Appcues vs BigQuery
Side-by-side trajectory, velocity, and editorial themes.
Appcues drops Embeds — in-product experiences that live inside the UI rather than overlay it.
Appcues is a product-adoption platform whose recent quarter has run two parallel storylines. Captain AI, the in-product assistant, has gone from a chat helper to something that drafts segments, analyzes funnels, diagnoses display problems, and explains performance — adding capability essentially every monthly release. Alongside that, the team has expanded the experience surface itself: an MCP Server that exposes Appcues data to ChatGPT and Claude, and Embeds — a new experience type that lives inside the product UI rather than as an overlay.
Appcues is reframing what an 'in-product experience' tool covers. Embeds break the long-standing overlay-only model that defines the category (Pendo, Userpilot, Chameleon all anchor on overlays). MCP exposes the same data surface to external AI tools, which makes Appcues a source as well as a destination. Captain AI keeps absorbing operator tasks — segmentation, funnel analysis, install diagnostics — turning the product manager's in-tool workflow into more of a conversation than a configuration session.
Expect Captain AI to start fully building things autonomously rather than drafting (the team teased this in the January notes), and for Embeds to gain a bigger pattern library now that the underlying primitive is shipped. The MCP server integration line will likely grow with more bidirectional actions exposed to external AI tools.
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.
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