Atlan vs Collibra: What's Better for Data Catalogs?

Ready to demo the first data catalog crafted for the AI era? Join 2+ million users that trust data.world with their data catalog and governance needs.

Atlan and Collibra are popular solution providers in the world of data governance and cataloging. While both aim to simplify data governance through enhanced visibility, collaboration, and automation, they also have distinct features that set them apart. 

For example, Atlan is a metadata platform that focuses on creating a user-friendly experience with a collaborative environment to help teams manage their data tasks with flexibility. It aims to democratize internal and external data while automating repetitive tasks to simplify data governance processes. 

On the other hand, Collibra leans towards a more comprehensive and structured approach to data governance. 

Collibra provides its clients with in-depth data management capabilities, robust workflows, and extensive compliance features to help them manage their data more efficiently. This makes Collibra especially well-suited for large enterprises and regulated industries that require strict data governance structures. 

A quick overview of Atlan and Collibra:

• Both are data intelligence platforms that help companies manage their data workflows more effectively.

• Atlan excels in ease of use and team connectivity.

• Collibra’s strengths lie in automation within data governance workflows.

Continue reading as we break down the benefits and drawbacks of each company to help you find the data cataloging tool that best fits your business needs.

Atlan is a data cataloging solution for data discovery and metadata management that aims to help teams catalog, govern, and better collaborate on all things data. Its simple UX and intuitive platform have made it a popular tool among enterprise users.

Atlan operates on a centralized platform where all data assets are cataloged and readily accessible. This approach helps to break down data silos and eliminates the barriers that traditionally keep data isolated across different departments or systems within a company.

Similarly, it provides a unified data view, encouraging cross-functional teams and stakeholders to collaborate and leverage shared insights and resources. As a result, it streamlines data workflows through automation and integration capabilities, facilitating seamless connections among different data tools and systems.

In addition to these features, Atlan democratizes data access, ensuring that it is granted only to authorized individuals, based on their roles. As such, authorized team members can make informed decisions based on reliable and updated data.

• Notifies downstream consumers of potential impacts through alerts while simultaneously supporting security and compliance reporting

• Assigns a “freshness” status to assets to avoid the accidental reuse of stale data

• Enriches the user experience in BI tools using additional metadata for consistency and to reduce repeated efforts

• Helps businesses understand their data lineage (origin, transformation, and utilization) to build trust and transparency in data management

• Provides visibility into how a company’s data transforms across its lifecycle

• Improves data accuracy and reliability

• Provides detailed visibility into the system’s underlying technology to allow for customization and extend functionalities to meet your organization’s specific requirements

• Similarly, offers product customization to meet specific user needs and ensure a unique, tailored user experience

• Frees you from the constraints of proprietary systems so you can integrate seamlessly with your existing technology stack and avoid data discrepancies

• Start in three simple steps: add the credentials, select the metadata, and schedule operations

• Organizations can sync their data stack within minutes of purchasing Atlan

• From there, Atlan provides activity logs and automated Slack alerts to constantly monitor data source connections

• Contextualized data curation and policies for efficient governance

• Granular, role-based access control tailored to team needs

• Collaborative knowledge management with easily controlled approvals

• Maintains a simple user interface for managing connections that improves troubleshooting and overall operational efficiency

• Supports a quick setup with native integrations to connect data sources right from the start

• Provides automated, context-rich alerts for every workflow

• AI capabilities are not included in the core data catalog platform, incurring additional fees for access

• This limitation might hinder some companies from accessing advanced data insights and fully realizing their automation potential

• Configuring data governance automation and workflows can be challenging

• This can restrict the adaptability and efficiency of data governance processes

• Lacks streamlined governance task management and notification systems to help users complete assigned reviews and approvals

• This adds an extra challenge for users and can lead to disconnects within or between multiple teams

• Lacks streamlined DataOps communication via pipeline monitors, which leads to inefficiencies and potential errors within your data management and processing workflows

• Can also prevent cross-functional collaboration and alignment between different teams involved in the data lifecycle

• Contains outdated public documentation and lacks readily available information on bugs and fixes

• The rapid development of Atlan’s platform often confuses users due to inconsistent documentation updates and a steep learning curve

Simply put, Atlan is an excellent tool with many capabilities, but it lacks some of the features that fast-paced organizations need to scale their data management processes.

