Track conversion
Follow a visit through signup and activation. Connect each step to the requests that helped a user through, or held them up.
session_idevents + requests
Model in events.
Query your world.
A serverless analytics database for logs, product events, and AI traces. Query, join, and explore data as it arrives, without defining every field up front.
Agents turn events into answers.
Your agents choose the next query, connect related events, and follow the evidence in ScopeDB to explain what happened.
Scale with demand
Compute scales up as demand rises and back down when it falls.
- Workload
- Elastic
Independent compute, shared data
Run ingestion and analytics in separate compute groups, with one shared dataset in S3.
ArchitectureConnect user journeys with logs and traces
Query product events alongside logs and traces to see where users drop off, which requests slow them down, and what happens inside an agent run.
Find slow requests
Spot requests over your latency threshold. Join them to logs and traces to find the dependency behind the wait.
trace_idlogs + traces
Trace agent runs
See which tools an agent called, where it retried, and how it reached an answer. Keep the evidence behind every response.
run_idcalls + outcomes
Explore ScopeDB
All articlesInsight In No Time: Three ScopeDB Design Principles (Part 1)
ScopeDB allows users to get insights in no time by eliminating the ETL process and enabling direct data analysis and exploration for multiple scenarios.
Schema On The Fly: Three ScopeDB Design Principles (Part 2)
ScopeDB implements a real variant type system that supports both structured and semi-structured data. It provides a full-featured, flexible schema solution that allows users to reshape raw events into a semi-structured format during ingestion, query and index nested fields within the object column efficiently, and evolve the schema of existing tables online without downtime or data migration.
Cloud Elasticity: Three ScopeDB Design Principles (Part 3)
ScopeDB leverages cloud-native architecture to separate storage and compute, treating S3 as the primary storage layer and offering serverless resource groups to minimize TCO while maximizing performance.