External reviews
External reviews are not included in the AWS star rating for the product.
Integration with communication platforms streamlines data access
What is our primary use case?
What is most valuable?
The best feature of Atlan is its integration with communication platforms like Microsoft Teams and Slack, so business users don't have to go into a data catalog to see metadata about data assets. This integration feature is the coolest thing about Atlan. The ML capabilities that suggest data classifications and provide data descriptions are also impressive.
What needs improvement?
One of the main areas for improvement is its governance capabilities. Atlan supports only basic out-of-the-box workflows, and it becomes challenging to customize features like how data owners should approve access to data assets. Its performance is not optimal when dealing with larger datasets, particularly legacy data assets, as the performance declines when scanning datasets running in terabytes.
For how long have I used the solution?
I have done a couple of POCs using Atlan while working for a company. We were evaluating a few data catalogs, and we included Atlan as one of the prospects.
What do I think about the stability of the solution?
During our POC, the recently launched ML classification system was a hit-and-miss. However, the support team acknowledged it and since then, the feedback from various users indicates that the issues have been resolved, and it's now working well.
What do I think about the scalability of the solution?
Atlan integrates well with smaller datasets, making it suitable for agile companies. However, it struggles with performance when dealing with larger datasets, particularly those running in terabytes.
How are customer service and support?
During the POC, we had a dedicated account executive, and we received good support from them. They helped us navigate our challenges and brought in technical resources whenever required. There were instances when responses took longer than expected, but this could be attributed to us not being a full-time paid customer at that time.
How would you rate customer service and support?
Positive
How was the initial setup?
If implementing the cloud instance, the setup is straightforward and simpler than other tools I have experienced. However, placing it on-premises requires support from data engineering or technical associates.
What's my experience with pricing, setup cost, and licensing?
In comparison to established players like Collibra and Informatica, Atlan is cheaper. However, compared to the next generation of data catalogs like Castor, Atlan is pricier. For mid-sized organizations, Atlan provides a good pricing fit.
Which other solutions did I evaluate?
We evaluated Atlan alongside other data catalogs when working for a company.
What other advice do I have?
Atlan is an eight out of ten, primarily due to its need for improved governance features. If these features are enhanced, it is a ten on ten tool.
Atlan has unique ML/AI capabilities that aid engineering teams in documenting without having to start from scratch.
Additionally, its integration with communication platforms helps users understand context without accessing the data catalog directly.
Enhanced data management with intuitive data lineage and metadata visualization
What is our primary use case?
How has it helped my organization?
From a business user's perspective, Atlan has reduced the need to bother subject matter experts by surfacing all data and context. It has significantly reduced instances of business users contacting technical SMEs with questions about data content, providing time savings from a human hours perspective.
What is most valuable?
As a senior analytics engineer, Atlan's ability to show end-to-end data lineage is the most important feature for me. It graphically displays the entire data flow, allowing me to understand the flow from source systems to Tableau, including the ability to see SQL scripts behind it and usage metrics. Its capability to automatically pull data descriptions and assign ownership are also noteworthy.
What needs improvement?
Certain UI changes could make Atlan more user-friendly. While they have an Excel add-in for interaction with Atlan, it's in its early stages and could be improved. Additionally, data observability capabilities could be enhanced to provide more alerts on stale or outdated data via communication tools like Microsoft Teams, Slack, or email.
For how long have I used the solution?
I have been using Atlan for almost a year now.
What do I think about the stability of the solution?
Generally, I find Atlan stable. There have been instances where new features temporarily degraded performance. They were quickly optimized by Atlan's engineering team.
What do I think about the scalability of the solution?
There have been no notable scalability issues with Atlan. Its cloud-native backend infrastructure is designed to scale and may require human intervention occasionally, but it handles scalability well.
How are customer service and support?
The customer service and support are pretty good. Any issues are addressed promptly by Atlan's team.
How would you rate customer service and support?
Positive
Which solution did I use previously and why did I switch?
We looked at Google Cloud Platform's Dataplex. It wasn't fit for purpose because we needed an active metadata platform that could provide comprehensive data discovery and data dictionaries.
How was the initial setup?
The initial setup of Atlan was conducted as a minimum viable product, starting with basic capabilities and building up. From the user's perspective, it involved training a small community of super users to promote adoption.
What about the implementation team?
The implementation of Atlan required less than five people from different teams, mainly technical personnel.
What was our ROI?
