Alation Alternatives For Data-Driven Organizations

Alation is a data catalog platform. It helps organizations manage their vast data landscapes. Through a centralized repository for organizational data assets, Alation facilitates the discovery and governance of data. Essentially, it serves as a library for an organization’s data.

 How? Alation integrates with various data sources across an organization, digesting and contextualizing the details around that data. Users can search and catalog data assets to strengthen the library. The platform leverages artificial intelligence to enhance data searchability and governance. The end goal is that users can find the data they need and trust its accuracy.

Businesses can accomplish a multitude of objectives with Alation. Primarily, it aids in breaking down data silos, so all departments across an organization can make truly data-driven decisions. Alation also helps to solve data management issues, like staying in compliance or making data a source of collaboration for its users. Through improved data accessibility and reliability, Alation empowers employees to leverage data for analytics, insights, and operational efficiency. Ultimately, through a data catalog like Alation, users look to unlock a competitive edge in the marketplace through data. 

One key reason businesses choose Alation is its user-friendly interface. It’s relatively simple for users of all technical levels to engage with the platform and derive meaningful insights from their data. Alation's approach to democratizing access to data resonates with organizations looking to stand up a data-centric culture. Alation aims for a balance between accessibility and control that end users prefer in a data catalog solution. 

Top Alation Data Catalog Alternatives: 

• data.world

• Microsoft Purview 

• Collibra

• Atlan

• IBM Knowledge Catalog

• Google Cloud Data Catalog

• Secoda

While a solid data catalog, Alation isn’t ideal for all teams and organizations. Some of the particulars of Alation’s potential shortcomings: 

Lack of collaboration and community features

• May fall short in facilitating a dynamic, interactive community tool

• Limited real-time collaboration and shared annotations

• Little discussion in internal forums

Limited AI usage 

• AI is used exclusively for Alation’s search functionality 

• To date, AI functionality  is not used for enhancing data discovery or gaining insights

No dedicated customer success team

• While Alation does have customer success teams at implementation, adoption and growth initiatives tend to be self-serve

• Users are likely to lack support on fulfilling unique, bespoke data initiatives  

Missing key knowledge graph architecture

• Alation isn’t built on a knowledge graph, an architectural component that dramatically improves search, findability, clarity, and accuracy in a data catalog

data.world is a cloud-based platform for data collaboration and governance. It is capable of cataloging and managing enterprise data at scale, and it is one of the most commonly used Alation alternatives.The platform enables users to share and work with data, through a unified view of all data resources and knowledge. Because of its focus on data governance, it helps users manage risks and adhere to regulatory requirements around data. Businesses use data.world to speed time to insight, whether they're using a Business Intelligence dashboard or chatting with generative AI. See what users are saying about data.world. 

data.world Pros & Cons

Many companies use data.world’s data catalog platform for data management and governance. Data.world was built with a unique architecture, incorporating something called a “Knowledge Graph.”  A Knowledge Graph is used to link and integrate data coming from diverse sources. It bridges the “data-meaning gap,” connecting business terminology and context with data and enabling data access via a commonly understood language. This architecture dramatically improves search, findability, clarity, and accuracy in a data catalog. With 2+ million users and counting, data.world is the most-used data catalog on the market today. See how data.world compares to Alation.

Top features of data.world

• Partner intake and dedicated customer support, from implementation to scaling

• Automated data organization, including AI-assisted search with GPT-like bots 

• Automatic data enrichment

• Simple, clear user onboarding 

• Built for scale: as your data volume grows, the complexity of your data.world instance does not

• Responds to complex data pipelines and data-driven applications with automations, lineage, and in-app notifications

• Built on a Knowledge Graph, data.world’s technical architecture means its data queries are 3x more accurate than the traditional data catalog 

• Integrate diverse data types and find relationships between them

• Get context rich answers to questions rather than just a list of search results

“Imagine managing books without title information, author data, cover images, royalties, or number of chapters. That's what it's like managing data without a catalog. Now, information that once took our data scientists a week to find is discoverable in seconds on data.world.” 

– Rupal Sumaria, Penguin Random House

Want to learn more about how a knowledge graph unlocks the comprehensive spectrum of search? Read Data Discovery Without Limits. 

And if you’re interested in learning more about data.world, book a demo today.

Collibra is a data intelligence platform that empowers organizations to achieve effective data management. At its core, Collibra focuses on data governance, data quality, and data privacy. Data governance capability is central to the offering. The  data governance platform includes tools for defining and enforcing data policies, standards, and processes. By doing so, it helps organizations ensure compliance with internal policies and external regulations. It also facilitates the establishment of a common data language across the organization, so that the ways in which data is understood and used are standardized. Collibra also features a data catalog that enables users to discover and understand data assets within the organization. See what Collibra users think about the platform. 

