Korean Chain Ecosystem Competition Monthly Report — December 2025
2026.02.09
Meta
- Coverage period: 2025-12-01 to 2025-12-31 (UTC)
- Target audience: DApps / project teams (growth, BD, product, research)
- Core metric (usage intensity): MAU (Artemis)
- DApp/sector metric: TVL (DeFiLlama)
- Included chains (Top 8 by MAU): Solana, BNB Chain, Near, Tron, Polygon PoS, Aptos, Sei Network, Bitcoin
- Congestion definition:
$$\text{Congestion}=\frac{\text{Sum of TVL in the Top 3 sectors}}{\text{Total chain TVL}}$$
Echobit Labs Interpretation (Meta):
This issue uses the “MAU (Artemis) + TVL (DeFiLlama) + Attention (Google Trends)” trio to represent user scale, capital stickiness, and narrative heat. MAU is not the same as real active addresses, and attention is not the same as adoption. Therefore, our conclusions are directional only, and we prioritize using TVL and leading protocols for adoption-side cross-validation.
Five conclusions this month
- Opportunity chain (by MAU) #1: Solana — #1 in MAU. Its TVL structure covers DEX + PERPS + lending + yield-type OTHERS, making it the best fit for a “incentives → trading → capital stickiness” growth loop.
- Opportunity chain (by MAU) #2: BNB Chain — #2 in MAU and #2 in TVL scale. Strong in both DEX and lending. In OTHERS, stablecoin-related capital-holding protocols (e.g., USYC) appear, making it suitable for trading entry and capital routing products.
- Opportunity chain (by MAU) #3: Near — #3 in MAU, but TVL is small and highly concentrated (OTHERS/LENDING/DEX). Better for vertical tools to quickly validate PMF (e.g., lending/yield tools). It resembles an ecosystem with “strong user reach, weak capital stickiness.” Do not chase TVL scale from day one.
- Sector mainline: Lending (LENDING) is the most certain demand form — Lending TVL on Tron/BNB/Solana is in the billions, and Sei/Near/Aptos also show “lending-dominant” structures.
- Attention mainline: Points/Airdrop + Leverage/DEX + Stablecoin — Korean keyword attention significantly skews toward “incentives/yield + trading tools + stablecoin channels.” Projects should design incentives to *lead users into trading and stickiness*, not just run campaigns.
Echobit Labs Interpretation:
Behind these five conclusions is an executable product path:
- Reach is more likely triggered by incentives (Points/Airdrop).
- Conversion is more likely to happen via trading tools (DEX/Leverage).
- Retention and stickiness ultimately land in lending / yield infrastructure (LENDING/OTHERS).
- Therefore, we prioritize ecosystems that can support the full “entry → conversion → stickiness” chain (Solana/BNB), while using Tron/Sei/Near as high-certainty testbeds for vertical-tool PMF.
1) What happened this month?
1.1 Echobit Labs observation: How attention aligns with adoption
- Attention side (Google Trends, KR): In December’s Top 10 keywords, Points clearly leads. Stablecoins (USDT/USDC/Stablecoin) and trading tools (Leverage/DEX) maintained steady exposure.
- Adoption side (TVL / leading protocols): Across the Top 8 chains, TVL is highly concentrated in OTHERS + LENDING. Solana/BNB are stronger in DEX and trading entry; Tron is stronger in lending and stablecoin-driven capital demand.
- Implications for project teams:
- Treat “Points/Airdrop” as distribution, “Leverage/DEX” as conversion, and “LENDING/yield-type OTHERS” as stickiness. Prioritize chains with clear structural proof (Solana/BNB/Tron).
1.2 Echobit Labs interpretation (this month’s mainline)
In December, Korean attention shows a “yield/incentives + trading tools + stablecoin channels” structure, and adoption-side TVL is indeed concentrated in lending and yield infrastructure. For project teams, instead of chasing grand narratives, it is better to build a growth mechanism that converts: acquire users with incentives, convert via trading, and retain through lending/yield products.
2) Chain competition dashboard (sorted by MAU)
2.1 Top 8 chains (selected and ranked by MAU)
Note: High MAU does not necessarily translate into DeFi TVL. High MAU may come from non-DeFi scenarios or different measurement methodologies.
Note: Bitcoin TVL is NA (not comparable) and is excluded from TVL/congestion comparisons.
