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 Keboola and Parseable — release velocity, themes, recent moves, and the top alternatives to consider.
Keboola's Kai AI assistant hits GA, completing the pivot from data platform to AI-native pipeline orchestration layer.
Keboola's Kai AI assistant is now generally available for multi-tenant contracted customers, marking the formal transition from experimental feature to production-ready product. The platform is simultaneously navigating Snowflake's forced password authentication deprecation — a platform-level forcing function requiring customer migrations before September 7. Recent work also includes the MCP server gaining unified cross-project authentication, which enables AI coding assistants to act as first-class operators across a full Keboola stack.
After 3.0 turned it into an observability console, Parseable is hardening the query path.
Parseable shipped 3.0 in early August, pulling alerting, dashboards, traces and an APM view into what had been a log-storage engine, and moving ingestion onto an OpenTelemetry collector. The releases since are consolidation: alert evaluation correctness across multiple datasets and aggregates, query throttling, OIDC configurability, and a steady retirement of older API surface. The 2.9 line that preceded it was largely ingestion performance and multi-tenant security work.
Keboola's Kai AI assistant is now generally available for multi-tenant contracted customers, marking the formal transition from experimental feature to production-ready product. The platform is simultaneously navigating Snowflake's forced password authentication deprecation — a platform-level forcing function requiring customer migrations before September 7. Recent work also includes the MCP server gaining unified cross-project authentication, which enables AI coding assistants to act as first-class operators across a full Keboola stack.
Keboola is building toward a model where AI agents can autonomously manage the data pipeline lifecycle. The MCP server's unified auth is a signal: the target is a world where a developer's coding assistant can browse, create, and modify Keboola pipelines without a human navigating the UI. Kai GA and the MCP expansion are the same thesis from two directions — AI as interface, not AI as feature. Branched storage expansion to BigQuery and Flows improvements in the background are the operational stability layer those agents will depend on.
Kai gaining the ability to create and modify Flows, and the MCP server expanding its coverage to transformation and workspace management, are the two most visible next moves. The Branched Storage on BigQuery release is a prerequisite for Branches 2.0 approval workflows, which would give Kai a way to propose and commit pipeline changes with human review gates.
Parseable shipped 3.0 in early August, pulling alerting, dashboards, traces and an APM view into what had been a log-storage engine, and moving ingestion onto an OpenTelemetry collector. The releases since are consolidation: alert evaluation correctness across multiple datasets and aggregates, query throttling, OIDC configurability, and a steady retirement of older API surface. The 2.9 line that preceded it was largely ingestion performance and multi-tenant security work.
The shape of the work has shifted from making ingestion cheap to making query and alerting trustworthy. Throttling on queries and repeated fixes to alert aggregate evaluation are what a system starts shipping once users point real dashboards at it, and the deprecation of the role API suggests the access-control surface is being reshaped rather than extended. Security work — SSRF, path traversal, SQL injection sanitization, credential masking — has been a constant across both lines.
Expect the 3.1 line to continue as patch releases against alerting and query stability, with the deprecated role API replaced by a newer access-control endpoint rather than simply removed.
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 Keboola or Parseable.
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.
Omni's Apps reach general availability, completing its embedded analytics platform pitch.
See all Keboola alternatives → · See all Parseable alternatives →
Latest ship moves from both products, interleaved chronologically. ⚡ = editorial spark.
They serve adjacent needs but don't currently overlap on shipped themes. Keboola is currently shipping more aggressively (velocity 7.5 vs 6.3), 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. Keboola is currently shipping more aggressively (velocity 7.5 vs 6.3), 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 Keboola alternatives in Analytics are ranked by recent ship velocity. Browse the "Keboola alternatives" section above for the current picks, or visit /alternatives/keboola for the full list with editorial commentary on each.
Top Parseable alternatives in Analytics are ranked by recent ship velocity. Browse the "Parseable alternatives" section above for the current picks, or visit /alternatives/parseable for the full list with editorial commentary on each.