Eventual Consistency will ruin your graphs, eventually, a talk by Dr Jim Webber (Neo4j)
Abstract
Graph data has made a huge impact in computing systems, and network science is the new wave of data science. But many databases we might use to store and query graphs were not designed with this use-case in mind and struggle with correctness. Given the importance of connected data to the modern world, we should understand the dependability qualities of so-called non-native graph databases so that we can be aware of when our tools produce garbage, often without warning or detection.
This talk will present early results from an investigation into eventually consistent graph databases. It will informally explain the domain, typical database designs, and present a probabilistic model for reasoning about eventual corruption in graph data under no-fault operation. What’s more alarming is that the time to garbage is low, such that it impacts any reasonable production database.
Our early results suggest that eventual consistency is not strong enough to support dependable graph databases and that users should be cautious about the quality of their graph data.
No charge is made to attend meetings; non-IMA members are welcome.
Image credit: The Twingl Mind by Andy Wilkinson / Flickr / CC BY-SA 2.0
