DappRadar vs Bloom

Overview

DappRadar DappRadar is one of the world's largest dApp discovery and analytics platforms, tracking decentralized applications across 50+ blockchains including Solana. The platform provides real-time data on dAp... Bloom Bloom is an AI-powered Solana trading bot that uses machine learning to assist traders with token analysis, trade execution, and portfolio management. It represents the newer generation of trading too...

Community Ratings

Bloom is rated higher by the MadeOnSol community with 4.0/5 stars across 4 reviews, compared to 0.0/5 for DappRadar (0 reviews). That said, ratings only tell part of the story — what matters most is which tool fits your specific workflow.

Pricing & Value

DappRadar uses a freemium model, while Bloom is freemium. Both offer free tiers with paid upgrades, so try each before committing to a paid plan.

Key Features

DappRadar offers 5 features including dApp discovery across 50+ blockchains including Solana, Real-time usage, volume, and user metrics, Token Explorer with detailed analytics, and 2 more. Bloom counters with 8 features including AI-powered token analysis with risk assessment and sentiment detection, Telegram-based trading with quick swap execution, Machine learning-assisted trade recommendations, and 5 more. The right choice depends on which specific features matter for your use case — check the individual review pages for full breakdowns.

Reliability & Health

We monitor both tools around the clock for uptime, SSL validity, and response times. DappRadar currently has a healthy health status with 100.0% uptime over the last 30 days. Bloom is rated healthy with 100.0% uptime. For any tool you trust with your funds, trades, or yield, uptime and speed are non-negotiable.

Strengths

DappRadar's key strengths include industry-standard dapp rankings and metrics, comprehensive multi-chain coverage, free to use for basic features. Bloom stands out for ai analytics provide additional insight layer beyond basic trading features, comprehensive token analysis combines on-chain, social, and technical data, growing ai capabilities may improve over time as model training advances.