn’t just about milliseconds, it’s about perception.
