Data Catalog Benchmark

By Louise de Leyritz from CastorDoc

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More data, more tools, more people = more data catalogs

At Castor, we believe the first step to structure the data catalog market, is more transparency. For that reason, we put up a list of all the catalog tools we heard of.

Companies are deploying their analytics to more people in the company. Now, regardless of data literacy, most departments of large companies are using data. For that reason, there's a need to improve trust and understanding in data resources and infrastructure.

This explains the recent explosion in the past two years of data catalogs (internal, open-source, and SaaS). This new trend is not going to stop, and we'd rather bring visibility and structure soon.

Proposed Dimensions

  • Specialization: Data Catalog Only Tools vs Data Catalogs integrated into a larger offering
  • Optimized for: Mid-Market vs Enterprise
  • Main Use-Case: Compliance vs Analysts Productivity

This list is still exploratory, may contain errors, or lacking information. Please reach out to us, if you notice anything wrong:

In-depth analysis and evolution

Read the full breakdown by generation and market analysis of data catalogs here

Feature definition

This benchmark does not mention traditional features of data catalogs such as search & discovery - It assumes all data catalogs share these foundational features. This benchmark evaluates catalogues based on features that are susceptible to make a difference.

  • Collaboration
  • Column Lineage
  • Data quality
  • Governance
  • Personalized views
  • Chrome Extension
  • Two way sync: let the source of truth emerge. If everything is on sync then everything is the SSO  
  • AI documentation
  • AI for SQL
  • AI assistant
  • RBAC
  • Reporting suite
  • Metadata bulk edit

Frequently Asked Questions

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Do You Need a Data Catalog?

If you're having trouble finding the data; A data catalog is a tool that brings together information, from different data sources making it easier for users to search, discover and access the specific data they require. Without a catalog users may waste time navigating through databases and platforms in order to locate the datasets they need.

If you're unsure which datasets to utilize; A data catalog often provides features like data quality scores, user reviews and additional annotations. These features assist users in identifying relevant datasets that align with their goals leading to improved decision making and analytical outcomes.

If you have too many data sources at your disposal; In organizations data is scattered across various locations such as, on premises databases, cloud storage systems or third party platforms. A data catalog consolidates metadata from all these sources into a view making it easier for users to explore all data options and select the most suitable source based on their requirements.

If your data environment has never been properly documented it can lead to chaos and inefficiency. Having a data catalog is crucial as it not helps organize your data but also ensures documentation. It stores information, about data lineage, owners and definitions enabling everyone in the organization to have an understanding of the origin, purpose and characteristics of each dataset.

In case you need to comply with data regulations such as GDPR, CCPA or others it becomes essential to have an understanding of where personal data's stored how its utilized and who has access, to it. A data catalog can track this metadata, making it easier for organizations to demonstrate compliance and ensuring that sensitive data is handled appropriately.