Applications are becoming more data-driven, and to be effective they must process higher volumes of data in real time to make effective decisions.
Pavilion can turbo-charge any decision-making and analytics platform by offering massive storage bandwidth and capacity, combined with low latency, allowing larger data sets to be processed in real time.
Modernize NoSQL deployments by leveraging low latency NVMe-oF Storage
The rapid rise of modern cloud applications that process data in real time and are deployed at massive scale has driven a transformation in the ways that data is consumed, processed, analyzed, and managed for use cases like IoT, Telematics, Video Analytics, Social Media, Data Science, etc. This has had an impact on the way that databases have been designed and operated. The requirements of these applications have outgrown traditional relational database technology and ushered in the rise of unstructured NoSQL databases.
Learn more about how Pavilion Data’s NVMe-oF Storage Platform can improve the performance of applications built on NoSQL while lowering the cost of both infrastructure and operations in large-scale NoSQL deployments. Download Pavilion Data’s MongoDB and Cassandra Solutions Briefs to learn more.
Composable, Disaggregated Infrastructure for GreenPlum Environments
GreenPlum utilizes a modern “shared-nothing” database architecture that automates parallel processing of data and queries and petabyte-scale data ingestion. Greenplum recommends Direct-Attached Storage (DAS) to deploy distributed resources in a scale-out fashion. However, architecting for performance and capacity can be easily compromised. With the advent of NVMe-oF, it is now possible to disaggregate Greenplum compute from storage and achieve superior performance with low latency and advanced data management features.
Learn more about how Pavilion Data’s NVMe-oF Storage Platform can reduce deployed flash by 4x, decrease server overhead and simplify data protection and increase compute density per rack in GreenPlum environments.
Deploy low-latency NVMe-oF storage as a service to your MySQL clustered database
Businesses deploy MySQL to deliver scalability, reliability, and performance to their most demanding applications. High-performance MySQL databases typically require direct-attached storage (DAS) to maintain the necessary levels of performance, which brings along with it all of the problems inherent to DAS; low storage utilization, SKU bloat, and high operational overhead, to name a few.
Learn more about how Pavilion Data’s NVMe-oF Storage Platform can deliver a performance density of 1.66 TPM per unit of rack space. Download Pavilion Data’s MySQL Solution Brief to learn more.
Deliver a real-time, high-speed scalable analytics solutions for Splunk Enterprise
Real-time analytics deliver the actionable insights that enable businesses to remain agile and competitive. By leveraging Pavilion Data’s NVMe-oF Storage Platform, organizations can analyze more data, faster, using less infrastructure, while reducing complexity.
Pavilion Data’s NVMe-oF Platform decreases search times while reducing data-center sprawl by leveraging a composable architecture that allows for independent scaling of storage and compute resources. Download Pavilion Data’s Splunk Solution Brief to learn more.
Accelerating private cloud deployments
Kubernetes is an essential tool for organizations deploying containerized workloads at scale. The vast scalability of Kubernetes deployments is only limited by the performance and manageability of the hardware host. Direct Attached Storage (DAS) is the most common choice for these deployments, which in and of itself quickly runs into scalability challenges; low storage utilization, SKU bloat, and high operational overhead, to name a few.
Learn more about how Pavilion Data’s NVMe-oF Storage Platform can improve the performance and scalability of a wide range of Kubernetes applications. Download the Solution Brief to learn more.
Modern infrastructure for Spark-based applications
We are living in an era of data deluge and as a result, the term ‘‘big data’’ is appearing in many contexts, including meteorology, genomics, complex physics simulations, biological and environmental research, finance, IoT and healthcare. Apache Spark is an open source cluster computing framework for large-scale data processing. It provides parallel distributed processing, fault tolerance and scalability for big-data workloads.
Download our Apache Spark solution brief and learn more about how Pavilion Data’s NVMe-oF Storage Platform accesses high volumes of data, faster, increases operational flexibility and reduces costs in Apache Spark implementations.