Ship database changes without migration-day anxiety. Test schema changes, version upgrades, and query optimizations against real production workloads before deployment.
Transparent PostgreSQL and CockroachDB proxy with ~100μs overhead. Eliminate migration-day surprises and deploy with confidence.
Major database changes carry significant risk. Schema migrations, version upgrades, and query optimizations can break production in unexpected ways. Traditional staging environments lack production scale, traffic patterns, and edge cases that only emerge under real load.
Built in Rust with Tokio, ScryData eliminates migration-day anxiety by validating database changes against real production workloads. Catch breaking changes in hours, not after deployment.
ScryData sits transparently between your application and database, capturing production traffic and replaying it against your shadow database—with full instrumentation to see exactly how your changes perform.
Replay production queries against your shadow database with complete telemetry—see exactly how your changes perform under real load
Adapt incoming queries to match new schemas or query patterns—test breaking changes without breaking production
Compare latencies, catch errors, and spot result mismatches between production and shadow databases
ScryData captures every production query transparently
Optionally rewrite queries to match your new schema or data patterns
Execute queries against your shadow database with your proposed changes
Full instrumentation reveals performance impact, errors, and regressions
Built from the ground up in Rust for production workloads. ScryData eliminates the guesswork from database changes, giving you the confidence to ship faster.
Capture per-query metrics with value fingerprinting to identify hot data patterns. FlexBuffers serialization for high-throughput event publishing with minimal memory allocation.
Three-state circuit breaker using atomic operations prevents database overload. Automatic failover with exponential backoff and jitter ensures graceful degradation.
Active and passive health checks with EMA baseline anomaly detection. Catch performance degradation before it impacts production.
Blake3 cryptographic fingerprinting anonymizes query values while preserving pattern analysis. Maintain compliance without sacrificing observability.
Connection pooling with automatic state reset and health validation. Prevents connection exhaustion even when applications maintain their own pools.
Built-in metrics endpoint with percentile latencies, pool utilization, and circuit breaker state. Integrate seamlessly with existing monitoring infrastructure.
ScryData was born from real-world pain. After executing 70+ production PostgreSQL-to-CockroachDB migrations at enterprise scale, we knew there had to be a better way to validate database changes without the anxiety.
Hands-on experience migrating critical production databases at scale
Every failure mode we've seen is built into ScryData's design
Background in high-throughput systems serving critical workloads
We believe database migrations shouldn't be high-stakes gambling. ScryData brings production-scale validation to every team, eliminating the anxiety and risk of migration day. We built the tool we wished we had—now we're sharing it with you.
Join platform engineers, database architects, and SREs derisking major database changes with production-scale validation.