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Today, cloud adoption has become mainstream as most businesses have begun to invest heavily in consolidating and moving their data to the cloud. However, when it comes to BI and data analytics, they face limitations due to scale, costs or memory thresholds. Organizations face challenges in analyzing all their data using existing BI tools and cloud architecture to meet the performance SLAs or to justify the costs associated with analyzing billion-scale datasets.
On the other hand, meeting the end user's expectations to explore all their available data and deep-dive into the required metrics to get answers isn't a piece of cake either. No matter how efficient the optimization techniques deployed are, analysts still have to go through the hassle of sluggish dashboards when data volume crosses a threshold or when complex queries are fired. As a result, data analytics is delayed, decision-making suffers and the end users do not get the insights they need in time.
This is why businesses need an analytics acceleration platform that eliminates latency and delivers sub-second responses and can help them analyze as much data on the cloud as required, irrespective of data size or query complexity. Let's compare 5 leading acceleration platforms of 2023:
Dremio is an open data lakehouse platform that empowers data engineers and analysts to quickly get started with self-service SQL analytics. The solution enables data consumers to run BI workloads directly on the data lake eliminating the need to move data into data warehouses or create aggregation tables, or BI extracts.
Dremio's open architecture and intuitive interface allow data access using any BI tool while ensuring flexibility and strict access control for data consumers. The cloud and on-premises offerings of Dremio deliver cost efficiencies and performance benefits across multiple clouds.
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