It's difficult to quantify ROI at the moment due to our immature use of Atlan, however, it has reduced interruptions for technical queries significantly.
What's my experience with pricing, setup cost, and licensing?
The pricing model for Atlan is reasonable compared to other cloud-based platforms. There are different license levels, and we receive a discount on the unit price, making it very competitive.
Which other solutions did I evaluate?
We evaluated Google Cloud Platform's Dataplex, among other tools, yet chose Atlan for its comprehensive capabilities in data lineage and metadata management.
What other advice do I have?
I would recommend dedicated resources from the beginning, including a product manager, as it facilitates better planning and adoption of the solution.
Overall, I rate Atlan a nine out of ten. They continue to innovate and listen to customer feedback.
Intuitive comprehensive tool enhances metadata management but needs improved lineage capabilities
What is our primary use case?
Data governance is a broad area, and Atlas is used for various purposes including self-service discovery, lineage, root cause analysis, impact analysis, and capturing all the metadata.
What is most valuable?
Atlas is quite intuitive. In the market, tools like Informatica require multiple components, however, Atlas provides all capabilities within one tool. Its UI is appealing and intuitive.
Additionally, the AI part is integrated for enriching metadata engagement, making it a comprehensive tool.
What needs improvement?
The challenge is in the lineage, where it requires improvement. Atlas needs to capture areas where organizations use less known applications.
For how long have I used the solution?
I've used the solution for more than a year now.
What do I think about the stability of the solution?
The UI exposure is very good, but as you consume more resources from the infrastructural point, such as managing bulk metadata, you might need the support of an infrastructure team. This is where Atlas's product team can help by increasing resources.
What do I think about the scalability of the solution?
You can scale, but it's necessary to reach out to their architectural team. Out-of-the-box scaling capabilities are limited and defined as standard by Atlas for their clients.
How are customer service and support?
The support team can be improved, especially the ticketing system. Though the team's knowledge is satisfactory, the overall ticketing process requires enhancements.
How would you rate customer service and support?
Neutral
Which solution did I use previously and why did I switch?
We evaluated other data governance tools before settling on Atlas.
How was the initial setup?
The initial setup doesn't take much time since it's a cloud platform. However, issues may arise with the lineage aspects that Atlas needs to address.
What's my experience with pricing, setup cost, and licensing?
Atlas is competitively priced compared to other data governance platforms like Collibra and Informatica. The only major drawback is its lack of an integrated data quality module.
Which other solutions did I evaluate?
We evaluated other data governance tools previously.
What other advice do I have?
For stability, I would rate relevant features at seven out of ten. Atlas is suitable for smaller to mid-size companies, however, for larger organizations with multiple ERPs and data lakes, it may present challenges.
Streamlined data discovery with cohesive glossary and lineage tracking
What is our primary use case?
We use Atlan as a data discovery tool for data assets in our organization. It is particularly valuable for its ability to serve as a business glossary and a metrics glossary.
Additionally, it helps in lineage tracking to find data sources and overall dataset schema and is used extensively for data quality checks.
What is most valuable?
Atlan is helpful for identifying datasets and discovering PI data, such as the classification levels of datasets (gold, silver, bronze). The tool facilitates easy navigation by keeping descriptions and source information in one place. It supports data glossary terms, which helps with understanding business terms.
What needs improvement?
One area that could be improved is the capability to find duplicates of datasets. This would allow users to identify and consolidate similar datasets, having one point of access for consistent data.
For how long have I used the solution?
I have been working with Atlan for about a year and a half.
What do I think about the stability of the solution?
Atlan is quite stable. I have never seen it crash, and it has always been available to meet our needs. This consistent availability ensures we can find the right dataset when needed.
What do I think about the scalability of the solution?
Regarding scalability, recent updates in Atlan have included data contracts and specification levels for datasets. The company has a good relationship with Atlan, which regularly visits our office to understand our needs. As a result, I would rate the scalability as nine.
How are customer service and support?
I have never spoken to technical support, as I have not experienced any issues that required their assistance.
How would you rate customer service and support?
Positive
Which solution did I use previously and why did I switch?
I am not aware of any previous solutions the organization used before Atlan.
What was our ROI?
It's challenging for me to comment on the ROI since I am just a user of Atlan and do not have visibility into metrics or financial improvements.
What's my experience with pricing, setup cost, and licensing?
I am not aware of the pricing or setup cost.
Which other solutions did I evaluate?
I am not aware of any other solutions that were evaluated.
What other advice do I have?
