Alex Merced

Senior Tech Evangelist, Dremio

Alex Merced is a Senior Tech Evangelist for Dremio, a developer, and a seasoned instructor with a rich professional background. Having worked with companies like GenEd Systems, Crossfield Digital, CampusGuard, and General Assembly.

Alex is a co-author of the O’Reilly Book “Apache Iceberg: The Definitive Guide.”  With a deep understanding of the subject matter, Alex has shared his insights as a speaker at events including Data Day Texas, OSA Con, P99Conf and Data Council.

Driven by a profound passion for technology, Alex has been instrumental in disseminating his knowledge through various platforms. His tech content can be found in blogs, videos, and his podcasts, Datanation and Web Dev 101.

Moreover, Alex Merced has made contributions to the JavaScript and Python communities by developing a range of libraries. Notable examples include SencilloDB, CoquitoJS, and dremio-simple-query, among others.

Alex Merced's Articles and Resources

Blog Post

Adopting Apache Iceberg? How Dremio can enhance your Iceberg Journey

The rise of data lakehouses is transforming the way organizations manage, analyze, and leverage their data. Lakehouse architecture offers a flexible, scalable solution that bridges the gap between traditional data warehouses and data lakes. Apache Iceberg, an open table format designed to deliver reliable, high-performance analytics on large datasets, is at the heart of this […]

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Gnarly Data Waves Episode

An In-Depth Exploration on the World of Data Lakehouse Catalogs (Iceberg, Polaris, Nessie, Unity, etc.) – Other Catalogs

Our final session will explore other catalog options like Unity, Gravitino and beyond. We’ll compare different lakehouse catalog solutions, highlighting their unique capabilities and how to choose the right one for your organization.
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Gnarly Data Waves Episode

An In-Depth Exploration on the World of Data Lakehouse Catalogs (Iceberg, Polaris, Nessie, Unity, etc.) – The Nessie and Polaris Iceberg Catalogs

In this session, we’ll take a closer look at the Nessie and Polaris catalogs and how they enable efficient data management in Apache Iceberg environments. We’ll cover their key features, implementation strategies, and how they improve upon traditional approaches.
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Gnarly Data Waves Episode

An In-Depth Exploration on the World of Data Lakehouse Catalogs (Iceberg, Polaris, Nessie, Unity, etc.) – What are Data Lakehouse Catalogs?

In the first session, we’ll cover the fundamentals of data lakehouse catalogs—what they are, their core functionality, and how they fit into a lakehouse architecture. You’ll gain insights into how catalogs support data versioning, governance, and facilitate better data management.
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Blog Post

Integrating Databricks’ Unity Catalog with On-Prem Hive/HDFS using Dremio

As organizations increasingly adopt hybrid data architectures, they often face challenges in accessing and analyzing data stored across cloud and on-premises environments. Databricks’ Unity Catalog offers a unified metastore that centralizes data management for cloud-based Delta Lake tables, enabling streamlined access to cloud data. At the same time, many companies retain valuable data in on-premises […]

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Blog Post

Integrating Polaris Catalog Iceberg Tables with On-Prem Hive/HDFS Data for Hybrid Analytics Using Dremio

Organizations often have a blend of cloud and on-premises data sources, creating a need for tools that can seamlessly bridge these environments. Dremio has introduced a new connector for Polaris Catalogs managed by Snowflake’s “Open Catalog” service, designed for Iceberg tables, and provides an open-source catalog solution for flexible data access and interoperability across cloud […]

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Blog Post

Dremio Now Has Dark Mode

Dremio has just rolled out version 25.2, and it’s bringing a feature many users have been eagerly waiting for – full dark mode across the entire platform. Whether you’re working late into the night or simply prefer the aesthetics and reduced eye strain that dark mode offers, this update brings a refreshing new way to […]

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Blog Post

Seamless Data Integration with Dremio: Joining Snowflake and HDFS/Hive On-Prem Data for a Unified Data Lakehouse

Organizations often have data distributed across cloud and on-premises environments, which poses significant integration challenges. Cloud-based platforms like Snowflake offer scalable, high-performance data warehousing capabilities, while on-premises systems like HDFS and Hive often store large volumes of legacy or sensitive data. Traditionally, analyzing data from these environments together would require complex data movement and transformation […]

