Mark Shainman is a Principal Product Marketing Manager for Dremio. He has spent more than 20-years working in both the analytics as well as privacy, governance, and security space. He has worked with numerous data products and on numerous initiatives, including database migrations, data warehousing, big data, SQL on Hadoop, data lakes, federated query access, data cataloging, privacy compliance and, now, the data lakehouse.
Most enterprise AI projects fail at the same place. Not the model. Not the infrastructure. The data. Specifically: the AI doesn’t understand the data well enough to act on it accurately, and it can’t reach most of the data anyway. These two problems compound each other. A model that can only see 30% of your […]
Apache Polaris provides the open foundation, but enterprises running enterprise-wide, AI-driven platforms need more than a standards-compliant catalog service. They need enterprise governance, automation, and business context that AI systems can reason over. As original co-creator of Apache Polaris and one of the project’s largest contributors, Dremio uses Polaris as the foundation of Dremio’s Open […]
Apache Polaris is now a Top-Level Project at the Apache Software Foundation. For anyone building on Apache Iceberg, this is one of the most important catalog milestones since the REST Catalog spec itself. Graduation means Polaris has cleared Apache’s bar for contributor diversity, governance maturity, and long-term sustainability. It’s no longer incubating. It’s production-grade open […]
The data lakehouse market has moved past the “is this real?” phase. According to Forrester’s The Data Lakehouses Landscape, Q1 2026, lakehouses are now the default architectural choice for modern analytics and AI workloads, driven by the need to simplify data architectures, control costs, and support modern analytics and AI workloads. For technology leaders navigating […]
Companies are racing to operationalize agentic AI, yet the final process of getting from data to decision is extremely difficult, requiring data integration, tuning, and governance management. With Dremio’s latest release, we remove these blockers by putting natural‑language intelligence, explainability, and self‑optimizing performance directly into the lakehouse experience. You get clarity and control without copies, […]
The New Economics of Data Cloud data warehouses like Amazon Redshift were built for a world that no longer exists. In that earlier era, organizations focused primarily on structured business intelligence, static dashboards, and predictable workloads. Data was tightly controlled, compute resources were fixed, and dynamic scalability for rapidly changing workloads was not a concern. […]
Companies today are under constant pressure to deliver faster insights, support advanced analytics, and enable AI-driven innovation. Many organizations chose Amazon Redshift as their cloud data warehouse. However, as data volumes grow and workloads change, Redshift’s legacy warehouse architecture is not meeting their needs—driving many organizations to consider alternatives. Dremio’s intelligent lakehouse platform: a modern, […]
Modern data teams are under pressure to deliver faster insights, support AI initiatives, and reduce architectural complexity. To meet these demands, more organizations are adopting active data architectures—frameworks that unify access, governance, and real-time analytics across hybrid environments. In the newly released Dresner 2025 Active Data Architecture Report, Dremio was ranked #1—recognized as a top […]
Enterprises today face increasing pressure to extract insights from data quickly while controlling spend. Yet, as data volumes explode across cloud and on-prem environments, traditional architectures often fall short—resulting in higher costs, rigid pipelines, and slower decision-making. The Dremio Intelligent Lakehouse Platform addresses these challenges by delivering faster insights and significant total cost of ownership […]
Artificial Intelligence (AI) has become essential for modern enterprises, driving innovation across industries by transforming data into actionable insights. However, AI’s success depends heavily on having consistent, high-quality data readily available for experimentation and model development. It is estimated that data scientists spend 80+% of their time on data acquisition and preparation, compared to model […]
As businesses generate increasing volumes of data, the need for efficient, flexible, and cost-effective data management solutions has never been greater. Legacy Hadoop environments, though groundbreaking when first introduced, often struggle to keep up with the demands of modern data and analytic workloads. From high costs associated with licensing to the complexity of managing Hadoop […]
Enterprises have revolutionized analytics by leveraging the cloud’s scalability and flexibility. Yet, despite the promise of the cloud, many organizations find that a cloud-only strategy doesn’t always meet their performance, cost, or governance expectations. As the complexities of multi-cloud and hybrid data environments grow, it’s time to consider a hybrid lakehouse strategy that combines the […]
Organizations are constantly pressured to unlock data insights quickly and efficiently while controlling costs. However, as businesses amass ever-increasing volumes of data across multiple environments—both on-premises and in the cloud—they encounter significant challenges with traditional data architectures. A Hybrid Iceberg Lakehouse, such as the one offered by Dremio, delivers substantial Total Cost of Ownership (TCO) […]
