Dremio Blog: Open Data Insights
-
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: Open Data Insights
Dremio’s Commitment to being the Ideal Platform for Apache Iceberg Data Lakehouses
Dremio's unwavering commitment to Apache Iceberg is not merely a strategic choice but a reflection of our vision to create an open, flexible, and high-performing data ecosystem. Our deep integration with Apache Iceberg throughout the entire stack complements Dremio's extensive functionality, empowering users to document, organize, and govern their data across diverse sources, including data lakes, data warehouses, relational databases and NoSQL tables. This synergy forms the bedrock of our open platform philosophy, facilitating seamless data accessibility and distribution across the organization. -
Dremio Blog: Open Data Insights
Run Graph Queries on Apache Iceberg Tables with Dremio & Puppygraph
The allure of the data lakehouse architecture, particularly with the Apache Iceberg table format, lies in its ability to be utilized across various systems, eliminating the need for expensive data movement and migration planning. In this article, we will explore how Apache Iceberg tables are employed within Dremio—a data lakehouse platform that serves as a […] -
Dremio Blog: Open Data Insights
BI Dashboards 101 with Dremio and Superset
By enabling efficient, real-time analytics directly from data lakes, Dremio provides organizations with the tools they need to navigate the complexities of big data, derive actionable insights, and maintain a competitive edge in the digital age. -
Dremio Blog: Open Data Insights
Data Lakehouse Versioning Comparison: (Nessie, Apache Iceberg, LakeFS)
Choosing the right versioning solution involves considering your organization's specific data management needs, existing infrastructure, and the desired level of granularity for version control. Whether you prioritize the flexibility of file-level versioning with LakeFS, the seamless table-level versioning of Apache Iceberg, or the comprehensive catalog-level versioning offered by Nessie, each system presents a pathway to more efficient, reliable, and manageable data operations. -
Dremio Blog: Open Data Insights
What is DataOps? Automating Data Management on the Apache Iceberg Lakehouse
DataOps represents a paradigm shift in managing and utilizing data across organizations. By adopting DataOps principles, companies can ensure their data lakehouse architecture is not just a repository of information but a dynamic, efficient engine for innovation and growth. -
Dremio Blog: Open Data Insights
What is Nessie, Catalog Versioning and Git-for-Data?
Nessie's integration with platforms like Dremio demonstrates the significant value that version control brings to the data lakehouse architecture. Whether through the cloud-based ease of Dremio Cloud or the flexible, self-managed approach with Dremio software, Nessie is set to redefine how organizations manage, collaborate on, and deploy their data assets. -
Dremio Blog: Open Data Insights
Trends in Data Decentralization: Mesh, Lakehouse, and Virtualization
Data lakehouse, data virtualization, and data mesh trends significantly shift how we approach data management, addressing today's growing scale, speed, and complexity. -
Dremio Blog: Open Data Insights
What Is a Data Lakehouse Platform?
Dremio also facilitates a gradual and flexible adoption process. Organizations can start small, using only the necessary components, and scale up as their requirements grow. This approach reduces the initial investment and complexity, making it easier for businesses to transition to a data lakehouse architecture at their own pace. -
Dremio Blog: Open Data Insights
Open Source and the Data Lakehouse: Apache Arrow, Apache Iceberg, Nessie and Dremio
The synergy of Apache Arrow, Apache Iceberg, and Nessie within Dremio simplifies complex data management tasks and democratizes access to data analytics, enabling a more data-driven approach in organizations. -
Dremio Blog: Open Data Insights
Why Lakehouse, Why Now?: What is a data lakehouse, and How to Get Started
The data lakehouse, as the latest milestone in this evolution, embodies the collective strengths of its predecessors while addressing their limitations. It represents a unified, efficient, and scalable approach to data storage and analysis, promising to unlock new possibilities in data analytics. -
Dremio Blog: Open Data Insights
ZeroETL: Where Virtualization and Lakehouse Patterns Unite
Dremio's Lakehouse platform represents a significant step forward in the evolution of data management. By leveraging data virtualization and lakehouse architecture, it offers a viable solution to the limitations of traditional ETL-based approaches. Organizations embracing Dremio can expect an improvement in their data management capabilities and a strategic advantage in the fast-paced world of data-driven decision-making. -
Dremio Blog: Open Data Insights
Overcoming Data Silos: How Dremio Unifies Disparate Data Sources for Seamless Analytics
Dremio stands as a formidable solution to the pervasive challenge of data silos. Unifying disparate data sources enables organizations to leverage their data assets fully, enhancing decision-making and operational efficiency. As the data landscape evolves, tools like Dremio will be critical in shaping a more integrated and insightful approach to data analytics. -
Dremio Blog: Open Data Insights
Connecting to Dremio Using Apache Arrow Flight in Python
Whether through direct PyArrow library usage or leveraging the dremio-simple-query library for simplified querying and data manipulation, the synergy of these tools opens up new possibilities for data analysis and processing. The ability to convert data streams into different formats ensures compatibility with a wide array of data processing and analytics tools, making this approach highly versatile. -
Dremio Blog: News Highlights
Loading Data Into Apache Iceberg Just Got Easier With Dremio 24.3 and Dremio Cloud
this is a product release announcement regarding new ingestion capabilities for Apache Iceberg. Customers can now use COPY INTO to get data in parquet format into Iceberg tables.
- 1
- 2
- 3
- …
- 7
- Next Page »