Let’s take a look at what customers think of Atlan in a list of pros and cons:

Pros	Cons
Simplified data search and discovery: Atlan helps organizations save time by simplifying the process of discovering and accessing data assets	Expenses: Fees related to scalability, licensing, and maintenance add up and can quickly turn the platform from an asset to a liability
Robust data governance: Their platform offers comprehensive data governance functionalities that help companies maintain control over data security, data compliance, and personalized quality standards	Difficult to learn: Learning and understanding Atlan’s platform takes time and resources that an organization may not have readily available
Data collaboration: Atlan streamlines teamwork throughout an entire organization, encouraging a more data-driven and collaborative environment	Data integration hurdles: Integrating your current data systems, tools, and processes can be complicated and time-consuming

Collibra is a data intelligence platform that provides trusted data to organizations, allowing them to make confident decisions. It unifies data governance, cataloging, privacy, and quality across all data sources so you can convert your data into a single strategic asset.

Collibra is selected by many businesses because it is one of the longest-standing data catalog solutions in the market. Collibra also has advanced data modeling capabilities, making it a robust and reliable choice for risk-averse buyers.  

Collibra thoroughly maps end-to-end data lineage so users understand where your data comes from and how it's being used. It also automatically categorizes physical data assets and aims to automate manual data tasks.  

Ultimately, Collibra's data modeling capabilities outshine Atlan's due to its extensive functionality across data cataloging, governance, lineage, and privacy. Collibra also integrates AI to govern data with precision while constantly aiming to maximize productivity. Simply put, Collibra makes it easier for businesses to manage complex data structures, when compared to Atlan.

• Defines, monitors, and governs AI models across an organization with automated workflows, processes, and policies.

• Simplifies cross-functional collaboration and integrates with data and AI infrastructures.

• Improves AI model reliability through continuous monitoring and validation

• Automates data governance workflows for swift adaptation to changes

• Centralizes data management so organizations can establish a shared vocabulary for data

• Boosts team collaboration and governance efficiency with smart workflows and AI-enhanced processes

• Connects and catalogs data from different sources for seamless data exploration and understanding

• Provides rich context by integrating business, technical, and privacy metadata with detailed column-level lineage

• Automates classification and categorization of your physical data assets

• Utilizes metadata and business context to dictate who, how, and why data access should be granted

• Uses advanced algorithms to organize and classify sensitive data

• Leverages a no-code interface to create and deploy data access policies

• Integrates with the data catalog to pre-populate asset information

• Collibra has a complex interface that makes it difficult to learn and familiarize with

• External assistance or developer support is required to use the platform

• Cannot directly query and analyze data stored within the platform, which restricts data exploration and analysis to external tools or data sources

• Doesn’t leverage metadata to its full potential for data understanding, governance, and decision-making processes

• Doesn’t incorporate generative AI capabilities to assist users in ideating and formulating research queries

• Can’t provide context-aware search suggestions and recommendations

Simply put, Collibra is a robust data catalog with an extensive range of features, but it can be difficult to personalize. Some teams are turned off by the steep learning curve required to truly incorporate the tool.

