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 ThingsBoard and Basedash — release velocity, themes, recent moves, and the top alternatives to consider.
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.
Basedash's chat builds entire dashboards now — it's crossed from question-answering into workspace creation.
Basedash has shipped a concentrated wave of AI-first features: chat can now build full dashboards from plain language (charts, tabs, filters, variables with live preview), Models introduced a governed semantic layer with reusable SQL definitions, AI Sources shows the tables and SQL behind every answer, and Tasks launched an AI-driven operations autopilot in research preview. The product has fundamentally shifted its positioning from BI tool with AI to AI-native analytics workspace.
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.
Basedash has shipped a concentrated wave of AI-first features: chat can now build full dashboards from plain language (charts, tabs, filters, variables with live preview), Models introduced a governed semantic layer with reusable SQL definitions, AI Sources shows the tables and SQL behind every answer, and Tasks launched an AI-driven operations autopilot in research preview. The product has fundamentally shifted its positioning from BI tool with AI to AI-native analytics workspace.
The arc is toward autonomous analytics: AI that doesn't just answer questions but plans, builds, and governs the data infrastructure behind those answers. Models give AI answers an auditable foundation; Tasks translates those answers into operational to-do lists; chat now builds the dashboards that communicate them. Public sharing, i18n, and the Grok Bot plugin extend the audience beyond data teams to external stakeholders and non-English users.
Tasks will leave research preview and become a core product pillar, with more automation triggers (scheduled runs, threshold-based). Chat dashboard creation will deepen — full automation of recurring reports, not just one-shot builds. Expect additional LLM integrations beyond Grok Bot as the plugin pattern proves out.
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 ThingsBoard or Basedash.
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
dbt 2.0 enters final RC with beta Snowflake interactive_table materialization and full ClickHouse MV support.
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.
See all ThingsBoard alternatives → · See all Basedash alternatives →
Latest ship moves from both products, interleaved chronologically. ⚡ = editorial spark.
They serve adjacent needs but don't currently overlap on shipped themes. Basedash is currently shipping more aggressively (velocity 10.0 vs 5.0), with 2 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. Basedash is currently shipping more aggressively (velocity 10.0 vs 5.0), with 2 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 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.
Top Basedash alternatives in Analytics are ranked by recent ship velocity. Browse the "Basedash alternatives" section above for the current picks, or visit /alternatives/basedash for the full list with editorial commentary on each.