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 Neo4j — release velocity, themes, recent moves, and the top alternatives to consider.
| Feature | dbt Core | Neo4j |
|---|---|---|
| Sector | Analytics | Analytics |
| Velocity score | 7.5 | 7.5 |
| Sparks · 30d | 1 | 1 |
| Top themes | analytics-engineering, data-transformation, ai-native, open-source | graph-database, agentic, data-warehouse, abac |
| Last editorial update | 6m ago | 11d ago |
| Website | Visit → | — |
dbt 2.0 ships stable with an official OSS/proprietary split and agentic skill loading
dbt shipped its 2.0 stable release on September 16, the first generational version milestone in the project's history. The release formally renames the CLI: what was 'Fusion/dbt-core' becomes 'dbt' (proprietary) and 'dbt-oss' (open source)—a structural separation that existed in practice but now has an official name. New capabilities include native Databricks metric view materializations, a ClickHouse ADBC driver, and AgentSkill installation from dbt packages gated on a new ai_provider flag.
Neo4j's Virtual Graph lets you run Cypher against Snowflake and BigQuery without moving any data.
Neo4j is expanding Aura's geographic reach (AWS London and Montreal this week) while pushing two substantial capability betas: Virtual Graph — a zero-copy bridge that translates Cypher to SQL against BigQuery, Databricks, and Snowflake — and Multiple Databases in a single instance. The August release also shipped native UUID types in Cypher 25 and ABAC for fine-grained access control.
dbt shipped its 2.0 stable release on September 16, the first generational version milestone in the project's history. The release formally renames the CLI: what was 'Fusion/dbt-core' becomes 'dbt' (proprietary) and 'dbt-oss' (open source)—a structural separation that existed in practice but now has an official name. New capabilities include native Databricks metric view materializations, a ClickHouse ADBC driver, and AgentSkill installation from dbt packages gated on a new ai_provider flag.
The OSS/proprietary split is the architectural move that matters most. dbt Labs is building a commercial product on top of dbt-oss, and 2.0 makes that boundary explicit to the ecosystem. The AgentSkills integration signals that dbt sees AI-assisted data transformation as a core product direction—not an add-on. The ai_provider flag is the gating mechanism through which commercial features will increasingly be differentiated.
Expect near-term differentiation between dbt (proprietary) and dbt-oss at the feature level, with AI-native capabilities—AgentSkills, model suggestions, lineage intelligence—landing exclusively in the commercial tier first.
Neo4j is expanding Aura's geographic reach (AWS London and Montreal this week) while pushing two substantial capability betas: Virtual Graph — a zero-copy bridge that translates Cypher to SQL against BigQuery, Databricks, and Snowflake — and Multiple Databases in a single instance. The August release also shipped native UUID types in Cypher 25 and ABAC for fine-grained access control.
Neo4j is positioning itself as the graph layer on top of existing data warehouses rather than a replacement for them. Virtual Graph and ABAC together signal a push into enterprise data architectures where teams have data in Snowflake or BigQuery and want graph traversal without ETL. The multiple-databases GA (coming in months per the release) reinforces that Aura is targeting organizations running multiple isolated tenants on a single cluster.
Virtual Graph will likely exit preview with paid pricing attached once the query-pushdown behavior stabilizes; the next move is probably native support for LLM embedding pipelines that stay in Aura without exporting data to a warehouse.
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 Neo4j.
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 Neo4j 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 and Neo4j are shipping at a similar cadence (velocity 7.5 vs 7.5, both within Sparkpulse's "active" band). 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 and Neo4j are shipping at a similar cadence (velocity 7.5 vs 7.5, both within Sparkpulse's "active" band). 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 Neo4j alternatives in Analytics are ranked by recent ship velocity. Browse the "Neo4j alternatives" section above for the current picks, or visit /alternatives/neo4j for the full list with editorial commentary on each.