Fulcrum
Fulcrum ships MCP server and AI Toolkit to let AI assistants build and query field data forms
A side-by-side editorial comparison of dbt Core and ThingsBoard — release velocity, themes, recent moves, and the top alternatives to consider.
dbt 2.0 enters final RC with beta Snowflake interactive_table materialization and full ClickHouse MV support.
dbt Core is in the final stretch of the v2.0 release cycle, running RC builds while the 1.x stable branch continues receiving targeted fixes. RC.2 added beta support for Snowflake's interactive_table materialization — covering static and dynamic variants with config-change detection for target_lag, warehouse, and cluster_by — and completed ClickHouse materialized view support via the new ADBC driver. The 1.12.5 and 1.11.15 patch releases address a MetricFlow protocol compliance issue and a package path traversal security fix respectively.
ThingsBoard patches aggressively across two release lines while quietly adding IoT Hub and AI model support.
ThingsBoard is in sustained patch mode across 4.2.x (LTS) and 4.3.x (current), resolving dozens of CVEs per release cycle. Beneath the security churn, the 4.3.x line has accumulated real additions since spring: IoT Hub integration, AI model structured output support for multiple providers, LZ4 Kafka compression, automatic SSL cert reload without restarts, and an HTML container widget. The dual-track model shows an enterprise customer base that demands long-term stability alongside continuous development.
dbt Core is in the final stretch of the v2.0 release cycle, running RC builds while the 1.x stable branch continues receiving targeted fixes. RC.2 added beta support for Snowflake's interactive_table materialization — covering static and dynamic variants with config-change detection for target_lag, warehouse, and cluster_by — and completed ClickHouse materialized view support via the new ADBC driver. The 1.12.5 and 1.11.15 patch releases address a MetricFlow protocol compliance issue and a package path traversal security fix respectively.
dbt 2.0's final stabilization phase is expanding adapter coverage depth rather than adding new DAG primitives. ClickHouse now has full MV and unit-test support; Snowflake gets interactive table handling with edge-case-level cluster_by comparison fixes that only come from deep validation work. The pattern: make dbt reliably correct on what modern warehouses already ship, rather than shipping new features.
The v2.0 stable tag is imminent — RC.2's fixes are narrow and precision-targeted, not broad. Post-2.0 expect a Fusion manifest integration stabilization push, given that 1.12.4 shipped two fixes specifically for Fusion-generated manifests.
ThingsBoard is in sustained patch mode across 4.2.x (LTS) and 4.3.x (current), resolving dozens of CVEs per release cycle. Beneath the security churn, the 4.3.x line has accumulated real additions since spring: IoT Hub integration, AI model structured output support for multiple providers, LZ4 Kafka compression, automatic SSL cert reload without restarts, and an HTML container widget. The dual-track model shows an enterprise customer base that demands long-term stability alongside continuous development.
The parallel LTS and current release trains signal a maturing platform with paying enterprise customers who cannot absorb breaking changes. The AI model integration thread — structured outputs, Vertex AI location routing — suggests ThingsBoard is building a rule-engine layer that can route telemetry decisions through LLMs, not just static rules. This points toward an edge-to-AI data fabric positioning rather than dashboarding alone.
The next substantive release will likely deepen the AI rule-engine integration with more providers or an agent-style action node. The IoT Hub connector introduced in 4.3.1.3 will likely be backported to 4.2.x once stabilized. Security patch cadence will continue regardless.
Other Analytics 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 dbt Core or ThingsBoard.
Fulcrum ships MCP server and AI Toolkit to let AI assistants build and query field data forms
Holistics builds AI governance and docs-as-analytics in parallel, shipping both weekly
OpenHouse breaks ground on Iceberg views while tightening storage lifecycle and authorization
Lightdash is cutting its dbt dependency and building AI-powered authoring into every layer of its BI stack.
Keboola's Kai AI assistant hits GA, completing the pivot from data platform to AI-native pipeline orchestration layer.
Omni's Apps reach general availability, completing its embedded analytics platform pitch.
See all dbt Core alternatives → · See all ThingsBoard alternatives →
Latest ship moves from both products, interleaved chronologically. ⚡ = editorial spark.
They serve adjacent needs but don't currently overlap on shipped themes. dbt Core is currently shipping more aggressively (velocity 6.3 vs 5.0), with 0 editorial sparks in the last 30 days against 0. See the at-a-glance table above for a side-by-side breakdown of velocity, recent sparks, and editorial themes.
Sparkpulse doesn't pick a winner — we score release velocity, not feature parity. dbt Core is currently shipping more aggressively (velocity 6.3 vs 5.0), with 0 editorial sparks in the last 30 days against 0. For your specific use case, the alternatives sections above list other Analytics products to evaluate alongside.
Top dbt Core alternatives in Analytics are ranked by recent ship velocity. Browse the "dbt Core alternatives" section above for the current picks, or visit /alternatives/dbt-core for the full list with editorial commentary on each.
Top ThingsBoard alternatives in Analytics are ranked by recent ship velocity. Browse the "ThingsBoard alternatives" section above for the current picks, or visit /alternatives/thingsboard for the full list with editorial commentary on each.