Compare Castor vs Metaphor to choose the best Data Catalog for your business. Learn about their unique features in our full product comparison.Try castor
Perhaps you're here because you're actively searching for a data catalog, embarking on your documentation and governance journey, or simply a passionate enthusiast of data and technology. Whatever the reason, we respect and share your interest!
Castor and Metaphor are two popular data catalogs in the market, so you may be wondering, “How do these two solutions compare? Which one is better?”. In this Castor vs Metaphor article, we’ll give a detailed comparison of the two platforms by looking at their key features, target audience, technology integrations, pricing, ratings, and ease of use.
Whether you're on the data team or you’re a business user, you'll gain a comprehensive understanding of how Castor compares to Metaphor, enabling you to make an informed decision on which one is best for your organization.
Let’s start with the basics. If you’re wondering what a data catalog IS, we’ve got you covered. Here’s a brief explanation according to Gartner:
A data catalog creates and maintains an inventory of data assets through the discovery, description, and organization of distributed datasets. The data catalog provides context to enable data stewards, data/business analysts, data engineers, data scientists and other data consumers to find and understand relevant datasets for the purpose of extracting business value.
- Gartner, Augmented Data Catalogs 2019.
The management and organization of extensive datasets are crucial for organizations, and data catalogs serve a pivotal role in this regard. With the increasing need for companies to access, comprehend, and utilize their data on various platforms and software systems, the demand for machine learning data catalog software has surged in recent years. Check out our data catalog landscape if you want to see just how vast the market looks.
We have kept our process as unbiased as possible and have focused solely on the facts available. We have analyzed each company’s offerings paired with reputable customer and third-party review websites such as G2 and Gartner. We evaluated six key factors to help you make an informed decision:
Castor was established by former data scientists, engineers, and heads of data to help companies improve the data experience. It is a plug-and-play data catalog that unifies your data stack by simplifying data discovery, community, and health.
Castor is fit for full company adoption, including use by business teams and analysts. It provides a sleek, easy-to-understand user interface that helps companies understand the data they already have, without having to request reports from the data engineering team. This saves time for both data teams and non-technical teams by harnessing everyone’s collective intelligence so you can work smarter by default.
Business users are empowered by the accessibility of the system, which streamlines data workflows and unblocks data team bottlenecks. In turn, companies can drive efficiency and ROI by improving data health, deprecating unused data, and making higher-quality business decisions. Ultimately, Castor allows companies to optimize their data stack by unifying all of their preferred tools into one cohesive system - without the chaos.
Castor can be integrated with a company’s data stack in less than an hour. They have deep integrations and can connect to metadata across data warehouses, data transformation, and data visualization tools. This provides end users with immediate value and full stack visibility.
Some of the favorite features of Castor, per user reviews, are the elegant interface, the locking of documentation between tools, the query history functionality, and the Autodoc functionality. Other key benefits include the data lineage tool, the automation of data generation, and the overall ease of use.
Metaphor was established in 2020 by the team that created Datahub at LinkedIn. DataHub is an open-source metadata management platform developed by LinkedIn to manage its vast and complex data ecosystem. It was designed to provide a centralized and scalable solution for discovering, understanding, and using data assets across the organization. After seeing the effects of data democratization firsthand at LinkedIn, the founders realized an opportunity to offer metadata management at a larger scale, and they founded Metaphor Data in November 2020. It is important to note that while the company was founded in 2020, the Metaphor Metadata Platform was not released until January 2022, making it relatively new to the market.
Metaphor is a cloud-native, enterprise-ready platform for data discovery and literacy. As a company's data stack tends to grow with time, Metaphor offers a “future-proof” solution that will meet the needs of growing companies. They offer 3 main types of metadata:
The combination of these three data types allows for both technical and business users to easily find what they need. Metaphor integrates into your daily workflow, with a built-in Slack app that allows you to easily communicate, share data, and respond to questions.
Now that you have all the context, let's dive into our evaluation of Metaphor vs Castor along our six key dimensions:
Castor was built for viral, company-wide adoption. The main users are data team members like Data Analysts, Data Scientists, Data Stewards, Data Engineers, and Heads of Data. However, it’s also intentionally designed to be used by the larger company, including Business, Operations, Support, Finance, and Management teams who are looking to make decisions based on accurate and accountable data.
Metaphor was primarily built for Data Scientists, Data Engineers, Subject Matter Experts, and Data Stewards. However, their basic and advanced search options, Slack integration, and social hashtags allow for non-technical use as well. Non-technical users may include Business Analysts, Business Intelligence users, and Product Teams.
While both solutions are built for technical and non-technical users, Metaphor is still very new to the market, and user reviews are not readily available to evaluate the experience of a non-technical user. When you look at Castor compared to Metaphor, Castor is a tried and true choice for company-wide adoption.
Both Castor and Metaphor have external integrations as well as APIs. Here are their current integrations, but please note that as these technologies are developing, more connections are frequently becoming available. For the most up-to-date resources, check out the live pages for Castor Integrations and Metaphor Integrations.
