Quickstep is now part of Pivotal

In January, my students and I spun out a company to help commercialize the technology produced in the Quickstep project. I'm excited to announce that we have now been acquired by Pivotal. More details are here and here.

Comments

Post a Comment

Popular posts from this blog

WideTable: An Accelerator for Analytic Data Processing

Image
Last year, I told you about BitWeaving , which is a compressed columnar scan that exploits intra-cycle parallelism. With BitWeaving, you can scan a table ... pretty darn fast! As part of the Quickstep project, Yinan and I have been wondering if we could expand the "sweet spot'' of the bare metal performance of BitWeaving to a wider variety of analytical query processing. The answer that we have come up with is called WideTable . The key idea behind WideTable is to denormalize the data into a wide table , and then run complex analytic SQL queries (e.g. with joins and nested subqueries) on the WideTable using BitWeaved scans. There are a number of different ways to use a WideTable, including as a materialized view and as an accelerator. Below, we show the how WideTable can be used as an accelerator. The WideTable component plugs in as a front-end to a traditional SQL engine, which could be a traditional SQL RDBMS system (like Oracle) or a Hadoop/SQL engine (li...
Read more

Graph Analytics: Simpler than we think?

Image
Graph analytics are all the rage today with companies rushing to build new software platforms that target just graph analytics all the time. But, are they really that different than many types of iterative data processing? Here we argue that for iterative graph processing, it is not. In fact, one can map BSP-style computation to the good-old relational algebra, with a few extensions for user-defined functions and the ability to express a loop. How can this be done? Consider the common BSP style vertex-centric computation.  The canonical graph analytics computation loop looks like this:   We can map this generic BSP computation to relational algebra using the following recipe. First, store the graph data in two relational tables, a nodes table (with one tuple for each node), and an edges table (with one edge tuple for each edge in the graph). Then, use the table below to map the BSP computation to relational algebra. Essentially in the relational syst...
Read more