DSE Graph Partitioning Part 1: Custom Vertex Ids
DSE Graph is a distributed property graph database that uses Apache Cassandra for storage, DSE Search for full text and geospatial search, and DSE Analytics for analytical graph processing. This series of blog posts will dive into the graph partitioning capabilities of DSE Graph, discussing how they work and when they may be helpful to you.
DSE Graph is a distributed property graph database that uses Apache Cassandra for storage, DSE Search for full text and geospatial search, and DSE Analytics for analytical graph processing. This series of blog posts will dive into the graph partitioning capabilities of DSE Graph, discussing how they work and when they may be helpful to you.read more
As Agile principles and Lean methodologies continue to take center stage in product management and strategy, it’s easy to get caught up in daily scrums and design iterations and shoot right past the user research (UR). Everything’s moving so fast and we’re seeing big improvements (we think) on a daily basis. Surely user research isn’t as important as full-steam-ahead? Wrong!read more
Watch Expero Sr. Architect Dave Bechberger use Google gRPC and Apache Cassandra to create a high-performance data pipeline for storing time series data that comes from IoT-style applications.read more
Most stream processing frameworks require that you have processing infrastructure available or require the use of a 3rd party service in order to accomplish your stream processing. The overhead associated with these sorts of solutions, either the operational effort required for the infrastructure or direct cost, can sometimes be prohibitive to getting a project off the ground. Kafka Streams has taken a different approach and does not require any external infrastructure beyond Kafka. Instead of relying on this external infrastructure, Kafka Streams integrates into your project as a normal library. This approach minimizes the upfront cost and reduces the adoption penalty (i.e. it’s easy to use for just one project) but it does come with some trade-offs.read more
Graph Database Shootout 2.0 slide deck from DataDay Seattle. Given by Josh Perryman on July 23. 2016. After a quick review of the original Graph Database shootout presentation given in Austin earlier in the year, I turn attention to two popular graph database engines: Neo4j and DataStax’s DSE Graph. I look at the features added for each in the past 6 months, and walk through basic data load and query writing use cases.read more