Amazon DynamoDB is a managed NoSQL database in the AWS cloud that delivers a key piece of infrastructure for use cases ranging from mobile application back-ends to ad tech. DynamoDB is optimized for transactional applications that need to read and write individual keys but do not need joins or other…

In this blog I compare options for real-time analytics on DynamoDB — Athena, Spark and Elastic — in terms of ease of setup, maintenance, query capability, latency. There is limited support for SQL analytics with some of these options. I also evaluate which use cases each of them are best…

In this post I explore how to support analytical queries without encountering prohibitive scan costs, by leveraging secondary indexes in DynamoDB. I also evaluate the pros and cons of this approach in contrast to extracting data to another system like Athena, Spark or Elastic. Rockset recently added support for DynamoDB…

This post outlines how to use SQL for querying and joining raw data sets like nested JSON and CSV — for enabling fast, interactive data science. Data scientists and analysts deal with complex data. Much of what they analyze could be third-party data, over which there is little control. In…

When we surveyed the market, we saw the need for a solution that could perform fast SQL queries on fluid JSON data, including arrays and nested objects: Best architecture to convert JSON to SQL? What are the ways to run SQL on JSON data without predefining schemas? I need database…

This post is inspired from a book I read, Naked Statistics and a documentary that I watched, “The Human Face of Big Data”. I recommend the documentary to anyone who wants to know more about what the big fuss is about data and why we care. The book is focused…