Overall, I rate Atlan as a ten out of ten. It is an excellent solution for data discovery and glossary needs. I suggest improving duplication detection for datasets as an enhancement.
Democratizing Data: How Atlan Encourages Organization-Wide Collaboration
Easy, Breezy, Data Governance
•It was easy to set up and integrate with our tech stack.
•Navigating it feels intuitive which is critical to a metadata management system you need to put in front of multiple user personas.
They are also developing at a rapid pace which features getting releases each week and an eagerness to hear/respond to feedback. Some of the newer features aren't perfect but they are generally equiavalent to competitors and at the pace of development I see they pulling ahead.
Support has been great - we actually get responses from people that want to help instead of it going into a black hole.
In general the experience is good in usability and could be improved in technical support
Atlan - Modern Data Governance platform
- Data Catalog - An ability to surface catalog of Data Warehouse, Transactional Databases and Data Pipelines in a highly complex environment
- Data Quality and Ownership - Ability to pinpoint critical data and its impact to our clients
- Business Glossary - A single source of truth for all things data
One of a kind player in the data space!
- Collaborating with various other data practitioners.
- Communicating and defining lineage
Atlan: Best-in-class data catalog with customer-centric product development & services
2. Outstanding support from our CSM & Customer Support team: Our CSM serves as a trusted advisor when it comes to the overall architecture of the tool and general data governance best practices. His level of support & commitment for us to get the most value out of the tool is far above the average SaaS CSM support. For instance, our CSM introduced us to a dedicated internal Data Governance Consultant, who took multiple hours of time to share his experience and advise us on how to effectively implement data governance at our organisation.
Likewise, the Customer Support team exhibit impressive technical understanding & structured problem solving, providing us with very timely and deep analyses of any issues coming up.
3. Great pace of delivery for new features: Atlan regularly publishes highly relevant new product features at a fast pace. Very regularly, if we provide feedback around missing or non-optimal functionalities, it turns out that the respective feature is already on the roadmap and might even be released within the next couple of weeks. It has become very apparent that the product strategy is very much centered around customer feedback & pain points, which we appreciate a lot.
2. Pricing: While the Atlan team has been ensuring that pricing should not be a blocker for our data governance efforts, the list prices for connectors and member licenses are fairly high compared to other SaaS tools and only economical at high discounts.
3. Bugs: While Atlan publishes new features at a very strong pace, there are somewhat regular cases where features do not work as expected and need to be fixed by the engineering team. It's worth calling out that in those cases, the fixes are implemented very quickly as well, though!
4. Permission management: The general permission management based on Personas & Purposes is somewhat too complex compared to other SaaS tools and not very user-friendly. We would love for our users to immediately see all metadata and assets that they have access to rather than having to switch between personas & purposes.
Atlan enables us to effectively share knowledge both within our data team and with external stakeholders by serving as a source of truth for our most important term & metric definitions. Terms & metrics can be easily & extensively documented in the Glossary including descriptions, in-depth ReadMes, custom metadata and external documentation (e.g. Confluence). It's also very helpful to be able to link these terms to suitable dashboards and tables to indicate where the source of truth for the respective term or metric comes from.
We're also using Atlan for the documentation of our Snowflake tables. While some documentation has already been included in our DBT models directly, this documentation is not easily accessible for stakeholders or downstream consumers of the data (e.g. analysts). Using Atlan, we can democratise this documentation automatically by pulling the respective descriptions from DBT directly and populating them in Atlan. Using Atlans powerful API, we're also working on loading ReadMes from our directory directly, such that documentation for data engineers becomes easy to populate and consumable by stakeholders at the same time.
Atlan is proving to be highly effective to analyse up- & downstream dependencies of tables, data products and dashboards, significantly reducing communication efforts. For instance, exporting downstream dependencies for impact analysis and analysing upstream dependencies for root cause analysis in Atlan have become an integral part of our data incident management process. Being able to quickly identify impacted assets and their owners not only enables fast assessment of the incident impact. It also allows for immediate stakeholder identification, saving valuable time in the incident resolution.
Lastly, we're also currently starting to use the Data Products & Data Domain features in more depth. Atlan allows to extensively document data products (e.g. description, ReadMe, criticality, sensitivity) and relate relevant tables and dashbaords via automated rules. By being able to add both data products and individual tables & dashboards to data domains, the tool is becoming our source of truth for data roles & responsibilities and valuable input for domain-specific reporting on data governance maturity.