Seer vs Subsquid

Overview

Seer Seer is a transaction debugging tool for Solana that gives developers full source-code-level tracing of program execution. It is the Solana equivalent of what Tenderly offers for EVM, turning a standa... Subsquid Subsquid (SQD) is a decentralized data lake and indexing framework supporting Solana that allows developers to extract, transform, and query on-chain data at scale. Unlike centralized indexing solutio...

Community Ratings

Both Seer and Subsquid hold similar community ratings, suggesting users find comparable value in each. Your choice should come down to specific features, pricing, and ecosystem fit rather than overall score.

Pricing & Value

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

Key Features

Seer offers 5 features including Function and line-level tracing mapped to source code, Full call-stack trace of instructions, CPIs, logs, and errors in one flow, Variable snapshots and runtime account state changes per step, and 2 more. Subsquid counters with 5 features including Decentralized data lake with native Solana support, Custom data indexing with SQL-like queries, Real-time and historical data access, and 2 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. Seer currently has a healthy health status with 100.0% uptime over the last 30 days. Subsquid 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

Seer's key strengths include brings evm-grade (tenderly-style) debugging visibility to solana, no special setup; works with existing frameworks like anchor, source mapping and variable snapshots go far beyond raw log parsing. Subsquid stands out for decentralized architecture avoids single points of failure, highly flexible data transformation for any solana use case, cost-effective compared to running custom indexing infrastructure.