bitdrift vs Supernova: Features, Pricing & Which Is Better (2026)

A side-by-side comparison of bitdrift and Supernova — features, pricing, and ideal use cases — to help you decide which AI tool fits your workflow.

bitdrift

bitdrift Labs

Freemium

bitdrift is an agentic mobile observability platform that logs everything on-device in a ring buffer and uploads only the sessions you care about.

On-Device Ring Buffer: A patented local buffer captures unlimited telemetry on the device and only the signals you actually request are ever transmitted, decoupling log volume from cost.
Remote Workflow Deployment: Change or deploy a new telemetry workflow and data starts flowing immediately — no app redeploy, no app store review cycle.
bd-skills for Coding Agents: Built on the open agentskills.io standard, bd-skills let Claude Code, Cursor, Codex, and Copilot query live customer-device data while debugging.
Beyond Crash Reporting: Surfaces ANRs, out-of-memory errors, slow-loading screens, and other non-fatals alongside full crashes, with the relevant context attached.
3D Session Replay: Privacy-conscious moment-by-moment replays of the sessions that matter, paired with in-depth logs and synthetic metrics.
Fleet-Wide Filtering: Zoom from millions of devices down to the single one that matters by filtering on device type, OS version, and behavior.
Lightweight Multi-Platform SDK: Android, iOS, and React Native SDKs capture rich telemetry with minimal runtime overhead.
Instant Insights Metrics: Out-of-the-box mobile health, UX, resource, network, and device metrics available without custom instrumentation.

Catching Bugs Before Reviews: Mobile teams spot crashes and slow screens in real time rather than learning about them from 1-star app store reviews.
Cutting Observability Spend: Orgs where observability exceeds 30% of infrastructure cost move to paying for used data instead of generated data.
Debugging Without a Release: Engineers add the telemetry they wish they had mid-incident by deploying a workflow, without waiting for the next app version.
Agent-Assisted Bug Fixing: Coding agents pull real device sessions through bd-skills so fixes are grounded in actual user behavior.
Diagnosing Non-Fatal Degradation: Track ANRs, memory pressure, and battery drain that never produce a crash report but still drive churn.
Reproducing Elusive User Reports: Session replay plus the session timeline reconstructs exactly what a specific user saw around an issue.

Paid

An encrypted Iceberg data lake with a built-in engine and MCP endpoint, so Claude and Codex can query every tool your company uses.

MCP Endpoint for Claude and Codex: Point any MCP-speaking assistant at mcp.supernova.ai/mcp and every synced table becomes queryable in natural language.
Encrypted Iceberg Lake: Open Apache Iceberg tables in object storage with table-level encryption, so the data stays in a portable open format you control.
Zero-Copy Connections: Any engine that speaks Iceberg can read the lake directly, avoiding a second copy of your warehouse.
Time Travel: Every table retains version history, so you can query the state of your data as of any earlier point.
Built-In Frontier Models: Ask a question or describe a dashboard in plain language and Supernova generates the models and visualisations without a data team.
TypeSQL: Schema-aware SQL that autocompletes across joins and type-checks before execution, catching errors the way a typed language would.
Single-Binary CLI: One command-line tool connects sources, runs queries, tails live table changes and registers the MCP endpoint with Claude Desktop, from a laptop or CI.
Git-Backed Dashboards: Models and dashboards are readable and writable through Git, putting analytics artefacts under normal version control.

Conversational Revenue Analysis: Ask Claude which customers churned last quarter and why, with the answer computed over live Stripe and HubSpot tables.
Warehouse Cost Reduction: Replace a multi-vendor pipeline-plus-warehouse stack with one usage-billed platform, which the vendor illustrates as $5,640/mo dropping to $540/mo for a hardware company.
Dashboards Without a Data Team: Describe the dashboard you want in a sentence and have the models and charts generated for you.
AI-Native Data Access Layer: Give internal agents a governed, encrypted single endpoint for company data instead of per-tool API integrations.
Auditing Historical State: Use table version history to reconstruct what the numbers looked like before a pricing or schema change.
CI-Driven Data Workflows: Drive connections, queries and change tailing from pipelines using the single CLI binary.