Upstart blockchain Fantom (FTM) overtook rival Avalanche (AVAX) in daily transaction count once more in the first week of 2022. Both are popular networks for decentralized finance (DeFi).
Fantom’s daily transaction count eclipsed Avalanche’s in the first few days of the year, reported Delphi Digital, with its lead growing over the past few days.
Avalanche led Fantom in transaction count for some of 2021’s fourth quarter, but on Thursday:
- Fantom processed 853,422 transactions.
- Avalanche saw 737,200 transactions
- Ethereum processed 1.21 million transactions, about 40% more than Fantom.
FTM’s market capitalization has doubled over the last 30 days alone. The $9-billion protocol now has $5.77 billion in total value locked (TVL), a popular albeit misleading measure of DeFi popularity.
Almost 45% of Fantom’s TVL was kept in token bridge Multichain at press time.
Fantom’s older competitor, Avalanche, has slid in value 16% over the past seven days to a $22-billion market capitalization.
Avalanche also hosts third-party DeFi apps like liquidity protocols Aave and Spell, and decentralized exchanges Pangolin and Trader Joe.
At current prices, users have locked $11 billion worth of AVAX into its DeFi protocols. Lending platform Aave is the most dominant on Avalanche, currently managing 25% of its TVL, according to DeFi Llama.
Celebrity DeFi devs drive Fantom interest
Fantom describes itself as a low-cost blockchain for launching decentralized applications (dapps) with Ethereum compatibility.
The 80-plus dapps launched on Fantom include NFT marketplaces Artion, ZooCoin, and PaintSwap; and decentralized exchanges Spooky Swap, Curve, and Morpheus Swap.
New projects launching on Fantom are driving its momentum. Sestagalli and his confidante, Yearn Finance’s Andre Cronje, announced on Thursday they intend to launch a new token on Fantom.
The duo created TIME, SPELL, ICE, and MIM — Avalanche tokens with a $6-billion combined market cap.
Another fledgling multi-chain DeFi protocol, Hundred Finance, is also gaining traction with its new, Fantom-based Voting Escrow Token (“ve-token”) to help stakers manage voting power.
In November 2021, Fantom reported significant growth from its FTM Incentive Program, including a 600% increase in TVL, and a 300% increase in daily transactions and active users since its announcement last August.
Fantom recently made some of its code open-source and offers APIs and oracles for dapp developers.
The blockchain’s official wallet includes synthetic assets that represent crypto assets outside of the Fantom ecosystem.
This feature relies on price oracles and Fantom’s native “fSwap” exchange. Users can also use “fLend” to loan and borrow FTM and Fantom’s native stablecoin, fUSD.
High yield, ultra-high risk
Risks of DeFi platforms like Avalanche and Fantom include unaudited code, exploitable bugs, insufficient risk disclosures, aggressive marketing tactics, and occasional exit scams.
Fantom dubiously claims that its “Lachesis” consensus algorithm is superior to Bitcoin’s Nakamoto consensus.
The project states that its algorithms are Byzantine fault tolerant, allegedly enabling it to withstand attacks by malicious or faulty nodes comprising up to one-third of its network.
For its part, Avalanche brags its testnet can support up to 4,500 transactions per second across thousands of pruned nodes.
However, Avalanche’s mainnet currently processes around 10 transactions per second, according to SnowTrace (Ethereum handles around 14 per second, Fantom under six).
The primary allure of DeFi protocols are their high yields. Positioned as an alternative to traditional bank accounts, these platforms advertise annualized yields on tokens with double-digit percentages.
Aggressive protocols advertise triple-digit and even higher yields while burying the risk of default within terms of service documents.
Forensic security company Chainalysis reports that orchestrators of rug pulls and DeFi exploits stole $3.2 billion in 2021.
Chainalysis cites the lack of code audits across DeFi as a significant factor in at least 68% of those losses, amounting to at least $2.2 billion.
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Edit 11:50 UTC, Jan 9: Corrected millions to billions in final paragraph.