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Highlights from the Kinetica Founders Interview Series

By Andrew Wooler | January 14, 2021

Last month we released an interview series with our founders, Amit Vij and Nima Negahban. We asked them to touch on some of the hottest topics in the data and analytics community today, such as machine learning, the optimal architecture for analytics at scale, and how to be developer-friendly. Below we’ve collected some of the…

Understanding the Challenges of Supply Chain and Logistics

By Andrew Wooler | January 8, 2021

While many of us have marvelled at modern logistics and supply chains, we haven’t had to think too much about how they are made possible — just drop your letter in the mail, or click a button online, and your item will arrive only days later. The pandemic, however, has brought the unique challenges of…

Sensitive Data Protection in Kinetica

By Dipti Joshi | December 7, 2020

Introduction Protecting personal and sensitive data, and complying with security and privacy regulations, is high priority for organizations. Inability to protect sensitive user and customer data not only  violates regulations but also leads to loss of reputation and hence loss of current and future customers, along with costs to correct a data breach.  The average…

Ditching the Performance Constraints of Snowflake for a Streaming Data Warehouse

By Nick Alonso | November 25, 2020

Introduction Snowflake just recorded the largest IPO in history – confirming the demand for high-performance data warehousing in the enterprise analytics space. Snowflake’s offering is extremely attractive upfront. It is easy to use with a relatively fast and seamless installation process. On smaller scale traditional OLAP workloads, users experience great performance with a lulling consumption…

The Cloud Data Warehouse Conundrum

By Andrew Wooler | November 19, 2020

As companies like Snowflake have proven, there is strong demand for data warehouses that have been re-architected for the cloud. It’s tough to argue with these cloud data warehouses as  flexible and scalable places to store data. With their ease of use and elasticity, they can also appear cost-effective for traditional SQL use cases.  However,…