A collection of 54 posts from Brenna Buuck
Catalogs are revolutionizing modern datalakes, with industry giants like Databricks and Snowflake adopting Apache Iceberg’s catalog REST API. A commitment to open standards enhances performance, fosters innovation, and transforms data management for AI and ML.
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The semantic layer in modern datalakes provides context and structure to raw data, crucial for key data initiatives like AI model training, data management and data governance. A unified strategy and robust infrastructure are essential for effective implementation of the semantic layer.
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Databricks' acquisition of Tabular, founded by the creators of Apache Iceberg, underscores the importance of open frameworks in modern data lake design. Open frameworks ensure interoperability, flexibility, and simplicity, benefiting those leveraging data for AI.
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Migrate from Hitachi Content Platform (HCP) to MinIO using the HCP-to-MinIO tool. Migration is a no-brainer given how MinIO offers modern, scalable, high-performance storage optimized for AI.
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Unlock Snowflake's potential by integrating external tables with MinIO. Seamlessly query external data without migration, boost analytics, save costs, and simplify access. This setup provides real-time insights and maximizes your infrastructure investment for both MinIO and Snowflake.
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Snowflake's support for external tables has seen significant updates since our last blog post on how to extend your Snowflake implementation with MinIO. External tables allow users of Snowflake to treat data in object storage like MinIO as a read-only table in Snowflake without migration. Snowflake's ongoing enhancements to their external table functionality clearly demonstrate the
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Discover how MinIO Catalog optimizes resource utilization. With real-time insights from powerful GraphQL queries, MinIO Catalog helps organizations streamline storage, cut costs, and enhance data security. Learn to manage your data efficiently and make smarter decisions.
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Explore how Kubernetes v1.30 can enhance your MinIO deployment. Kubernetes v1.30 offers enhanced security, networking improvements upcoming features in beta. Consider upgrading for optimized, secure deployments for modern data workflows.
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Discover how to seamlessly migrate from HDFS to modern object storage without ripping out all of your current systems. Learn valuable strategies to retain essential tools and modernize your infrastructure for AI/ML.
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Discover RisingWave, an open-source streaming database revolutionizing data lakehouses. Built for speed and scalability, it empowers developers with SQL on streaming data. Unlock the potential of real-time analytics and scalable data processing for your AI initiatives.
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Apache Arrow is an open-source columnar memory format that is vital for modern datalakes. This is because Arrow makes data processing swift and seamless across various systems. Arrow propels AI and analytics by enhancing interoperability and computational efficiency.
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Explore the integration of SingleStore, a high-performance cloud-native database, with MinIO in the Modern Datalake Stack. This tutorial provides hands-on experience in data storage, processing, and querying, fostering experimentation and innovation in data management, analytics, and AI workloads.
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Discover the latest trend in databases: Disaggregation 2.0. Tomasz Tunguz's insightful post on LinkedIn explores how databases are evolving into high-speed query engines, shedding traditional storage constraints. Embrace flexible, performance-driven architectures.
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Unlock the power of modern datalakes with Hudi, MinIO, and HMS. Seamlessly integrate these technologies for enhanced data governance. Set up your own cloud-native datalake and explore it with Spark.
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Explore how MinIO Catalog revolutionizes data management by enabling efficient searching and querying of namespaces and metadata. Discover how this exclusive feature streamlines compliance checks, operational automation, and space utilization management.
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Explore modern data architecture with Iceberg, Tabular, and MinIO. Learn to seamlessly integrate structured and unstructured data, optimize AI/ML workloads, and build a high-performance, cloud-native data lake.
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This tutorial guides you through constructing robust data pipelines on the edge, ensuring flexibility and scalability. Learn to create, populate, and transform datasets seamlessly while prioritizing data privacy. Master the art of automation with MinIO's Python SDK.
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Explore the essential role of Data Engineers in unleashing the true power of AI! Data Engineers have a critical foundation in cleaning and structuring raw data for ML success. Learn why their expertise in data infrastructure, feature engineering, and pipeline optimization is indispensable.
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Learn how to integrate MinIO into your Enterprise CockroachDB instance as a changefeed sink, ensuring durability and scalability. This guide enables an enterprise-grade CDC strategy, vital for real-time data fabrics, analytics, and machine learning.
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Explore the future of AI in an open-source landscape, challenging Big Tech's masked efforts. Learn how embracing extreme open innovation fosters collaboration, drives market growth, and sets the stage for an open-source AI data stack.
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Replication
Versioning
Observability
Encryption
Key Management Server
S3 Compatibility
Object Immutability
Catalog
Object Prompt
Identity + Access Mgt
Firewall
AIHub
Lifecycle
Cache
Events and Lambdas
Console
Erasure Code Calculator
Reference Hardware
Integrations with MinIO
Download MinIO Object Store
Events