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Blog Post

Breaking Down the Benefits of Lakehouses, Apache Iceberg and Dremio

Organizations are striving to build architectures that manage massive volumes of data and maximize the insights drawn from it. Traditional data architectures, however, often fail to handle the scale and complexity required. The modern answer lies in the data lakehouse, a hybrid approach combining the best aspects of data lakes and data warehouses. This blog […]

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Blog Post

Hands-on with Apache Iceberg Tables using PyIceberg using Nessie and Minio

Flexibility and simplicity in managing metadata catalogs and storage solutions are key to efficient data platform management. Nessie’s REST Catalog Implementation brings this flexibility by centralizing table management across multiple environments in the cloud and on-prem, while PyIceberg provides an accessible Python implementation for interacting with Iceberg tables. In this blog, we’ll walk through setting […]

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Blog Post

The Importance of Versioning in Modern Data Platforms: Catalog Versioning with Nessie vs. Code Versioning with dbt

Version control is a key aspect of modern data management, ensuring the smooth and reliable evolution of both your data and the code that generates insights from it. While code versioning has long been a staple in software development, the advent of catalog versioning brings a powerful new tool to data teams. In this post, […]

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Blog Post

Introduction to Apache Polaris (incubating) Data Catalog

The Apache Polaris (incubating) lakehouse catalog is the next step in the world of open lakehouses built on top of open community-run standards. While many other lakehouse catalogs are vendor-controlled or don’t enable full read-and-write support for Iceberg lakehouses, Polaris takes it a step further by being a community-run project integrating seamlessly with Apache Iceberg […]

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Blog Post

Unlocking the Power of Data Transformation: The Value of dbt with Dremio

The ability to transform raw data into actionable insights is critical. As organizations scale, they need efficient ways to standardize, organize, and govern data transformations. This is where dbt (data build tool) shines. What is dbt? dbt is an open-source tool that allows data analysts and engineers to transform raw data into models using SQL. […]

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Blog Post

Enhance Customer 360 with second-party data using AWS and Dremio

Operational analytic capabilities are foundational to delivering the personalized experiences that customers expect. While first and third-party market data are often the natural starting point, organizations are increasingly discovering that second-party data—the information exchanged securely and confidentially through partnerships and other strategic vendor relationships — are the differentiator that elevates the customer experience to new […]

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Blog Post

Automating Your Dremio dbt Models with GitHub Actions for Seamless Version Control

Maintaining a well-structured and version-controlled semantic layer is crucial for ensuring consistent and reliable data models. With Dremio’s robust semantic layer, organizations can achieve unified, self-service access to data, making analytics more agile and responsive. However, as teams grow and models evolve, maintaining this layer can become increasingly complex. This is where automation and version […]

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Blog Post

Orchestration of Dremio with Airflow and CRON Jobs

Efficiency and reliability are paramount when dealing with the orchestration of data pipelines. Whether you’re managing simple tasks or complex workflows across multiple systems, orchestration tools can make or break your data strategy. This blog will explore how orchestration plays a crucial role in automating and managing data processes, using tools like CRON and Apache […]

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Blog Post

Hybrid Data Lakehouse: Benefits and Architecture Overview

Introduction to the Hybrid Data Lakehouse Organizations are increasingly challenged to manage, store, and analyze vast data. While effective in the past, more than traditional data architectures is needed to meet the demands of modern data workloads, which require flexibility, scalability, and performance. This is where the concept of the hybrid data lakehouse comes into […]

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Blog Post

Tutorial: Accelerating Queries with Dremio Reflections (Laptop Exercise)

In this tutorial, you’ll learn how to use Dremio’s Reflections to accelerate query performance. We’ll walk through the process of setting up a Dremio environment using Docker, connecting to sample datasets, running a complex query, and then using Reflections to significantly improve the query’s performance. Further Reading on Reflections Step 1: Spin Up a Dremio […]

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Blog Post

Simplifying Your Partition Strategies with Dremio Reflections and Apache Iceberg

Designing an optimal partitioning strategy for your data is often one of the most challenging aspects of building a scalable data platform. In traditional systems, data engineers frequently partition data by multiple columns, such as date and another frequently queried field. However, this can result in too many small files or partitions, which ultimately leads […]