2.2 Echobit Labs interpretation (chain competition)
We sort by MAU to serve project teams from a “growth/distribution” perspective: first identify where users are, then where capital sticks. December’s structure is typical: Solana/BNB have both users and sticky capital; Near looks like an ecosystem with “strong reach but weak stickiness,” suitable for lightweight product validation and distribution experiments rather than using TVL as the only objective from the start.
3) Sector penetration: What users are doing on-chain (TVL metric)
3.1 Sector structure (share)
Key points: In the Top 8 (excluding BTC), TVL is mainly concentrated in OTHERS (62.3%) + lending (24.7%). DEX (9.7%) and PERPS (3.8%) act as “conversion scenarios / amplifier sectors.”
Echobit Labs interpretation (sector structure):
The “staples” of TVL are OTHERS + lending, indicating that the core demand in December remains yield/collateral/infrastructure. DEX and PERPS are smaller in share, but they often determine trading momentum and conversion efficiency. They are better used as growth amplifiers than as the final TVL endgame.
3.2 Sector → chain mapping heatmap (share)
The heatmap uses share as the value; purple transparency indicates intensity (darker means higher share). Bitcoin is NA.
Echobit Labs interpretation (sector → chain mapping):
The heatmap quickly answers “how mature the same sector is across different chains.” For example, PERPS adoption is mainly concentrated on Solana. Lending is the “main narrative sector” on Tron/Sei. Polygon’s very high OTHERS suggests a more “bridge/staking/infrastructure-driven” partnership model.
3.3 Top 8 (excluding BTC) sector shares (aggregated by TVL)
This chart represents the “overall structure”: OTHERS + LENDING dominate, while DEX/PERPS are conversion scenarios.
Echobit Labs interpretation (overall structure):
When OTHERS exceeds half, project teams must break down what OTHERS contains (staking, bridges, yield, institutional assets, etc.) and choose the subset that creates positive feedback with your product. Otherwise, you risk misreading “big TVL that has nothing to do with you.”
3.4 Sector winners (Top 2 by TVL)
Echobit Labs interpretation (sector winners):
Winners are for execution decisions, not narrative decisions. PERPS winner is Solana, meaning derivative/leverage tools benefit from existing user mindshare and liquidity there. Lending winners are Tron/BNB, better for capital-efficiency and stablecoin-related products.
3.5 Echobit Labs interpretation (how to use sector penetration for chain selection)
Use “sector structure” as the first filter:
- If you build trading/derivatives: prioritize chains where DEX/PERPS already have scale and user base (Solana first, then BNB).
- If you build lending/yield tools: prioritize chains where lending share is high and capital demand is clear (Tron/Sei/BNB) to validate PMF with a shorter path.
- If you build partnership infrastructure/distribution: watch chains dominated by OTHERS but with concentrated applications (Polygon’s bridges/staking, Near’s staking-driven categories). Use partnerships for distribution rather than only competing on features.
4) DApp rankings (TVL) — Top 8 chains × Top 3
Note: This issue is a 2025.12 snapshot only; no MoM comparison.
Echobit Labs interpretation (how to use DApp Picks)
This table is not a “project ranking,” but an “ecosystem entry map.” It shows which protocols hold capital and mindshare on each chain. The most practical use is two steps:
- Pick a chain: check whether your target sector already has leading incumbents (avoid educating the market from zero).
- Then partner/integrate: prioritize integrating Top protocols for distribution and joint incentives to shorten cold start.
5) Activity and congestion
5.1 Congestion (Top 3 sector TVL / total chain TVL)
The bar chart is sorted by MAU to visualize how concentrated sectors are.
Note: Bitcoin TVL is NA and excluded.
5.2 Echobit Labs interpretation (what congestion means)
Congestion close to 1 means “capital is concentrated in a few sectors.” This is double-edged:
- Upside: clear demand and shorter user paths (e.g., lending/yield tools).
- Risk: more direct competition and strong incumbency; new projects must enter via distribution/incentives/differentiated mechanisms rather than feature parity.
- This month Solana is more diversified (congestion $$0.915$$), implying more niche opportunities. Tron/Sei/Near are extremely concentrated, making them better for vertical PMF.