Artificial Intelligence (AI) has become essential for modern enterprises, driving innovation across industries by transforming data into actionable insights. However, AI’s success depends heavily on having consistent, high-quality data readily available for experimentation and model development. It is estimated that data scientists spend 80+% of their time on data acquisition and preparation, compared to model […]
Organizations are constantly seeking ways to optimize data management and analytics. The Dremio and NetApp Hybrid Iceberg Lakehouse Reference Architecture brings together Dremio’s Unified Lakehouse Platform and NetApp’s advanced data storage solutions to create a high-performance, scalable, and cost-efficient data lakehouse platform. With this solution combining NetApp’s advanced storage technologies with Dremio’s high-performance lakehouse platform, […]
Dremio’s latest version sets a new standard in the overall performance for lakehouse platforms. This release underscores Dremio’s commitment to providing the most high performance Iceberg lakehouse platform, positioning it as the market’s premier lakehouse analytics platform. Reflection Enhancements A Reflection In Dremio, is an optimized relational cache that takes advantage of the platform’s advanced […]
In today’s data-driven world, organizations are increasingly dealing with diverse data environments, encompassing cloud, multi-cloud, on-premises, and hybrid. Efficiently managing and querying data across these varied landscapes can be challenging, particularly when it comes to access control and workload management. Dremio has introduced significant improvements in query federation capabilities, simplifying data access and ensuring robust […]
Dremio continues to innovate and enhance the capabilities of Data Lakehouse environments with its latest feature, Auto Ingest Pipelines for Iceberg tables. This cutting-edge functionality for both Dremio Enterprise Software and Dremio Cloud changes the way organizations handle data ingestion from Amazon S3 into Iceberg tables in Lakehouse environments. What is Automatic Iceberg Data Ingestion? […]
In today’s data-driven world, businesses face the constant challenge of managing and analyzing data across various environments—cloud, on-premises, and hybrid. With our latest release of Dremio 25.1, we continue to innovate and deliver features that enhance performance, streamline data ingestion, and improve federated query access. This release introduces improvements that collectively drive better performance, efficiency, […]
IntroductionIn the era of big data, organizations are increasingly recognizing the limitations of traditional Hadoop infrastructures. As data volumes grow and analytics requirements become more complex, the need for a more agile, scalable, and cost-effective solution has never been greater. Enter the data lakehouse architecture—a modern approach combining the best data lakes and data warehouses. […]
Hadoop, once celebrated as a groundbreaking framework for processing massive datasets, has become increasingly burdensome for most enterprises. Despite its initial advantages, Hadoop is now recognized as slow, costly, and time-consuming to manage. While it was once cheap to provision, the tight coupling of compute and storage, combined with high maintenance costs and inefficiencies, has […]
The data lakehouse is an architectural pattern that leverages storage layers like Hadoop or object storage as the center of gravity for your data. Using tools like Dremio, you can create a decoupled, modular data warehouse. The key component connecting platforms like Dremio to your data lake is a data lakehouse table format such as […]
Part 1: The Challenge for Organizations Organizations must enable data users to leverage and gain insights from their data seamlessly. The goal is to drive business value through comprehensive data analysis, regardless of where the data resides: on-premises, in the cloud, or hybrid cloud environments. While there is a significant push towards cloud adoption, many […]
Over the years, cybersecurity capabilities have evolved from single-point solutions to comprehensive cyber data platforms utilizing advanced analytic-based technologies. With the exponential growth in the volume, variety, and complexity of cyber-relevant data, cybersecurity professionals must leverage cutting-edge data platform technologies to address their needs effectively and economically. In today’s digital age, virtually all data holds […]
Two prominent solutions have emerged in the on-prem, cloud, and hybrid-cloud lakehouse space: Dremio and Starburst Data. Both platforms offer unique features and benefits. On the surface, the platforms look fairly similar, with federated query capability, object store connectivity, SQL on Hadoop functionality, Iceberg support, and support for hybrid cloud environments. A deeper dive reveals […]
With the latest release of Dremio, 25.0 we are helping accelerate the adoption and benefits of Apache Iceberg, while bringing your users closer to the data with lakehouse flexibility, scalability and performance at a fraction of the cost. We are excited to announce some of the new features that improve scalability, manageability, ease of use […]