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Blog Post

A Guide to Change Data Capture (CDC) with Apache Iceberg

Change Data Capture (CDC) is a design pattern used in databases and data processing to track and capture data changes—such as insertions, updates, and deletions—in real-time. Instead of periodically extracting entire datasets, CDC focuses on capturing only the data that has changed since the last update. This approach is crucial in modern data architectures, where […]

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Blog Post

Using Nessie’s REST Catalog Support for Working with Apache Iceberg Tables

The recent support for the Iceberg REST Catalog Spec in Project Nessie marks a significant improvement in how we interact with the Iceberg catalog across multiple environments and languages. Historically, using a catalog required the client side be implemented for each language (Java, Python, Rust, Go), resulting in disparities of catalog support across different tools […]

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Blog Post

How Dremio brings together Data Unification and Decentralization for Ease-of-Use and Performance in Analytics

The scale, speed, and variety of data are growing exponentially. Organizations are inundated with vast amounts of information from an ever-increasing number of sources, ranging from traditional databases to cloud-based systems and real-time data streams. This data deluge presents significant challenges for traditional data architectures, which often rely on extensive data pipelines and centralized storage […]

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Blog Post

Leveraging Apache Iceberg Metadata Tables in Dremio for Effective Data Lakehouse Auditing

Organizations are inundated with vast amounts of data generated from diverse sources. Managing, processing, and extracting meaningful insights from this data is a significant challenge. The Data Lakehouse architecture has become the next evolution in overcoming these challenges, combining the best features of data lakes and data warehouses to deliver a unified platform for both […]

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Blog Post

Unifying Data Sources with Dremio to Power a Streamlit App

Businesses often face the daunting task of unifying data scattered across multiple platforms. Whether it’s transactional data stored in PostgreSQL, customer preferences housed in MongoDB, or analytics data in a data warehouse like Snowflake, integrating these disparate sources into a cohesive dataset is a complex challenge. This fragmentation not only complicates data analytics but also […]

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Blog Post

Hands-on with Apache Iceberg on Your Laptop: Deep Dive with Apache Spark, Nessie, Minio, Dremio, Polars and Seaborn

Apache Iceberg and the Data Lakehouse architecture have garnered significant attention in the data landscape. Technologies such as Dremio, Nessie, and Minio play a vital role in enabling the Lakehouse paradigm, offering powerful tools for data management and analytics. In this blog, we’ll explore the concept of the Lakehouse, introduce the key technologies that make […]

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Gnarly Data Waves Episode

From Hadoop & Hive to Minio & Dremio: Moving Towards a Next Gen Data Architecture

Join this session to learn how Legacy data platforms often struggle with performance, processing, and scaling for robust AI/ML initiatives, particularly in complex multi-cloud environments. The combined power of MinIO and Dremio creates a data lakehouse platform that overcomes these…
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Blog Post

Why Thinking about Apache Iceberg Catalogs Like Nessie and Apache Polaris (incubating) Matters

The Data Lakehouse pattern, which involves building data warehouse-like functionality on top of a data lake, is rapidly becoming a popular data architecture trend. This approach offers several benefits, including faster data delivery, the ability to make data accessible across teams regardless of their preferred query tools, and a reduction in compute and storage costs. […]

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Blog Post

Evaluating Dremio: Deploying a Single-Node Instance on a VM

If you are reading this, you are probably looking at Dremio as a potential solution to many different problems: If any of the above propositions would add value to your organization, then it would be advisable to evaluate Dremio as a solution, and this guide can hopefully help you learn how to assess Dremio. Individual […]

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Gnarly Data Waves Episode

Special Edition 1 – Apache Iceberg Q&A

The "Apache Iceberg Q&A" is an interactive event featuring Alex Merced, Co-author of Apache Iceberg: The Definitive Guide. Attendees will have the unique opportunity to ask Alex their most pressing questions about Apache Iceberg, whether pre-submitted or asked live during…
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Blog Post

The Iceberg Lakehouse: Key Benefits for Your Business

Introduction to Iceberg Lakehouse Apache Iceberg has been transforming the data industry as a pillar of the open lakehouse architecture. It enables you to maintain a single copy of your data that can be accessed by a vast ecosystem of tools and platforms, providing flexibility and efficiency in data management. Definition and Concept of Data […]

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