Bitcoin Transactions Get Stranded as Cryptocurrency Maxes Out
Bitcoin hit a capacity limit that could hamper dreams of it becoming widely used.
For more than a year now, people who use or work on the digital currency Bitcoin have been arguing about how to fend off a looming problem that some leaders in the community say could kill the whole system. This week that problem has become very real. Some people and businesses using Bitcoin have found their funds stranded after trying to send them to other users.
The problem is caused by Bitcoin’s design, which is capable of processing at best only seven transactions per second. This week the currency, which is powered by a decentralized network of computers run by people and businesses around the world, hit its capacity limit. A backlog of stranded transactions has built up. (There is debate as to whether this happened naturally, or by a person or group intentionally trying to cause problems for Bitcoin.)
At the time of writing there were about 20,000 Bitcoin transactions waiting to be processed. Some will go through much sooner than others.
You can attach a fee to a Bitcoin transaction for priority processing, and some Bitcoin software automatically suggests or sets one that will get you prompt processing. People using software that doesn’t adjust like that have found themselves cut off. Individual Bitcoin users and businesses have complained of transactions expected to go through in minutes getting stuck for many hours, or even days.
You don’t have to pay much to jump to the front of the queue. An online calculator from Bitcoin company 21 Inc. suggests that the average transaction need pay only seven cents to get through quickly.
But Bitcoin’s overall capacity limit remains a major problem. One stopgap measure to increase it could be implemented in a few months, but will only increase capacity a little bit. A recent study of Bitcoin’s design concluded that Bitcoin needs a radical rethink, because no proposal put forward so far is a sure bet to make Bitcoin work at very large scale.