Collibra key features: 

• Data discovery: Collect and aggregate data from a variety of sources and prepare it in formats that both people and software can easily use to run analytics

• Compliance: Supports compliance with PII, GDPR, HIPPA, PCI, and other regulatory standards

• Comprehensive feature set: Access wide range of features to manage data governance

• Integrations: Extensive set of OOTB connectors 

Atlan is the active metadata platform for the modern data stack. It was “built by data teams, for data teams.” Atlan stitches together metadata from various sources (Snowflake, dbt, Databricks, Looker, Tableau, Postgres, etc.) to create a unified data discovery, cataloging, lineage, and governance experience across a team’s data assets. Those assets include columns, queries, metrics, dashboards, and more. Atlan facilitates a two-way movement of metadata to bring context back into the tools and workflows that data teams use every day. For example, a team might deliver context into a BI tool to explain what a metric on the dashboard means. See what Atlan users think about the platform. 

Atlan key features: 

• 360 degree context: Verify assets, add warnings, and attach resources to a GitHub-like repository

• Column-level lineage: Visualize column-level relationships from source to BI

• Business glossary: Build a connected semantic layer by linking your data to keywords in your business with a business glossary

• Auto PII detection: Run Playbooks to auto-identify sensitive PII, HIPAA, and GDPR data

Microsoft Purview is Microsoft’s data governance platform. The platform helps users safeguard and manage data compliance, while natively interoperating with Microsoft Copilot. Purview aims to create visibility into all data assets across an organizational environment. It does so through features like context-aware detection, which helps users identify critical risks with ML-driven analysis. See what Microsoft Purview users think about the platform. 

Microsoft Purview key features: 

• Data map: Manage and automate metadata from multiple hybrid sources

• Data catalog: Understand data origins with lineage visualization

• Data protection: Set data protection policies and track their enforcement, ensuring compliance with laws like GDPR and HIPAA

• Advanced reporting: Understand data usage patterns, detect anomalies, and make informed decisions regarding data governance strategies

IBM’s knowledge catalog is IBM’s answer to the need for a data catalog. The platform claims to help users activate data for AI and analytics with intelligent cataloging and policy management. The software helps manage and curate data, knowledge assets, and their relationships. It is available as managed SaaS or within IBM Cloud Pak for Data. As a cloud-based enterprise metadata repository, it activates information for AI, machine learning and deep learning supported by active metadata. See what IBM Knowledge Catalog users are saying about the platform. 

IBM Knowledge Catalog key features: 

• Advanced discovery: Find relevant assets quickly and at scale based on intelligent recommendations

• Operationalized quality: Track lineage and quality scores across structured data, unstructured data, AI models and notebooks

• Flexible deployment: Deploy on premises, on cloud, or fully managed as a service on IBM Cloud Pak for Data

• Automated governance: Protect data, manage compliance and audit-readiness, and maintain client trust with active policy management and dynamic masking of sensitive data

Google Dataplex is an intelligent data fabric that enables organizations to centrally discover, manage, monitor, and govern data across data lakes, data warehouses, and data marts with consistent controls, providing access to trusted data and powering analytics and AI at scale. Among its features, the platform boasts simplified data discovery, lifecycle management, and centralized security and governance. See what Google Dataplex users are saying about the platform. 

Google Cloud Dataplex key features: 

• Simplified data discovery: Automate data discovery, classification, and metadata enrichment of structured, semi-structured, and unstructured data

• Lifecycle management: Logically organize your data that spans multiple storage services into business-specific domains using Dataplex lakes and data zones

• Centralized security and governance: Enable central policy management, monitoring, and auditing for data authorization and classification, across data silos

• Built-in data quality: Automate data quality across distributed data and enable access to data you can trust

Secoda is an all-in-one data search, catalog, lineage, monitoring, and governance platform to simplify your stack. They encourage users to consolidate data tools and cut costs by monitoring and simplifying the data stack. Secoda draws the through line between data observability, data quality, and data discovery. It’s a version-controlled data catalog that lets you set role-based permissions for each team member. See what Secoda users are saying about the platform. 

Secoda key features: 

• AI assistant: Using a chat interface, get an answer to a data question, regardless of technical ability

• Queries: extract queries from an integration or write and run them within Secoda

• Data quality: Monitor, identify stale data and undocumented resources, and configure notifications

• Data governance: Define roles and responsibilities, assign stakeholders