Time to rethink your HDFS stack?

Hadoop Distributed File System (HDFS) powered the early wave of big data. But today’s pipelines need more flexibility, speed, and compatibility with AI and modern analytics tools.

If you're exploring an HDFS replacement or Hadoop modernization project, you’re in the right place. Below you'll find expert guides, real migration stories, and architectural advice to help you make your next move, on your timeline.

What's Driving the Shift?

HDFS didn’t fail; the world changed. Most teams migrating off Hadoop cite:

Coupled compute+storage designs that limit scalability and drive up TCO

Limited compatibility with cloud-native or modern infrastructure

Complex, brittle operations and outdated replication mode

Tooling gaps for modern analytics and AI

Still running HDFS? You’re not behind. But there’s a better way forward.

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Why replace HDFS with AIStor?

1. Architecture Built for Modern Infrastructure

Today’s data lakehouse environments demand independent scaling of compute and storage. AIStor supports a disaggregated architecture with high-density, high-throughput storage that evolves with you, delivering performance HDFS can’t match.

2. Performance That Scales

AIStor delivers cloud-native object storage for Spark, Hive, Flink or Iceberg — powering fast, consistent performance across diverse file sizes, BI and analytics workloads, and AI pipelines.

3. Real-time Resilience and Security

AIStor replaces HDFS’s 3x replication with inline erasure coding, bitrot protection, and active-active replication, offering stronger data protection with significantly less storage waste.

4. Efficiency that lowers TCO

AIStor’s simplicity reduces operational complexity and infrastructure overhead. Less hardware, fewer copies of data required, and fewer moving parts to troubleshoot means greater efficiency, lower TCO, and more freedom to grow.

What you gain when you move

60%

total cost reduction with increased storage capacity.¹

93%

faster performance compared to HDFS benchmark data.²

0-5 TiB support

Better handling of diverse object sizes (0-5TB) vs HDFS small file limitations.³

PB to EB scale

AIStor capacity scales from Terabytes to Exabytes in a single namespace.

¹60%+ cost-to-performance improvement achieved by a leading financial group when migrating from HDFS to MinIO min
‍²93% faster on Sort operations compared to HDFS blocksandfiles
‍³MinIO handles objects from 0 to 5 TiB in size, while HDFS struggles with small files due to NameNode limitations min

What our
Customers
are Saying

“MinIO has helped modernize our data analytics workloads, making them highly scalable, and has increased the adoption of cloud-native technologies within our organization.”

– Cloud Engineer, Major Canadian Bank

“With open file formats + object store, MinIO helped us deploy data services that resulted in sub second responses. I strongly believe Iceberg+MinIO outperforms many traditional solutions like Hive, HDFS, MPP db engines.”

– Data Architect, Global Financial Services Company

Trusted by industry leaders

Start your migration

Your workloads have outgrown HDFS. That’s a good thing.

You’ve taken HDFS as far as it can go. But your infrastructure, your pipelines, and your teams are ready for more. MinIO AIStor replaces HDFS with something built for the next decade, without forcing you to start over.

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