We analyzed customer review of Collibra. In summary, these are the pros and cons of choosing Collibra as your data catalog platform: 

Pros	Cons
Comprehensive data governance: Collibra is widely recognized for its robust data governance capabilities, catering to organizations prioritizing data compliance and quality	Resource-intensive deployment and maintenance: Deploying and managing Collibra effectively requires both time and the expertise of skilled data governance professionals due to its complex features and functionalities
Data catalog management: The platform provides centralized data cataloging and metadata management functionalities, streamlining tasks like data discovery, lineage tracking, and asset organization	Overkill for smaller organizations: Collibra's extensive features might be excessive for smaller companies or those with simpler data governance needs
Data integrity and quality: Focusing on the accuracy and reliability of data assets, Collibra provides tools and features for data profiling and quality assessment, helping organizations maintain high standards for their data	Vendor dependency: Organizations may find themselves dependent on Collibra's technology, posing challenges for transitioning to alternative solutions or adding new integrations down the road

Although Atlan and Collibra are good data platforms, they lack AI-assisted search functionalities, streamlined dataOps, and easy-to-use interfaces. That’s why over 2 million users have turned to data.world as their go-to data cataloging solution. 

data.world is the only data catalog built on an advanced knowledge graph architecture that allows users to review all objects, including metadata, tables, and documents, within a graph with interconnected relationships. Leveraging AI capabilities, it automates and streamlines organizational workflows, thereby enhancing data governance and fostering greater data visibility.

Unlike traditional data catalogs, which either focus on data discovery for consumers or data governance for compliance — data.world addresses both needs at once. This ensures organizations don't have to compromise between enabling productive analytics and maintaining well-governed, compliant data. 

While Collibra requires external support, data.world has a high customer success rate because it provides a smooth onboarding process with quick access to ongoing support. That means it's significantly easier to integrate your current data architecture with data.world than it is with either Collibra, Atlan, or any other data intelligence tool. Whether you have prior tech knowledge or not, you can easily become used to data.world’s advanced features without going through a steep learning curve.

Our focus on serving the entire data community with AI-driven features sets data.world apart from Atlan and Collibra — providing a more holistic and supportive data cataloging solution. Check out a full comparison of Atlan and Collibra with data.world:

• Collibra vs data.world

• Atlan vs data.world 

Here’s a quick breakdown detailing the top features of data.world that make it a top choice for customers around the globe.

• data.world's technical architecture ensures that its data queries deliver accuracy levels 3x higher than those of traditional data catalogs

• A highly interconnected data environment highlighting relationships and dependencies within data while also eliminating potential data silos

• data.world allows for better data discovery while implementing AI and automation tools, enabling users to better understand their data and its use cases in a broader business context

• data.world expedites data discovery through AI-assisted search, offering deep contextual results, auto-enrichment, and comprehensive data lineage

• Leveraging highly configurable automations and automation-driven workflows, data.world enhances productivity, engages stakeholders, and accelerates the delivery of analytics

• data.world streamlines the establishment of data trust and collaboration among data-driven teams, fostering confidence in data products and facilitating self-serve access to data and its context

• data.world offers a holistic view of your data, providing comprehensive insights into data stored within the platform itself as well as across all external integrations

• Swift identification of data breaches or potential fraud

Download the data governance report to learn more about the importance of data governance for organizing, locating, and accessing secure data.

• data.world streamlines common data governance tasks using AI-powered Eureka Bots

• Eliminating most repetitive or manual tasks related to data management and metadata enrichment to reduce the risk of human errors in data governance processes

• Scalability solutions for your data no matter how big or complex your database is when you first partner with data.world

• As your data volume increases, your data.world instance stays simple and straightforward

• data.world efficiently handles complex data pipelines and data-driven applications through automations, lineage, and in-app notifications

• Easily accessible, dedicated customer support to guide you from purchase and implementation to future scalability

• Receive support at any time for installation, configuration, and troubleshooting

• data.world is the most-used data catalog on the global market, with 2+ million users and counting

• Serving the leading data teams worldwide, including The Associated Press, OneWeb, Prologis, and others

To sum it up, data.world is the only data catalog built on a knowledge graph architecture, ensuring that its data queries deliver accuracy levels 3x higher than those of traditional data catalogs. Compared to Atlan and Collibra, data.world is the better choice for teams looking to incorporate AI into their business models, or to justify the business case for AI. 

To learn more about why the leading data teams choose data.world, schedule a demo today.