Apache Polaris 1.2.0 continues to make the case for a fully open, production-grade Iceberg catalog. These changes reflect real-world needs: better control, stronger security, broader compatibility, and early hooks for observability.As Iceberg adoption grows, Polaris is becoming the default choice for teams who want to avoid vendor lock-in while building modern lakehouse infrastructure. Whether you’re using Dremio Catalog or deploying Polaris yourself, this release brings features that suppo...| Dremio
Storage Optimization is the process of improving data storage efficiency to enhance data processing, analytics, and overall business performance.| Dremio
Batch Data Synchronization is a process of updating data in bulk to ensure consistency across systems and enable efficient data processing and analytics.| Dremio
Data Refinement is the process of improving the quality, consistency, and reliability of data, enhancing its usability for analysis and decision-making.| Dremio
Data Producers is a term referring to systems or processes that generate and provide raw data for processing, analytics, and other data-driven tasks.| Dremio
Anomaly Detection is the process of identifying patterns or data points that deviate significantly from the norm, indicating unusual behavior or events.| Dremio
ETL Pipelines is a data integration process that extracts, transforms, and loads data from various sources into a unified format for analysis and reporting.| Dremio
Regression is a statistical analysis technique used to model the relationship between a dependent variable and one or more independent variables.| Dremio
Unstructured Data is data that does not adhere to a specific data model or format and cannot be easily organized or processed by traditional databases.| Dremio
Data Access Control is a security measure that regulates and restricts access to data, ensuring that only authorized individuals can view or manipulate it.| Dremio
Data Archiving is the process of moving data that is no longer actively used to a separate storage system for long-term retention and future reference.| Dremio
The Dremio Wiki is a resource-rich hub for data professionals and enthusiasts, covering topics ranging from data lakehouses to data governance and more.| Dremio
Explore the Apache Parquet file format, its storage advantages, and considerations for choosing between Parquet and other data formats in this Dremio guide.| Dremio
Learn how to effectively manage and optimize cloud data lake platforms, using best practices for scalability, performance, and cost-efficiency.| Dremio
See Dremio, the easy and open lakehouse for low-cost analytics. Analyze data quickly and efficiently with new tools, regardless of where it's stored.| Dremio
File formats rarely get the spotlight. They sit under layers of query engines, orchestration tools, and machine learning frameworks, quietly doing the heavy lifting. Yet, the way we store and access data has a direct impact on everything from query latency to model accuracy. And right now, the file format space is undergoing one of […] The post Exploring the Evolving File Format Landscape in AI Era: Parquet, Lance, Nimble and Vortex And What It Means for Apache Iceberg appeared first on Dre...| Dremio
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. […] The post Dremio vs. Redshift: The Cost Advantage of the Dremio Agentic Lakehouse appeared first on Dremio.| Dremio
Apache Polaris brings open, standards-based governance to the modern data lakehouse. It provides a central catalog that defines how Iceberg tables are organized, accessed, and secured across engines and clouds. For anyone who wants to understand how Polaris works, running it locally is the fastest way to see its features in action. This guide walks […] The post Try Apache Polaris (incubating) on Your Laptop with Minio appeared first on Dremio.| Dremio
Caching dramatically reduces latency and computational costs by storing frequently accessed data closer to where it's needed. Instead of repeated expensive operations - such as fetching from object storage, planning complex queries, or executing SQL - the data you need is provided in fast, local memory. To deliver on this, Dremio implements different layers of […] The post The Value of Dremio’s End-to-End to Caching appeared first on Dremio.| Dremio
The Shift from Warehouses to the Agentic Lakehouse Amazon Redshift has long been a dependable data warehouse for analytics, but the analytics landscape has evolved. Organizations are no longer just running dashboards—they’re powering agentic AI systems that reason, act, and make autonomous decisions based on live business data. These workloads demand real-time responses, high concurrency, […] The post Why Dremio Outperforms Redshift: Query Speed, Concurrency, and Cost Efficiency Without...| Dremio
The data world is moving fast. AI agents are no longer science fiction; they’re showing up in workflows, automating tasks, generating insights, and acting on behalf of users. But for these agents to be effective, they need more than just good models. They need consistent, fast, and governed access to enterprise data. That’s where Dremio’s […] The post A Guide to Dremio’s Agentic AI, Apache Iceberg and Lakehouse Content appeared first on Dremio.| Dremio
Apache Iceberg provides a powerful foundation for managing large analytical datasets, but like any data system, performance depends heavily on how well the data is organized on disk. Over time, frequent writes, schema evolution, and streaming ingestion can leave tables fragmented with many small files or oversized files that hurt query speed. Left unmanaged, this […] The post Apache Iceberg Table Performance Management with Dremio’s OPTIMIZE appeared first on Dremio.| Dremio
Managing Apache Iceberg tables effectively is often a balancing act between write performance, storage efficiency, and query speed. While Iceberg’s flexibility enables powerful features like time travel and schema evolution, many teams find themselves running frequent OPTIMIZE jobs to compact small files and rebalance partitions. These jobs improve performance but also consume valuable compute resources, […] The post Minimizing Iceberg Table Management with Smart Writing appeared first on...| Dremio
Apache Iceberg’s snapshot-based architecture is one of its greatest strengths, enabling time travel queries, rollbacks, and strong auditability. But with every update, new snapshots are created and old data files linger. Over time, this leads to growing storage costs, expanding metadata, and, perhaps most importantly, questions around regulatory compliance. How do you ensure that data […] The post Apache Iceberg Table Storage Management with Dremio’s VACUUM TABLE appeared first on Dremio.| Dremio
Reinventing the data warehouse – for the AI era. Accelerate AI and analytics with AI-ready data products - driven by unified data and autonomous performance.| Dremio
Dremio's Reflections technology accelerates queries for near-instant BI across all your data. Effortless to use, it saves time and reduces costs.| Dremio
Integrated Data is a data management approach that combines various sources of data into a unified view for efficient processing and analytics.| Dremio
Unlock the full value of your data with data discovery. Discover, understand, and analyze your data to make better decisions and solve business problems.| Dremio
Learn about ETL and its advantages and disadvantages. Discover the different types of ETL tools available, including code generators and GUI-based tools.| Dremio
Validation is the process of ensuring the accuracy, completeness, and reliability of data, which is crucial for effective data processing and analytics.| Dremio
Predictive Modeling is a technique used in data analysis that involves creating models to predict future events or outcomes based on historical data.| Dremio
Data Mining is the process of discovering patterns, trends, and insights from large datasets using various statistical and machine learning techniques.| Dremio
Data Lifecycle Management is the process of managing data throughout its lifecycle, from creation to archival or deletion, to optimize its usage and value.| Dremio
Explore data modeling, its importance, and how it helps organizations manage data effectively, optimize performance, and drive decision-making.| Dremio
Distributed Systems is a network of interconnected computers working together to solve a problem and process large amounts of data efficiently.| Dremio
Learn about data integration, its benefits, and how it streamlines decision-making by consolidating diverse datasets for effective analysis and reporting.| Dremio
Data Profiling is a process that analyzes data to gain insights into its structure, quality, and content, aiding in data processing and analytics.| Dremio