In terms of Data Sources, Metaphor offers two additional integrations that Castor does not - MongoDB and Microsoft SQL Server. However, for Data Visualization and Business Intelligence Tools, Castor offers many more integrations, including Superset, Sisense, Domo, Qlik Sense, Redash, Mode, and Sigma. The two companies offer vastly different Auto-Ingestion/Data Movement integrations, with Castor having dbt, Fivetran, and Stitch, and Metaphor having AWS Glue, Hive, Unity Catalog, Airflow, and dbt. Metaphor also offers some Data Quality integrations, such as Great Expectations, Lightup, Monte Carlo, and Soda.io.
Castor is farther along in the relationship and partnership process with 3rd party integrations specifically when it comes to Data Visualization and Business Intelligence Tools to help business teams. However, Metaphor has more integrations on Engineering and the Data Quality side. Therefore, we’ll give both tools a tie score.
Castor offers three pricing plans - Starter, Premium, and Enterprise, as well as a 14-day free trial.
You can compare all of the features of each plan here. For pricing on Premium and Enterprise, please contact sales.
Metaphor does not include any pricing information on their website. They do offer a free trial and a demo, which you can sign up for online.
Given the less information on Metaphor’s pricing plans, it is difficult to make a comparison to Castor’s pricing information. We’ll score them at average for now.
Castor was created as a result of the founder's experiences with traditional data catalogs, which are clunky, outdated, and difficult to manage. One of Castor’s true differentiators in the world of data catalog systems is its phenomenal user experience and ease of use.
Castor is built for anyone, regardless of their data literacy level, department, or technical prowess, to use. It has a “Google-like” search engine, allowing users to quickly find what they need, with no technical expertise required. It can be set up very quickly and provides value from the very first day of use.
Castor’s goal is to make working with data easy - even fun! (Yes, we said that!)
Metaphor offers an easy-to-use web application, as well as access embedded directly into the tools that teams use on a daily basis, such as Looker, Slack, and Notebooks. Their goal is to make data part of your everyday workflow.
Castor is highly rated in the “Ease of Use” category by independent sites like G2. G2 does not yet have enough information on Metaphor to rate it in any category. We’ll detail this more in the section below.
In writing this article, we consulted both Castor and Metaphor reviews from sites like G2. You can review the Castor ratings here. Because Metaphor is so new to the market, G2 does not yet have enough information to provide rankings for key categories like Ease of Use, Ease of Setup, and Quality of Support.
G2 highlights Ease of Use as the top factor that impacts user satisfaction for Machine Learning Data Catalog products. It rates Castor as a 10/10 in this category.
For Quality of Support, Castor ranks 9.7/10, with the average in this category as 8.6/10. G2 does not have enough information on Metaphor to provide a ranking in this category.
For Ease of Setup, Castor ranks 9.2/10, with the average score in this category 8.1/10. G2 does not have enough information on Metaphor to provide a ranking in this category.
Here are some helpful reviews:
“Easy to use platform that facilitates self-service for our organization and helps us on our documentation journey. The integrations to our data stack and Data Viz layer have been fantastic. The lineage even assisted in a data recovery effort. Very happy with the solution”
- Carson W.
"Castor is saving me a lot of time and money. It's like adding another team to your company that is responsible for one of the most important tasks when growing your database: documentation. This is a lifesaver, especially for a team with a high turnover, it's very easy to pick up the database knowledge for new joiners and person not familiar with what another team is doing. It increases a lot the efficiency of going over data. I recommend and the Castor team is amazing!"
- Marc A.
It is difficult to make a direct comparison between Castor and Metaphor reviews, due to the lack of 3rd party reviews of Metaphor. Metaphor’s scores are not available because G2 does not have enough information on them to provide a score, so we’ll give it the category average. However, Castor’s scores in ALL categories are significantly higher than the industry average in Machine Learning Data Catalog Software.
Castor includes 24/7 Email & LiveChat support for all three plans, including Starter. All clients will be set up with a dedicated Slack channel, and a Solutions Engineer who connects their data and is available to answer any technical questions that may arise. Premium and Enterprise clients also get a dedicated Customer Success Manager for the white glove experience and point of contact. A full list of features can be found alongside their pricing plans.
Metaphor does not specifically outline its service and support options on its website, other than to say that they offer 24/7 support. If you are looking for help with Metaphor, their website lists an email address to contact - firstname.lastname@example.org, where you will receive a response within 24 hours.
When looking at all of the factors discussed, including the target audience, integrations, pricing, ease of use, reviews and ratings, and service and support, the clear winner is Castor.
Castor is ranked higher than the industry average in ALL categories on independent sites like G2. It is farther along in the 3rd party integration process, and offers a very clear service and support plan for all users.
Metaphor has some great features, including its social hashtags, but Castor is the #1 tried and true platform for data lineage and ease of use for the whole organization.
Get a 14-day free trial today and enhance your data experience with Castor.
Enhance your data experience with discovery, documentation, and lineage.