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Best Data Catalogs mark: an unfinished lineage pathBest Data Catalogs

Reviewed, not scored

AI context tools we reviewed but did not score

Short answer

Stardog, data.world (now ServiceNow Data Catalog), Modus and Jedify all position themselves around context for AI agents. Our sources did not cover enough of the nine criteria to score them without guessing, so we list what we found and what is missing.

By The Lineage Desk · Best Data Catalogs · Published

Desk research from public vendor pages. Editorial assessment.

What is Stardog, and why is it not scored?

Semantic layerKnowledge-graph semantic layer

Our reads did not cover lineage, metadata automation or BI coverage, and Stardog's MCP server appears only in a secondary source, so too many criteria would be guesses.

FactWhat we found
Positioning"Semantic AI platform for the enterprise"; page title "The Knowledge Graph-Powered Semantic Layer". Unifies data where it lives and adds semantic context for AI agents.

Source: Stardog homepage

PricingStardog Free at no cost (not open source, renewable license); Enterprise pricing on request.

Source: Stardog pricing

DeploymentStardog Enterprise for on-prem, Stardog Cloud and cloud marketplace offerings.

Source: Stardog pricing

SupportThe Enterprise license includes base support, a dedicated customer success rep and access to solutions architects.

Source: Stardog pricing

Strengths

  • A free edition and an on-prem option.
  • A knowledge-graph approach that unifies data where it lives.

Limits

  • Lineage, metadata automation and BI coverage are not described on the pages we read.
  • Enterprise pricing is not published.
Stardog context path: documents 1 of 5 stages.1Warehouse and lakehouse2Transformation (dbt, ETL)3BI and semantic logic4Governance and access rules5Delivery to agents (MCP or API)
  • Solid dotDocumented on the vendor's pages
  • Dashed hollow dotNot documented on the pages we read
  1. 1Warehouse and lakehouse: Documented

    Unifies data where it lives.

    Source: Stardog homepage

  2. 2Transformation (dbt, ETL): Not documented

    Not described on the pages we read.

  3. 3BI and semantic logic: Not documented

    Not described on the pages we read.

  4. 4Governance and access rules: Not documented

    Not described on the pages we read.

  5. 5Delivery to agents (MCP or API): Not documented

    An MCP server was not confirmed on the vendor pages we read.

A filled node means the vendor's own pages describe that hop. It does not measure how well it works.

Stardog profile

What is data.world (ServiceNow Data Catalog), and why is it not scored?

Catalog and governanceData catalog (part of ServiceNow)

data.world is now sold as ServiceNow Data Catalog with the ServiceNow AI Platform. Its own site could not be opened, and agent delivery, lineage and time to value were not stated on the ServiceNow page we read.

FactWhat we found
OwnershipServiceNow announced an agreement to acquire data.world on 7 May 2025; terms not disclosed.

Source: ServiceNow newsroom (read as a search summary)

ProductServiceNow Data Catalog: centralized metadata, built-in governance and a knowledge graph; a semantic layer adds business meaning to metadata for AI agents; AI-powered search and chat-like exploration.

Source: ServiceNow Data Catalog

Availability and priceAvailable with the ServiceNow AI Platform. No public price.

Source: ServiceNow Data Catalog

IntegrationsSnowflake, Databricks, AWS, BigQuery, Oracle and "100+ platforms through zero-copy architecture".

Source: ServiceNow Data Catalog

GovernanceAutomated workflows for access requests, stewardship and compliance; sensitive data tracking; policy enforcement.

Source: ServiceNow Data Catalog

Customer namedEutelsat.

Source: ServiceNow Data Catalog

Strengths

  • A knowledge graph and semantic layer aimed at AI agents.
  • Governance workflows inside the ServiceNow platform.

Limits

  • Tied to the ServiceNow AI Platform.
  • No MCP server is stated, and no public price.
data.world (ServiceNow Data Catalog) context path: documents 2 of 5 stages.1Warehouse and lakehouse2Transformation (dbt, ETL)3BI and semantic logic4Governance and access rules5Delivery to agents (MCP or API)
  • Solid dotDocumented on the vendor's pages
  • Dashed hollow dotNot documented on the pages we read
  1. 1Warehouse and lakehouse: Documented

    Snowflake, Databricks, AWS, BigQuery and Oracle.

    Source: ServiceNow Data Catalog

  2. 2Transformation (dbt, ETL): Not documented

    Not described on the page we read.

  3. 3BI and semantic logic: Not documented

    Not described on the page we read.

  4. 4Governance and access rules: Documented

    Governance workflows and policy enforcement.

