Using Big Data to Drive a True Customer 360

In this webinar, MemSQL Product Marketing Manager Mike Boyarski describes the growth in popularity of time series data and talks about the best options for a time series database, including a live Q&A. You can view the webinar and download the slides here. Here at MemSQL, we’ve had a lot of interest in our blog posts on time series data and choosing a time series database, as well as our O’Reilly time series ebook download. However, this webinar does a particularly good job of explaining what you would want in a time series database, and how that fits with MemSQL. We encourage you to read this blog post, then view the webinar.

Denodo DataFest, the premier agile data management and analytics conference, returned once again to New York and London in 2018. Our annual user conference brings together industry analysts, subject matter experts, business leaders, data management leaders to discuss data strategies to enable a successful journey to the cloud, self-service BI, and data lakes with data virtualization. The event invited attendees to watch demos, hear customer success stories, and educate themselves on the best practice implementations of data virtualization.

It can be difficult to scale out relational databases and provide more schema flexibility, thus the rise of NoSQL. However, you shouldn’t have to sacrifice data integrity and transactions in order to scale out on commodity hardware and support semi-structured data. By using an RDBMS with built-in sharding and JSON support, you don’t have to. You get the scalability and flexibility of a NoSQL database along with the consistency and reliability of a relational database – and the ability to mix and match relational and JSON data. In this webinar, we’ll explain how MariaDB Platform can be deployed as a NoSQL database by using the Spider storage engine and built-in SQL functions for JSON. In addition, we’ll discuss how you can access relational data as JSON documents, and how to enforce data integrity if a relational data model is extended with JSON

Data democratization is tough for even the most established enterprises. Now imagine how difficult it is for an organization working to eliminate the connectivity and data access barriers that hold economies and communities back.