It's end of term time again. As part of making The Morning Paper habit sustainable I take a few weeks off three times a year to do some more relaxed background reading, recharge my paper queues, and let my mind wander. The Morning Paper will return on Monday 7th August. Here are a few selections … Continue reading End of term, and Orders of Magnitude
Month: July 2017
Do we need specialized graph databases? Benchmarking real-time social networking applications
Do we need specialized graph databases? Benchmarking real-time social networking applications Pacaci et al., GRADES'17 Today's paper comes from the GRADES workshop co-located with SIGMOD. The authors take an established graph data management system benchmark suite (LDBC) and run it across a variety of graph and relational stores. The findings make for very interesting reading, … Continue reading Do we need specialized graph databases? Benchmarking real-time social networking applications
Using word embedding to enable semantic queries on relational databases
Using word embedding to enable semantic queries in relational databases Bordawekar and Shmeuli, DEEM'17 As I'm sure some of you have figured out, I've started to work through a collection of papers from SIGMOD'17. Strictly speaking, this paper comes from the DEEM workshop held in conjunction with SIGMOD, but it sparked my imagination and I … Continue reading Using word embedding to enable semantic queries on relational databases
Blockbench: a framework for analyzing private blockchains
Blockbench: a framework for analyzing private blockchains Dinh et al., SIGMOD'17 Here's a paper which delivers way more than you might expect from the title alone. First we get a good discussion of private blockchains and why interest in them is growing rapidly. Then the authors analyse the core layers in a private blockchain, and … Continue reading Blockbench: a framework for analyzing private blockchains
Azure Data Lake Store: a hyperscale distributed file service for big data analytics
Azure data lake store: a hyperscale distributed file service for big data analytics Douceur et al., SIGMOD'17 Today's paper takes us inside Microsoft Azure's distributed file service called the Azure Data Lake Store (ADLS). ADLS is the successor to an internal file system called Cosmos, and marries Cosmos semantics with HDFS, supporting both Cosmos and … Continue reading Azure Data Lake Store: a hyperscale distributed file service for big data analytics
Spanner: becoming a SQL system
Spanner: becoming a SQL system Bacon et al., SIGMOD'17 This week we'll start digging into some of the papers from SIGMOD'17. First up is a terrific 'update' paper on Google's Spanner which brings the story up to date in the five years since the original OSDI'12 paper. ... in many ways, today's Spanner is very … Continue reading Spanner: becoming a SQL system
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