How to Integrate Apache Druid with Cloudian

This blog outlines the steps to integrate Imply Druid with Cloudian Object Storage and configure Druid to use Cloudian as its deep storage. Apache Druid is a high-performance, real-time analytics database designed for fast slice-and-dice analytics on large datasets. It integrates both streaming and batch data ingestion, enabling users to perform real-time data exploration and … Read More

How Cloudian Helps Users Save on Data Storage Costs

Enterprises today grapple with an unprecedented explosion of unstructured data at a growth rate that far exceeds the typical 5% to 8% annual IT budget increase. For IT professionals, the question is how to meet this growing need with the limited resources at hand. This challenge is especially acute with data intensive workloads such as … Read More

How Cloudian HyperStore Delivers Scalability and Data Security

Scalability and data security are two fundamental requirements of an on-prem enterprise storage platform. Scalability ensures the platform will meet your need for storage consolidation both now and into the future. Robust security protects your most valuable asset – your company’s data — from the full range of threat vectors. Cloudian is a proven leader … Read More

Solutions for AI, Data Observability, and Data Protection

The Cloudian secure hybrid data lake is a scale-out, on-premises data repository. Shared, scalable, and secure, it can house unstructured data of all types for use cases including AI, data observability, data protection, and more. It offers a unique combination of capabilities that make it ideal for capacity-intensive workloads that require cloud-like capabilities, but in an on-premises … Read More

How to Deploy Cloudian S3-Compatible Storage with Dremio

This blog discusses how to configure Cloudian with Dremio’s Unified Lakehouse.  Dremio enhances data analysts’ ability to perform exploratory analysis and visualization, providing swift query responses. It streamlines the workflow for data engineers by allowing in-place data management within the data lake. For this example of how to connect Dremio to a Cloudian HyperStore bucket … Read More

How to Deploy Cloudian S3-compatible Storage with AWS Mountpoint

For this example of how to connect AWS Mountpoint to a Cloudian HyperStore bucket we will be deploying and configuration the following: AWS CLI AWS Mountpoint We will be leveraging an existing Cloudian HyperStore 7.5.3 (minimum) environment and a CentOS Linux VM as a client host. Prepare HyperStore User and Bucket for AWS Mountpoint Log … Read More

TensorFlow Workloads Gain Scalable Capacity with a Cloudian AI Data Lake

Machine learning with TensorFlow requires vast amounts of data, making scalable object storage an obvious choice for the data platform. In this blog we’ll look at common TensorFlow workloads and why a Cloudian S3-compatible AI data lake is an ideal fit. And finally, how Cloudian HyperStore serves as a universal repository for all AI workloads. … Read More

Global Retailer Streamlines Splunk Data Analytics with a Cloudian AI Data Lake

A prominent global retailer faced challenges in managing the voluminous data generated by its Splunk analytics platform. To address these challenges, the company embarked on a strategic initiative to modernize its data storage infrastructure by integrating Cloudian’s S3-compatible AI data lake. This case study outlines the retailer’s journey from relying solely on HPE 3PAR/Primera Block … Read More

Building a Data Analysis Platform with Apache Druid and a Cloudian Data Lake

Enterprises today are in the thick of data-centric operations where understanding and utilizing time series data has become a fundamental aspect of business intelligence. Whether it’s system metrics, network telemetry, or IoT sensor outputs, time series data is crucial for providing actionable business insights. To analyze and visualize this complex time series data, businesses are … Read More

Provider of IoT for Fleet Management Gains Scalable Storage for Apache Kafka

A leading vehicle fleet management service provider faced challenges with its existing data management infrastructure. The company employed Apache Kafka for data ingest and Hadoop for back-end data management.  However, the lack of disaster recovery capabilities within the Hadoop framework prompted the organization to seek a more robust solution for their growing needs. Storage challenges … Read More