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Dremio Blog: Product Insights
From JSON, CSV and Parquet to Dashboards with Apache Iceberg and Dremio
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Dremio Blog: Product Insights
From Apache Druid to Dashboards with Dremio and Apache Iceberg
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Dremio Blog: Open Data Insights
Ingesting Data into Nessie & Apache Iceberg with kafka-connect and querying it with Dremio
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Dremio Blog: Product Insights
How to use Dremio’s Reflections to Reduce Your Snowflake Costs Within 60 minutes.
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Dremio Blog: Product Insights
From JSON, CSV and Parquet to Dashboards with Apache Iceberg and Dremio
Dremio's `COPY INTO` command, and the soon-to-be-released Auto Ingest feature provide robust solutions for importing these files into Apache Iceberg tables. By leveraging Dremio, ingesting and maintaining data in Apache Iceberg becomes manageable and efficient, paving the way for performant and flexible analytics directly from your data lake. In this article, we’ll do a hand-on exercise you can do in the safety of your local environment to see these techniques at work. -
Dremio Blog: Product Insights
From Apache Druid to Dashboards with Dremio and Apache Iceberg
Dremio enables directly serving BI dashboards from Apache Druid or leveraging Apache Iceberg tables in your data lake. This post will explore how Dremio's data lakehouse platform simplifies your data delivery for business intelligence by doing a prototype version that can run on your laptop. -
Dremio Blog: Open Data Insights
Ingesting Data into Nessie & Apache Iceberg with kafka-connect and querying it with Dremio
This exercise hopefully illustrates that setting up a data pipeline from Kafka to Iceberg and then analyzing that data with Dremio is feasible, straightforward, and highly effective. It showcases how these tools can work in concert to streamline data workflows, reduce the complexity of data systems, and deliver actionable insights directly into the hands of users through reports and dashboards. -
Dremio Blog: Product Insights
How to use Dremio’s Reflections to Reduce Your Snowflake Costs Within 60 minutes.
The most straightforward area to address in terms of reducing costs is your BI Dashboards. Whenever someone interacts with a BI dashboard that uses Snowflake as the data source, queries are sent to Snowflake, increasing your expenditure. Imagine if you could significantly cut the costs of serving dashboards from your Snowflake data by drastically reducing the amount of Snowflake compute resources needed. -
Dremio Blog: Product Insights
From MySQL to Dashboards with Dremio and Apache Iceberg
Moving data from source systems like MySQL to a dashboard traditionally involves a multi-step process: transferring data to a data lake, moving it into a data warehouse, and then building BI extracts and cubes for acceleration. This process can be tedious and costly. However, this entire workflow is simplified with Dremio, the Data Lakehouse Platform. Dremio enables you to directly serve BI dashboards from MySQL or leverage Apache Iceberg tables in your data lake. -
Dremio Blog: Product Insights
From Elasticsearch to Dashboards with Dremio and Apache Iceberg
Moving data from source systems like Elasticsearch to a dashboard traditionally involves a multi-step process: transferring data to a data lake, moving it into a data warehouse, and then building BI extracts and cubes for acceleration. This process can be tedious and costly. However, this entire workflow is simplified with Dremio, the Data Lakehouse Platform. Dremio enables direct serving of BI dashboards from Elasticsearch or leveraging Apache Iceberg tables in your data lake. -
Dremio Blog: Open Data Insights
How Apache Iceberg, Dremio and Lakehouse Architecture can optimize your Cloud Data Platform Costs
By leveraging a lakehouse architecture, organizations can achieve significant savings on storage and compute costs, streamline transformations with virtual modeling, and enhance data accessibility for analysts and scientists. -
Dremio Blog: News Highlights
Dremio is Accelerating Analytics and AI: Exciting New Capabilities and Announcements from Subsurface LIVE!
The Dremio Unified Analytics Platform for Analytics and AI hosted our 6th Annual Subsurface Live event this week - the only event dedicated to Lakehouse learning. We are excited to share a few of the exciting announcements, developments, and new capabilities! Dremio for Every Environment Dremio has always been the most flexible lakehouse deployment, with […] -
Dremio Blog: Product Insights
Experience the Dremio Lakehouse: Hands-on with Dremio, Nessie, Iceberg, Data-as-Code and dbt
ical use cases. While you can deploy Dremio as self-managed software in a Kubernetes environment, you can get some nice bonuses when working with a Dremio Cloud Managed environment -
Dremio Blog: Partnerships Unveiled
Puppygraph Sponsors the Subsurface Lakehouse Conference
PuppyGraph's sponsorship underlines our dedication to empowering individuals and organizations with knowledge and tools to navigate and excel in the evolving data landscape. Through its innovative platform and active participation in the community, PuppyGraph continues to lead the way in advancing graph analytics and data lakehouse technologies, making the complexities of big data more accessible and manageable. -
Dremio Blog: Partnerships Unveiled
Upsolver Sponsors the Subsurface Lakehouse Conference
By sponsoring the Subsurface Conference, we aim to connect with the community, share insights, and explore the future of data lakehouses together. Join us at the conference to witness the evolution of data management and take your first step towards an optimized data future with Apache Iceberg and Upsolver. -
Dremio Blog: Product Insights
Deep Dive into Better Stability with the new Memory Arbiter
Tim Hurski, Prashanth Badari, Sonal Chavan, Dexin Zhu and Dmitry Chirkov -
Dremio Blog: Product Insights
What’s new in Dremio, Delivering Market Leading Performance for Apache Iceberg Data Lakehouses
Dremio's version 25 is not just an update; it's a transformative upgrade that redefines the standards for SQL query performance in lakehouse environments. By intelligently optimizing query processing and introducing user-friendly features for data management, Dremio empowers organizations to harness the full potential of their data, driving insightful business decisions and achieving faster time-to-value. With these advancements, Dremio continues to solidify its position as a leader in the field of data analytics, offering solutions that are not only powerful but also practical and cost-effective. -
Dremio Blog: Product Insights
What’s New in Dremio, Improved Administration and Monitoring with Integrated Observability
Dremio version 25 represents a significant leap forward in making lakehouse analytics more accessible and manageable. With its enhanced monitoring capabilities, seamless third-party integrations, and a suite of additional features, Dremio is setting a new industry standard for ease of administration. These improvements streamline the monitoring process and empower administrators to proactively manage their environments, ensuring that Dremio continues to be an optimal choice for companies seeking advanced, user-friendly analytics solutions. -
Dremio Blog: Product Insights
What’s New in Dremio, Setting New Standards in Query Stability and Durability
Dremio's version 25 is not just an incremental update; it's a transformative release that redefines stability and durability in SQL analytics. By introducing sophisticated memory management, spillable hash joins, and a proactive memory arbiter, Dremio ensures businesses can rely on its engine for their most critical and complex data workloads.
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