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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This post initially appeared on The New Stack. For a few years there, the term “private cloud” had a negative connotation. But as we know, technology is more of a wheel than an arrow, and right on cue, the private cloud is getting a ton of attention and it is all positive. The statistics are clear, Forrester’s 2023 Infrastructure
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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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The Modern Datalake is one-half data warehouse and one-half data lake and uses object storage for everything. The use of object storage to build a data warehouse is made possible by Open Table Formats OTFs) like Apache Iceberg, Apache Hudi, and Delta Lake, which are specifications that, once implemented, make it seamless for object storage to be used as the
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In this blog, we will demonstrate how to use MinIO to build a Retrieval Augmented Generation(RAG) based chat application using commodity hardware.
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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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In this tutorial, we'll deploy a cohesive system that allows distributed SQL querying across large datasets stored in Minio, with Trino leveraging metadata from Hive Metastore and table schemas from Redis.
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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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An abbreviated version of this post appeared on The New Stack on March 26th, 2024. Businesses aiming to maximize their data assets are adopting scalable, flexible, and unified data storage and analytics approaches. This trend is driven by enterprise architects tasked with crafting infrastructures that align with evolving business demands. A Modern Datalake architecture addresses this need by integrating the
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An abbreviated version of this post appeared on The New Stack on March 19th, 2024. In enterprise artificial intelligence, there are two main types of models: discriminative and generative. Discriminative models are used to classify or predict data, while generative models are used to create new data. Even though Generative AI has dominated the news of late, organizations are still
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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 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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Tl;dr: In this post, we will use MinIO Bucket Notifications and Apache Tika, for document text extraction, which is at the heart of critical downstream tasks like Large Language Model (LLM) training and Retrieval Augmented Generation (RAG). The Premise Let’s say that I want to construct a dataset of text that I can then use to fine-tune an
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Amid the fervor to adopt AI is a critical and often overlooked truth - the success of any AI initiative is intrinsically tied to the quality, reliability and performance of the underlying data infrastructure. If you don't have the proper foundation, you are limited in what you can build and therefore what you can achieve. Your data infrastructure
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The combination of StarRocks and MinIO offers a cloud-native, flexible, and efficient data architecture for modern enterprises, enabling independent scaling and optimized resource utilization. Read the full tutorial for insights into cloud-native analytics with StarRocks and MinIO
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Discover how Databricks and Apache Iceberg's strides in open table formats influence data portability in the modern data stack. Learn how the shift to a private cloud operating model aligns with this evolution, fostering an adaptable, interoperable data ecosystem.
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Unleash data collaboration and quality with Nessie! Learn to manage branches, commits, and merges effortlessly. This guide walks you through deploying Dremio, MinIO, and Nessie, transforming your data engineering with collaborative precision. Dive in to revolutionize your workflows!
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