Rather than provide product reviews of all potential data mesh and data fabric products, of which there are hundreds, we decided to profile our three CDO TechVent sponsors.
We created the following reviews after conducting an in-depth briefing with each vendor. Our analysis focuses on each product’s key differentiators and is designed to help companies create a short list of products to evaluate.
Coginiti is an AI-enabled collaborative workspace tailored to the needs of data engineers and analysts. Our mission is to empower organizations by helping them discover, create, and share data assets seamlessly, aligning with their natural workflow.
Headquartered in Atlanta, Coginiti provides a unified enterprise interface, bridging the gaps in data accessibility across distributed organizational structures. Coginiti seamlessly integrates with today’s major data platforms such as Amazon Redshift, Snowflake, Google BigQuery, Databricks, Yellowbrick, and object stores. Coginiti’s AI Assistant empowers data professionals of all skill levels to write, understand, and optimize work, accelerating data and analytic product development. Coginiti provides each user its own workspace and supports an embedded workflow to publish and store certified data products into Coginiti’s analytic catalog, making it easy to search and use them across the entire organization.
Coginiti offers three different products to support individuals, teams, and enterprises:
– Coginiti Pro is designed for individual data analysts, data engineers, and data scientists and costs $189 per user per year.
– Coginiti Premium is designed for teams that want to deliver insights faster by collaborating around a catalog of reusable stored objects and code that can be automated.
– Coginiti Enterprise is designed to scale out to thousands of users and includes cost management capabilities for connected data platforms.
Collaborative Intelligence – The Essential Shift for Creating a Data-Driven Enterprise
White Paper- Why Data Products are the Next Foundation for Empowered, Data-driven Companies
Promethium provides a full-stack data fabric that connects to data wherever it resides, making it easy for power users to discover and evaluate data, join and transform it, and visualize and share it. This self-service data fabric injects agility into a monolithic environment, unlocking the potential of data and the users who want it.
Promethium is the brainchild of Kaycee Lai, former president of Waterline Data, an early data catalog company. Lai discovered that data catalog customers wanted to access and manipulate actual data, not just metadata, and were frustrated that they couldn’t with existing catalogs. Lai formed Promethium to turn a data catalog into a bonafide self-service data fabric that blends discovery and governance with a low-code, no-code data preparation environment to create data sets that answer business questions.
Founded in 2018, Promethium has hundreds of product users, 30 employees, and has received $34.5 million in funding. It’s ideal for companies that want to implement a self-service strategy that reduces or eliminates the persistent bottleneck between business users and an enterprise data team. Promethium’s goal is to deliver answers to business questions in minutes with one-tenth of the resources.
The company’s product supports a seamless workflow between business users, data analysts, and data engineers. It enables business users to pose natural language (NL) questions and receive answers from existing results or AI-generated queries. They can also assign their question to a data-savvy analyst or data engineer who uses the product’s data discovery platform to find appropriate data sets, build federated queries, prepare the results, and deliver a visual representation to the requesting user. Customers can use the product to build virtual or physical data pipelines, manage code in a GIT repository, and convert federated queries into dbt jobs for scheduled execution. The company offers both a freemium and commercial edition of the product.
Starburst offers a data fabric that contains a high-performance distributed query engine built for the cloud that provides analytics on data in your data lake or anywhere in or beyond your organization. With Starburst, you never have to move your data to analyze, govern, or share it. It’s always within reach.
Starburst runs against 18 data sources, including most data platforms in the cloud, such as Amazon Redshift, Google Big Query, Azure Synapse, Teradata, Hive, object stores, and others. Users can run both ad hoc and batch workloads using Starburst’s massively parallel processing engine based on Apache Trino, which was designed to query and analyze massive amounts of data across disparate sources. The creators of Trino founded Starburst to help organizations extract the most value out of their Trino investments. Starburst contains 90% of all Trino code commits but runs at 50% lower total cost of ownership with better connectivity, performance and security.
Starburst Galaxy is a fully managed service in the cloud that provides all the benefits of Starburst without the need to install it on your own servers. Starburst Enterprise runs on premises or in the cloud and provides a robust set of data connectors and centralized, fine-grained access control to all your data. Both products provide petabyte scalability and can access data sources across multiple cloud platforms.
