The stakes for modern businesses are high. It’s time to move beyond traditional data warehouse solutions. Get massive data capacity, unmatched performance, and operational ease-of-use.
With seemingly endless growth in data volumes, it’s time to consider modern approaches to data warehousing. Poorly utilized compute and storage can lead to costly inefficiencies. Scale storage resources without compromising performance to maximise the value of data.
Pure brings focus on the Modern Data Experience™ to analytics. Pure accelerates time to insight with fast “time to first byte” and high throughput. Deploying fast object storage on-premises increases choice and reduces risk via a cloud-native architecture.
Enterprise workloads demand flexibility. Say goodbye to data silos. Disaggregated storage from Pure scales elastically as a single high-performance source of data. Run multiple isolated workloads and leverage on-demand compute for faster insights.
Get cloud-scale power for hybrid and on-prem ecosystems. With the industry’s first analytical database solution that separates compute from storage for on-prem environments, Vertica and Pure offer new levels of simplicity and flexibility.
for Distributed File Systems & Object Storage
A data warehouse is a storage system optimised for storing structured data to perform the high-speed SQL queries needed to deliver timely business intelligence (BI). From processing high-speed transactions to predictive analytics, data warehouses have a decades-long history as the de facto storage standard used by enterprises to power their BI.
Benefits of data warehouses include:
Consolidation of structured data from multiple disparate sources
Fast analytical queries from relational databases
A dedicated storage solution for cheaper queries and quicker reporting
The differences between data warehouses, data lakes, and data hubs are as follows:
Data warehouse: A single repository for integrating and storing structured data pulled from multiple unstructured data sources across your organisation.
Data lake: A single unrefined repository of all the structured and unstructured raw data sources within an organisation (including data warehouses). Data must still be processed to extract BI insights.
Data hubs provide the data governance needed to streamline data sharing between a diverse collection of endpoints. In this way, data hubs consolidate data lakes and data warehouses into a single access layer. Data processing is abstracted away behind the data hub, giving your organisation a centralized place to extract BI insights.
No hardware, no setup, no cost—no problem. Experience a self-service instance of Pure1® to manage Pure FlashBlade™, the industry's most advanced solution delivering native scale-out file and object storage.
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“We went all in, and now everything runs on Pure Storage arrays. We no longer have discussions of whether storage is the reason for any performance problems.”
