AWS Glue vs Palantir Foundry comparison

AWS Glue is a serverless cloud data integration tool that facilitates the discovery, preparation, movement, and integration of data from multiple sources for machine learning (ML), analytics, and application development. The solution includes additional productivity and data ops tooling for running jobs, implementing business workflows, and authoring.

AWS Glue allows users to connect to more than 70 diverse data sources and manage data in a centralized data catalog. The solution facilitates visual creation, running, and monitoring of extract, transform, and load (ETL) pipelines to load data into users' data lakes. This Amazon product seamlessly integrates with other native applications of the brand and allows users to search and query cataloged data using Amazon EMR, Amazon Athena, and Amazon Redshift Spectrum.

The solution also utilizes application programming interface (API) operations to transform users' data, create runtime logs, store job logic, and create notifications for monitoring job runs. The console of AWS Glue connects all of these services into a managed application, facilitating the monitoring and operational processes. The solution also performs provisioning and management of the resources required to run users' workloads in order to minimize manual work time for organizations.

AWS Glue Features

AWS Glue groups its features into four categories - discover, prepare, integrate, and transform. Within those groups are the following features:

• Automatic schema discovery: AWS Glue crawlers connect to the organization's source or target data source through a prioritized list of classifiers to determine the schema for users' data. This feature creates metadata in companies' AWS Glue Data Catalog.
  
  
• Schemas for data stream management: The AWS Glue Schema Registry enables users to validate and control the evolution of streaming data through registered Apache Avro schemas for no additional charge.
  
  
• Automatic scaling based on workload: This feature dynamically scales resources up and down based on workload. The feature controls job resources, removing them depending on how much the workload can be split up.
  
  
• FindMatches: This feature is for machine learning-based data deduplication and cleansing, and works by finding records that are imperfect matches of each other to remove useless data copies.
  
  
• Edit, debug, and test ETL code: This feature helps users who have chosen to interactively develop their ETL code by providing development endpoints for editing, debugging, and testing the code it generates for them.
  
  
• AWS Glue DataBrew: An interactive, point-and-click visual interface for specialists to clean and normalize data without the need to write any code.
  
  
• AWS Glue Interactive Sessions: This feature simplifies the development of data integration jobs by enabling data engineers to interactively prepare and explore data.
  
  
• AWS Glue Studio Job Notebooks: This AWS Glue feature provides serverless notebooks with minimal setup, allowing developers to start working in a timely manner.
  
  
• Complex ETL pipeline building: This feature allows the product to be invoked on a schedule, on demand, or based on an event, allowing users to start multiple jobs in parallel or specify dependencies to build complex ETL pipelines.
  
  
• AWS Glue Studio: This AWS Glue feature allows users to visually transform data through a drag-and-drop interface. The product automatically generates the code for ETL processes for users' data.

AWS Glue Benefits

AWS Glue offers a wide range of benefits for its users. These benefits include:

• Users of other AWS products can easily onboard with AWS Glue, as it is integrated across a wide range of the company's services.
  
  
• The solution is serverless, which allows for a lower total cost of ownership.
  
  
• AWS Glue offers more power for users, as it automates much of the effort in building, maintaining, and running ETL jobs.
  
  
• The product allows customers to easily discover and search across all their AWS datasets through AWS Glue Data Catalog.
  
  
• AWS Glue does not require additional payment for managing and enforcing schemas for data streams.
  
  
• The solution facilitates the authority of scalable ETL jobs for beginners and non-coding experts through a drag-and-drop interface.

Reviews from Real Users

Mustapha A., a cloud data engineer at Jems Groupe, likes AWS Glue because it is a product that is great for serverless data transformations.

Liana I., CEO at Quark Technologies SRL, describes AWS Glue as a highly scalable, reliable, and beneficial pay-as-you-go pricing model.

Palantir Foundry is an enterprise data management platform offering comprehensive tooling for working with big data. Because it is an operating system made for modern enterprises, it is highly available and a continuously updated platform.

Palantir Foundry is a fully managed SaaS platform that spans from cloud hosting and data integration to flexible analytics, visualization, model-building, operational decision-making, and decision capture. It equips technical and non-technical users to make data-driven operational decisions.

Palantir Foundry includes tools to integrate data of any scale, format, or structure, and also has granular, flexible access controls for individual datasets. In addition, it has an open, modular architecture with multiple RESTful APIs, it has native applications for developing machine learning and artificial intelligence, it provides sophisticated data science applications for users of all technical abilities, and much more.

Palantir Foundry Features

The most valuable Palantir Foundry features include:

Security, flexibility, interoperability, easy deployment, built-in role classification, purpose-based access controls, interoperable architecture, model integration, AI modeling tools, ontology, custom workflows, team-specific applications, self-serve analytics, lineage system, operational application building, 200+ data connectors, data versioning, change management framework, sand decision orchestration, and custom dashboard and report building tools.

With Palantir Foundry You Can:

• Accelerate development & operations
• Collaborate globally
• Save time on security
• Reduce costs

Palantir Foundry Benefits

Some of the many Palantir Foundry benefits include:

• Modular: Because Palantir Foundry is modular, it can integrate with existing infrastructure.
  
  
• Granular governance: Robust data governance controls help ensure seamless compliance, auditability, and security.
  
  
• Secure data sharing: The security infrastructure allows you to share data securely, within organizations and with chosen partners.
  
  
• Rapid integration: Palantir Foundry can rapidly integrate models and data from data platforms into an operational ontology, and can also fuel existing data platforms.
  
  
• Stand-alone deployment: Palantir Foundry can be deployed standalone and can provide all necessary capabilities for data connection, data integration, and model building.
  
  
• Prevent lock-in: The data and model integration suites are designed to prevent lock-in, and assume that tools will be interoperating with Palantir Foundry as an organization grows.
  
  
• No SQL necessary: Users do not have to use SQL queries or employ engineers to write strings in order to search petabytes of data. With Palantir Foundry, natural language is used to query data and results are returned in real-time.
  
  
• Excellent data integration: Palantir Foundry provides secure, scalable, and resilient integration of all data sources.
  
  
• Availability: The Palantir platform uses DNS routing, gateways and elastic load balancing to ensure availability. Dedicated accounts and virtual resources are used on a per customer basis.
  
  
• Multiple metrics types: The Palantir platform provides hundreds of metrics. Some include average session length, drop-off rate, number of logins per user, number of accounts, and search speed.

Reviews from Real Users

PeerSpot users like Palantir Foundry because it has many advantages:

“It is user-friendly, good automation, and allows you to do a better job of data governance.” - Associate, Inhouse Consulting at a pharma/biotech company

“Works seamlessly with good end-to-end capabilities and the capability to scale.” - Wallace H., Sr. Director at a tech services company