DataGalaxy
vs. Azure Purview

• DataGalaxy has a straightforward setup process and offers pre-built connectors for popular data sources, which facilitates easy connection and cataloging of data.
• The platform also provides a guided onboarding process to help users get started quickly, which is beneficial especially for beginners.
• Some users have found DataGalaxy's interface to be user-friendly, and the platform's design and navigation are well-received​.

• Azure Purview, with its comprehensive data cataloging and scanning, may require a more extensive orientation.
• Its interface, while robust, may need some acclimatization for new users.
• Provides a powerful search functionality, albeit with a requirement for familiarity with Azure's ecosystem.

• DataGalaxy offers several collaboration features for teams to work together on data-related tasks
• Unique web browser plugin allows users to comment on and share data assets directly from their web browser
• Integrates with popular collaboration tools such as Slack and Microsoft Teams

• Azure Purview’s integration with Azure services lays the foundation for collaborative data governance.
• Azure Purview supports role-based access control ensuring secure collaboration.
• However, it might not provide as intuitive a collaborative experience as DataGalaxy.

• DataGalaxy has established a portal for customers to submit ideas for improvements or report technical issues, responding within a 2 to 3 day timeframe.
• The customer support team is known for being responsive and providing personalized support to customers.
• DataGalaxy also offers online resources including a knowledge base, FAQs, and tutorials to help users self-serve their inquiries.

• Azure Purview, being a part of Microsoft's suite of products, has a range of support options available through Azure Support Plans. Customers can choose a plan that best fits their needs, whether they are just starting their cloud journey or are part of a large organization deploying business-critical applications​.
• The support plans include a variety of service levels and response times, enabling customers to select the level of support that aligns with their operational requirements.
• Additionally, there are community forums, documentation, and other online resources available for self-service support.

• Cloud native architecture allows for easy scalability with business needs
• Built on microservices and containerization technologies to handle increasing workloads
• Can seamlessly adapt to the changing needs of an organization
  Provides consistent performance even as the data landscape expands
  
  

• Azure Purview, deeply integrated with the Azure ecosystem, offers superior cloud-native features.

• Its scalability and flexibility are top-notch, accommodating growing enterprise needs.

• Enhanced integration with other Azure services provides a holistic cloud-native data governance solution.

DataGalaxy offers a substantial library of ready-to-go connectors for a variety of data platforms:

• Data Warehouses & Databases: Snowflake, Databricks, Salesforce, MongoDB, DynamoDB, Azure Synapse, among others​.
• Data Visualization: PowerBI, Looker, Tableau Server, Qlik Sense, etc​.
• Data Processing and Others: Amazon Glue, Azure Data Lake, Teradata, Vertica, and more​.
• CRM and NoSQL: Hubspot, Salesforce, MongoDB, DynamoDB, etc​.
• Custom Integrations: Excel, CSV, and others for custom data integration needs

• Azure Services: Includes Blob Storage, Data Lake, Cosmos DB, SQL Database, and more.
• Databases: Encompasses Amazon RDS, SQL Server, Oracle, among others.
• File Stores: Features connectors like Amazon S3.
• Services and Apps: Integrates with Power BI, Salesforce, and similar services.

• DataGalaxy offers flexible pricing options for their data catalog solution
• Provides a quote-based pricing model based on the specific needs of each organization
• Appears to be a considerably more affordable solution according to some customer reviews.

• Azure Purview offers tiered pricing, though it may be on the higher side for larger enterprises.
• Its pricing model is transparent but the costs for extensive data governance needs may add up.
• Additional costs for support packages and extra features could be a consideration.