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Comparison · Infra & APIs
BigQuery vs Knock
A side-by-side editorial comparison of BigQuery and Knock — release velocity, themes, recent moves, and the top alternatives to consider.
BigQuery vs Knock: at a glance
| Feature | BigQuery | Knock |
|---|---|---|
| Sector | Infra & APIs, Analytics | Infra & APIs |
| Velocity score | 7.5 | 6.3 |
| Sparks · 30d | 0 | 1 |
| Top themes | lakehouse, iceberg, data-sharing, governance | notifications, agentic-tooling, no-code-config, integrations |
| Last editorial update | 1mo ago | 3d ago |
| Website | Visit → | — |
What is BigQuery?
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.
What is Knock?
Knock is pushing its agent into more surfaces while making notification config a no-engineering job.
Knock, a notifications-infrastructure platform, is building two parallel tracks: an agent that can create and manage messaging resources from inside tools like Slack, and a steady stream of dashboard-driven features that move configuration work off engineers. Recent releases span a hosted preference center, dynamic audiences, new data sources, and template tooling. The product is widening from a developer API toward a self-serve control surface.
BigQuery vs Knock: editorial side-by-side
BigQuery
7.5INFRA · APISANALYTICS
BigQuery doubles down on Iceberg, graph, and global data sharing as the lakehouse fight intensifies.
◆ Current state
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.
◆ Where it's heading
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.
◆ Prediction
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.
Knock
6.3INFRA · APIS
Knock is pushing its agent into more surfaces while making notification config a no-engineering job.
◆ Current state
Knock, a notifications-infrastructure platform, is building two parallel tracks: an agent that can create and manage messaging resources from inside tools like Slack, and a steady stream of dashboard-driven features that move configuration work off engineers. Recent releases span a hosted preference center, dynamic audiences, new data sources, and template tooling. The product is widening from a developer API toward a self-serve control surface.
◆ Where it's heading
The direction is toward less engineering involvement per change — agents, dashboard-built audiences, and hosted end-user UI all shorten the code path. Integrations like the Shopify data source extend Knock's triggers into commerce events, broadening what notifications can be driven by. The agent and the dashboard keep absorbing tasks that previously required custom code.
◆ Prediction
The next moves likely deepen the agent (more surfaces or skills) and add further data sources, continuing the shift toward dashboard- and agent-driven configuration over hand-written integration code.
Alternatives to BigQuery and Knock
Other Infra & APIs products tracked by Sparkpulse, ranked by recent ship velocity. Each card links to a full editorial trajectory and lets you pivot into a head-to-head comparison with either BigQuery or Knock.
Tailscale
Tailscale turns the tailnet into an identity layer for AI agents via Aperture
Jenkins
Jenkins keeps its weekly cadence, hardening the experimental UI and agent reliability.
Buildkite
Buildkite turns its MCP server into an agent control plane for CI/CD
Vercel
Vercel widens its AI Gateway and compute limits as regulation reshapes model access
Auth0
Auth0 is rebuilding identity around AI agents, M2M, and B2B self-service
See all BigQuery alternatives → · See all Knock alternatives →
Recent activity from BigQuery and Knock
Latest ship moves from both products, interleaved chronologically. ⚡ = editorial spark.
- 5d agoKnockPreference center
- 13d agoKnockNew partial input types
- 15d agoKnockKnock agent for Slack ⚡
- 26d agoKnockShopify data source
- 1mo agoKnockReusable request input schemas
- 1mo agoBigQueryBigQuery May 2026 - Multi-region sharing listings GA and Data Transfer Service updates
- 1mo agoBigQueryMFA required for new Google Ads data transfers
- 1mo agoBigQueryBigQuery Data Transfer Service connectors Google Ads data retention policy change
- 1mo agoBigQueryBigQuery ML ARIMA_PLUS_XREG model support for feature columns
- 1mo agoBigQueryBigQuery sharing listings for multiple regions
- 1mo agoBigQueryBigQuery May 2026 - Graph features, Iceberg v3, and Conversational Analytics ⚡
- 1mo agoKnockDynamic audiences ⚡
Frequently asked questions
What is the difference between BigQuery and Knock?
They serve adjacent needs but don't currently overlap on shipped themes. BigQuery is currently shipping more aggressively (velocity 7.5 vs 6.3), with 0 editorial sparks in the last 30 days against 1. See the at-a-glance table above for a side-by-side breakdown of velocity, recent sparks, and editorial themes.
Is BigQuery better than Knock?
Sparkpulse doesn't pick a winner — we score release velocity, not feature parity. BigQuery is currently shipping more aggressively (velocity 7.5 vs 6.3), with 0 editorial sparks in the last 30 days against 1. For your specific use case, the alternatives sections above list other Infra & APIs products to evaluate alongside.
What are the best alternatives to BigQuery?
Top BigQuery alternatives in Infra & APIs are ranked by recent ship velocity. Browse the "BigQuery alternatives" section above for the current picks, or visit /alternatives/bigquery for the full list with editorial commentary on each.
What are the best alternatives to Knock?
Top Knock alternatives in Infra & APIs are ranked by recent ship velocity. Browse the "Knock alternatives" section above for the current picks, or visit /alternatives/knock for the full list with editorial commentary on each.