Arcadia Data Demonstrates 88x Faster Performance for Gaining Insights from Modern Data Platforms

By Susan Rojo | September 13, 2018

Technical Review Shows Performance and Concurrency Advantages for Analytics on Apache Hadoop®

SAN MATEO, Calif. — Sep. 13, 2018 — Arcadia Data, provider of the first visual analytics and BI software native to Hadoop and cloud, today announced the results of an Enterprise Strategy Group (ESG) technical review of the Arcadia Data flagship product, Arcadia Enterprise. The review shows that for real-world dashboards each consisting of several visuals, the Arcadia Data native BI technology offered up to 88 times performance improvement compared to a typical configuration of an external BI tool connected to Hadoop.

Companies struggle to generate value and insights from large-scale Hadoop and cloud-based data lakes. The challenge arises because of attempts to shoehorn legacy BI tools into place next to their data lakes, by using data extracts in Tableau or cubes in MicroStrategy to increase performance, for example. This is inefficient and error-prone because of the manual effort required to take data from the data lake into the BI platform, which slows down time-to-insight while increasing costs. Movement of big data requires summarization at the expense of detailed analysis, reducing depth of insight. Alternatively, connecting legacy BI tools directly to Hadoop or cloud data lakes reduces dashboard responsiveness as user concurrency grows, reducing the value of data lakes by limiting the number of users. This report shows that organizations can leverage Arcadia Enterprise to accelerate BI-style dashboards for modern data platforms, alleviating both performance and user concurrency concerns at scale to enable faster and deeper insights for more users.

“Now, more than ever, it is imperative that business users access their organization’s data and perform analysis quickly,” said Priyank Patel, co-founder and chief product officer, Arcadia Data. “To enable this consumerization of data, organizations are turning to modern BI tools that were built natively for architectures like data lakes so they can speed up time-to-insight. These test results show that Arcadia Enterprise accelerates dashboards at scale, enabling a large number of concurrent business users to easily analyze vast amounts of data. It is clear we have built a solution that brings BI to the data, instead of the opposite.”

The benchmark focused on how Arcadia Enterprise improves dashboard and query response times at various levels of user concurrency. ESG examined how performance scaled with a native architecture — that is, without the data duplication required in the extra tiers of in-memory BI servers or external data marts. The testing was performed on a 7-node Amazon EC2 cluster on a data set including an 8-billion row table and was designed to test how much Arcadia Data “analytical views” could accelerate workloads run on a modern data platform. ESG assessed and validated the following effort and results:

  • Arcadia Data identified 3 types of real-world dashboards (basic, intermediate, and advanced) along with the typical queries associated with those dashboards, for a total of 38 different queries.
  • Arcadia Data set up two analytics environments on the same infrastructure. One environment represented the baseline of a configuration typical of external BI tools connecting to Hadoop, and the other used Arcadia Enterprise.
  • A workload simulator was run against varying levels of simulated user concurrency on each of the environments one at a time, to show how they scale as the user load grows.
  • Arcadia Enterprise showed performance improvements of up to 88x for mean visual load time versus the baseline configuration.
  • Arcadia Enterprise continued to scale gracefully at nearly 100 concurrent sessions. In contrast, the baseline configuration could not deliver responsiveness in a reasonable time frame at concurrencies as low as 10.

“While fast BI performance has always been an important capability for large analytical environments, it is even more important today to fulfill self-service demands in big data deployments,” said Kerry Dolan, Sr. IT validation analyst, Enterprise Strategy Group. “We are pleased with the results of our the technical review of Arcadia Enterprise performance, which validates the power of native BI technologies running on modern data platforms like Hadoop and cloud-based architectures.”

Learn more about the ESG Technical Review results and how Arcadia Data sets up users for accessible BI on big data, here.

See Arcadia Enterprise in action by registering for a live demo or view this video of Arcadia Enterprise Feature Highlights.

About Arcadia Data
Arcadia Data provides the first visual analytics and BI platform native to big data that delivers the scale, performance, and agility business users need to discover and productionize real-time insights. Its flagship product, Arcadia Enterprise, was built from inception to run natively within big data platforms, in the cloud and/or on-premises, to streamline the self-service analytics process on data in Apache Hadoop®, Apache Spark®, Apache Kafka®, and Apache Solr®. It enables real-time, high-definition insights in use cases like data lakes, cybersecurity, connected IoT devices, and customer intelligence. Arcadia Enterprise is deployed by some of the world’s leading brands, including Procter & Gamble, Nokia, Royal Bank of Canada, Kaiser Permanente, HPE, and Neustar. To learn more, follow @ArcadiaData or visit

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