Announcing General Availability of MinIO AIStor Tables
AIStor Tables: The first data store to build-in Apache Iceberg™ V3, unifying both tables and objects for analytics and AI at scale
Read moreApache Iceberg
A collection of 25 posts tagged with "Apache Iceberg"
AIStor Tables: Native Iceberg V3 for On-Premises Object Storage
Apache Iceberg V3 boosts performance with deletion vectors that move delete costs to write time, row-level lineage for accurate incremental processing, variant types for efficient JSON queries, and native geospatial types with storage-level pruning. AIStor is the first to support V3.
Read moreThe Case for Embedding Delta Sharing into Object Storage
On-premises data should participate in cloud AI/ML workflows without copying it anywhere. Delta Sharing should be embedded directly into object storage, eliminating separate servers and infrastructure. Data stays put. Queries travel.
Read moreA Global Telecommunications Leader and MinIO AIStor: Powering the Next Generation of Data Lakehouse for Analytics and AI
1. Executive Summary Our customer, a global telecommunications leader, established a Data Platform team to transform how data improved customer experiences and business operations. Faced with ballooning data growth and legacy storage constraints, they replaced aging legacy data storage systems with a high-performance, cloud-native data lakehouse, built on MinIO’s AIStor. The result: a scalable, cost-efficient foundation ready for AI,
Read moreAIStor Tables: Technical Deep Dive
AIStor Tables brings Iceberg catalogs natively into on-prem object storage. It simplifies data organization, enforces table-aware security, and lets AI teams catalog unstructured assets in structured tables, thereby enabling discovery.
Read moreApache Iceberg as the Foundation for Enterprise AI Data: Why MinIO Made Tables Native In AIStor
The format war is over, and Iceberg won. Every major engine now supports it, from Snowflake to Spark. Built for object stores, Iceberg delivers scale, consistency, and simplicity. It is the unified foundation for enterprise AI and analytics. Future-proof your data with Iceberg.
Read moreConverging Formats: From Competition to Consolidation in the Open Lakehouse
Apache Iceberg 1.9.0 closes the gap with Delta Lake, adding row-level ops with lineage, JSON-friendly variant type, geospatial support, REST catalog upgrades, and easier Delta migration. Dropping Hadoop 2 and Spark 3.3 signals a modern focus, driving open table format convergence.
Read moreFrom Data Swamps to Reliable Data Systems: How Iceberg Brought 40 Years of Database Wisdom to Data Lakes
The data lake was once heralded as the future, an infinitely scalable reservoir for all our raw data, promising to transform it into actionable insights. This was a logical progression from databases and data warehouses, each step driven by the increasing demand for scalability. Yet, in embracing the data lake's scale and flexibility, we overlooked a critical difference.
Read moreThe Case for Native Iceberg Catalog APIs and Unified Governance in Object Storage
Apache Iceberg is significantly transforming modern data lakes. Its introduction to object storage platforms has been celebrated for delivering ACID transactions, strong schema evolution, and warehouse-like reliability to data lake architectures. The Iceberg Catalog API standard is crucial to this transformation, as it ensures that various tools can consistently discover tables and execute atomic transactions once a compliant catalog service
Read moreDiscover, Transact, Govern? Unpacking the Iceberg Catalog API Standard's True Scope.
In data engineering, open standards are foundational for building interoperable, evolvable, and non-proprietary systems. Apache Iceberg, an open table format, is a prime example. Along with compute, Iceberg brings structure and reliability to data lakes. When coupled with high-performance object storage like MinIO AIStor, Iceberg unlocks new avenues for creating next-generation, high-performance, cost-effective, and scalable architectures. However, this powerful table
Read moreIceberg's Catalog API: The Atomic Pointer Manager Behind Your Iceberg Tables
Apache Iceberg has significantly reshaped how organizations manage and interact with massive structured analytical datasets inside object storage. It brings database-like reliability and powerful features such as ACID transactions, schema evolution, and time travel. Although these features are commonly emphasized, the Iceberg Catalog API is what makes these tables accessible. The Iceberg Catalog API is a centralized interface for managing
Read moreThe Case for On-Prem Iceberg: Cost, Control, and Performance
Cloud lakehouses break the bank at scale and compromise control. On-prem Iceberg lakehouses deliver speed, savings, and sovereignty. From cancer research to finance, real-world deployments prove it: petabyte-scale performance, full control, and lower TCO are within reach.
Read moreArchitect’s Guide to Open Table Formats and Object Storage
Choosing the right open table format—Apache Iceberg, Delta Lake, or Apache Hudi—can make or break your data lakehouse. This guide breaks down their strengths, how they integrate with object storage, and which one is best for AI, analytics, and real-time workloads.
Read moreThe Definitive Guide to Lakehouse Architecture with Iceberg and AIStor
Discover the power of Apache Iceberg and AIStor in transforming data lakehouses! From multi-engine compatibility to time travel, schema evolution, and blazing-fast performance, this guide dives deep into how Iceberg unlocks the full potential of modern AI and analytics workloads.
Read moreACID Transactions with Iceberg on AIStor
Pairing the Iceberg table format with AIStor creates a powerful, flexible and extensible lakehouse platform. The Iceberg Table Spec declares a table format that is designed to manage “a large, slow-changing collection” of files or objects stored in a distributed system.
Read moreThe Rise of Iceberg: Transforming Data Architectures
Iceberg is shifting the market's focus to scalable, cloud-native storage. This shift is leading to the commoditization of query engines, offering users more flexibility, better pricing, and innovation.
Read moreThe Catalog’s “IT” Moment and What it Means For Object Storage and AI
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.
Read moreThe Significance of Databricks' Acquisition of Tabular: A Triumph for Open Frameworks in Data
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.
Read moreBuilding Modern Data Architectures with Iceberg, Tabular and MinIO
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.
Read moreWhat the Interoperability Trend in Open Table Formats Means for Enterprise Data Architectures
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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