    Source: ServiceNow Data Catalog

  5. 5Delivery to agents (MCP or API): Not documented

    Delivery mechanism to agents is not stated.

A filled node means the vendor's own pages describe that hop. It does not measure how well it works.

data.world (ServiceNow Data Catalog) profile

What is Modus, and why is it not scored?

Context platformContext warehouse

Modus is early-stage. Integrations, customers, lineage depth and pricing were not stated in the page text we read, so most criteria could not be scored from facts.

FactWhat we found
Positioning"The Context Warehouse for Enterprise AI": automatically mine, compose and deliver intent-based context to any AI platform; sections Connect, Learn, Govern, Compose.

Source: Modus homepage

Agents"Claude, Cursor, or in-house: your agents call Modus over MCP or API and get back permission-checked context."

Source: Modus homepage

SecurityThe security section lists SOC 2, ISO 27001, GDPR, HIPAA and CCPA.

Source: Modus homepage

PricingNo public price found.

Source: Modus homepage

Strengths

  • MCP or API delivery with permission-checked context.
  • A security section listing SOC 2 and ISO 27001.

Limits

  • Integrations, customers and lineage are not stated in the page text we read.
  • No public price.
Modus context path: documents 2 of 5 stages.1Warehouse and lakehouse2Transformation (dbt, ETL)3BI and semantic logic4Governance and access rules5Delivery to agents (MCP or API)
  • Solid dotDocumented on the vendor's pages
  • Dashed hollow dotNot documented on the pages we read
  1. 1Warehouse and lakehouse: Not documented

    Not stated in the page text we read.

  2. 2Transformation (dbt, ETL): Not documented

    Not stated in the page text we read.

  3. 3BI and semantic logic: Not documented

    Not stated in the page text we read.

  4. 4Governance and access rules: Documented

    Permission-checked context.

    Source: Modus homepage

  5. 5Delivery to agents (MCP or API): Documented

    MCP or API.

    Source: Modus homepage

A filled node means the vendor's own pages describe that hop. It does not measure how well it works.

Modus profile

What is Jedify, and why is it not scored?

Context platformAutonomous context graph

jedify.com could not be opened, so product pages, pricing and agent delivery were not read; MCP is not mentioned in the funding release we read.

FactWhat we found
Positioning"The autonomous context graph for data-intensive agentic applications and workflows", with patent-pending Semantic Fusion technology.

Source: GlobeNewswire: Jedify raises $24 million Series A

What the graph holdsMetric definitions, entity relationships, lineage, permissions, business rules and terminology, from warehouses, CRMs, financial systems and BI tools plus documents, playbooks, Slack and meeting recordings. Model-agnostic.

Source: GlobeNewswire: Jedify raises $24 million Series A

SnowflakeIntegrates with Snowflake Cortex AI, including Semantic Views, Cortex Analyst and Snowflake CoWork.

Source: GlobeNewswire: Jedify raises $24 million Series A

Funding$24M Series A led by Norwest with Snowflake Ventures and others (10 June 2026); total just over $33 million.

Source: GlobeNewswire: Jedify raises $24 million Series A

Customer namedThe Weather Company.

Source: GlobeNewswire: Jedify raises $24 million Series A

Strengths

  • Covers structured and unstructured sources in one context graph.
  • Deep Snowflake Cortex integration.

Limits

  • Product pages and pricing could not be read.
  • Agent delivery (MCP or API) is not stated in the release.
Jedify context path: documents 3 of 5 stages.1Warehouse and lakehouse2Transformation (dbt, ETL)3BI and semantic logic4Governance and access rules5Delivery to agents (MCP or API)
  • Solid dotDocumented on the vendor's pages
  • Dashed hollow dotNot documented on the pages we read
  1. 1Warehouse and lakehouse: Documented

    Warehouses and Snowflake Cortex.

    Source: GlobeNewswire: Jedify raises $24 million Series A

  2. 2Transformation (dbt, ETL): Not documented

    Not described in the release.

  3. 3BI and semantic logic: Documented

    BI tools are named as sources.

    Source: GlobeNewswire: Jedify raises $24 million Series A

  4. 4Governance and access rules: Documented

    Permissions and business rules in the graph.

    Source: GlobeNewswire: Jedify raises $24 million Series A

  5. 5Delivery to agents (MCP or API): Not documented

    Delivery mechanism to agents is not stated.

A filled node means the vendor's own pages describe that hop. It does not measure how well it works.

Jedify profile

Frequently asked questions

Will these tools be scored later?

Yes, once their public pages cover the criteria. Send a correction with sources through the contact page.

Is a tool that is not scored worse than one that is?

No. Not scored means not enough published evidence for our criteria, not a judgment on the product.