BigQuery vs Rootly
Side-by-side trajectory, velocity, and editorial themes.
BigQuery doubles down on Iceberg, graph, and global data sharing as the lakehouse fight intensifies.
BigQuery's May 2026 ship list is dominated by three tracks: open-format lakehouse integration (Iceberg v3 with deletion vectors, REST catalog support in Conversational Analytics), graph capabilities maturing inside BigQuery Studio, and global data exchange via multi-region sharing listings reaching GA. Alongside the feature work, Google is tightening Data Transfer Service security (MFA on Google Ads transfers) and warning about Ads retention changes that will cap historical backfills from June 1. The release notes show a mature warehouse continuing to absorb adjacent workloads rather than reinventing itself.
BigQuery is positioning itself as the federated query and sharing fabric for a multi-format world, with Iceberg getting closer to first-class status and Conversational Analytics extending across external catalogs. The graph and notebook work signals a push to keep more analytical work inside Studio instead of bouncing to specialized tools. Expect continued layering of governance, AI-assisted query, and open-table support on top of the existing engine rather than core engine reinvention.
Next obvious step is GA for Iceberg v3 features and full conversational graph querying without Preview gating. Watch for additional first-party data sources getting MFA mandates, mirroring the Google Ads tightening.
Rootly is moving the incident workflow out of the dashboard and into the IDE.
Rootly is shipping steadily across three lanes: on-call ergonomics (SLA follow-ups, deferred paging, team heartbeats), AI surfaces (Claude Code and Cursor plugins), and enterprise plumbing (Google Workspace directory sync, deeper RBAC). The cadence is roughly one release per week and the changes are coherent rather than scattershot — each lane is building toward a recognizable end-state.
The on-call work is a maturation arc: features that used to be coarse (paging, heartbeats, follow-ups) are gaining ownership, scheduling, and SLA awareness. The AI work is the more interesting axis — pulling on-call context, retros, and incident state into Claude Code and Cursor signals that Rootly wants engineers to interact with the platform inside their editor, not by tabbing away to a separate UI.
Expect the IDE plugins to gain write-side actions next (acking pages, drafting retros, triggering runbooks from the editor), and on-call configuration to keep moving toward team-scoped, RBAC-aware defaults rather than global ones.
See more alternatives to BigQuery →
See more alternatives to Rootly →