6) Attention signals: Korean keywords (Google Trends, KR)
6.1 Top 10 (Dec-25)
One-line summary: In December, “Points / Airdrop” (campaign incentives) clearly leads keyword attention. Meanwhile, USDT, Leverage, DEX, NFT, and other trading/asset terms maintain stable exposure, indicating Korea’s focus skews toward “trading + yield/incentives.”
6.2 Top 10 Korean keywords (Dec, normalized index)
The chart uses Top 10 values (trends_index_dec) and renders intensity as purple bars.
Top 10 Korean keywords (Dec, normalized)
6.3 Narrative mapping (Top 10 composition)
- RWA: 3/10 (USDT, USDC, Stablecoin)
- PERPS: 2/10 (Leverage, DEX)
- RESTAKING: 2/10 (Points, Airdrop)
- GAMEFI: 1/10 (NFT)
- BASE: 2/10 (BTC, ETH)
Echobit Labs interpretation:
- RWA’s share is high, but it looks more like “stablecoin channel attention” than “asset tokenization/securitization.”
- PERPS looks more like broad trading interest than a clear “on-chain perps breakout”; adoption-side PERPS TVL is mainly on Solana.
- RESTAKING’s strong signal comes from Points: a typical incentive-driven attention structure, useful for growth design.
- Note: PERPS-specific keyword coverage is incomplete in this period, so this is closer to “broad trading interest” and must be cross-validated with perps TVL.
6.4 Echobit Labs interpretation (how attention guides action)
December’s keyword mix is more a growth methodology than a single sector bet:
- Points/Airdrop: users respond to incentives and migrations, but attention does not guarantee retention.
- Leverage/DEX: trading motivation still exists; design trade-driven conversion paths.
- Stablecoin (USDT/USDC/스테이블코인): “capital channels and unit of account” remain core.
- Therefore: use incentives for reach, trading for conversion, lending/yield for stickiness, and validate landing choices using TVL and leading protocols.
7) Echobit Labs interpretation: 90-day action checklist
7.1 Summary (overall 90-day strategy)
Data shows Korea’s attention favors incentives and trading tools, while adoption concentrates in lending and yield infrastructure. A robust 90-day approach is not betting on one narrative, but building a measurable loop:
$$\text{Reach (Points/Airdrop)} \rightarrow \text{Convert (DEX/Leverage)} \rightarrow \text{Stickiness (LENDING/OTHERS)}$$
Chain choice: Solana/BNB for full-funnel growth; Tron/Sei/Near for high-certainty vertical PMF.
7.2 Meme / consumer high-frequency projects
- Priority chains (by MAU): Solana → BNB Chain
- First 3 things to do: Design Points/Airdrop as “verifiable tasks → convertible behaviors” (trade/invite/stake/hold) to avoid pure farming. Bind to DEX/trading paths: route incentives into real trading (aligned with Leverage/DEX keywords). Co-distribute with leading protocols: Solana via Kamino/Jito; BNB via PancakeSwap/Venus.
- Avoid: campaigns without stickiness (missing lending/yield/trading relationship loops).
- Success metrics: MAU increase + number of traders (or transaction count)
7.3 DeFi tools / lending / aggregators
- Priority chains: Tron (lending/stablecoin axis) + BNB (scale and entry) + Solana (full stack)
- Priority integrations: Solana: Kamino Lend / Jito BNB: Venus / PancakeSwap Tron: JustLend / SUNSwap
- Success metrics: TVL increase + MAU increase (also track capital retention)
7.4 Games / social
- Priority chain: Solana (user base)
- Distribution (keywords): NFT has baseline exposure but is not strong. Treat NFT as an asset/identity layer, not the sole growth engine.
- Risk: capital-focused sectors compete for attention; you need stronger content and channel partnerships.
Appendix: Definitions and data sources
- Usage: MAU (Artemis, as a proxy for active addresses).
- Sectors and DApps: TVL (DeFiLlama; sector aggregation + protocol TVL).
- Attention: Google Trends (KR) Korean keywords + narrative mapping.
Important notes:
- MAU is a proxy: it reflects user scale and activity trend, not real active addresses; cross-chain comparability may be affected by measurement differences.
- DeFiLlama methodology differences: chain-level TVL (chainlevel) vs protocol-summed TVL (protocolsum) may differ (cross-chain attribution, double counting, category differences). For sector structure and congestion, this report uses the same basis (sector share and sum of top-3 sector shares) for reproducibility.