PostHog vs BigQuery
Side-by-side trajectory, velocity, and editorial themes.
PostHog is wiring itself into the MCP ecosystem while shoring up mobile-SDK feature parity.
PostHog continues its weekly grind, but the May releases cluster around two themes: an MCP toolchain (alerts to Slack and webhooks, SDK Doctor, mode selection via header) and LLM analytics BYOK providers (Together AI, Azure OpenAI). At the same time the mobile teams are filling in iOS and Android session-replay controls, rage-click detection, and survey delays that previously only the web SDK had.
The shape of PostHog's surface keeps widening rather than deepening: more LLM-vendor coverage in the analytics product, more MCP-tooling so AI agents can read and act on PostHog data, more parity across SDKs. Less obvious is which surface becomes the headliner; right now Conversations, Logs, Experiments, and Client Libraries are all shipping into a single weekly digest with comparable weight.
Expect MCP integration to keep expanding from peripheral utilities into the core insights and alerting paths, with PostHog positioning itself as the analytics endpoint AI agents read from when reasoning about product usage. Mobile SDK parity work should compress in the next month or two as the gap with the web SDK closes.
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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