Release 1.3 of GeoMesa has taken some great steps in making GeoMesa an even better analytics platform for Big Spatial Data. Many improvements fall into two categories: support for a wider range of Spark features and improved support for interactive … Read More
When starting a new data science project, one should typically first understand the problem domain, state a hypothesis, and then gather data to prove or disprove said hypothesis. But, if I’m being honest, I usually start with a new data … Read More
Earlier this summer, the CCRi blog entry GeoMesa analytics in a Jupyter notebook introduced the use of Jupyter notebooks with Scala and GeoMesa to do Apache Spark analytics and geospatial visualization. As the blog entry said, it only scratched the … Read More
Well-known GeoMesa use cases often center around its ability to work with large, scalable column-oriented database managers such as Accumulo, HBase, and Google Cloud Bigtable. These systems are well-known for their ability to store very large amounts of data, and … Read More
Release 1.2 of GeoMesa, our open source suite of geospatial analytics tools designed to run with Hadoop-scale volumes of data, is now out. Along with several new features, this is the first release after a thorough review by the Eclipse … Read More
Despite all the buzz that surrounds the term “big data,” we hear surprisingly little about “big spatial data.” Of the top ten results from an Incognito Google search for “Big Spatial Data,” only two results are from 2015 and only … Read More
CCRi in collaboration with Google, Inc., has announced the initial release of GeoMesa for Google Cloud Bigtable. GeoMesa is an open-source system that quickly stores, indexes, and queries hundreds of billions of geospatial features in a distributed (i.e. cloud) database. … Read More
[Editor’s note: This article first appeared in the March 2014 LocationTech newsletter.] GeoMesa is an open-source, LocationTech project that manages big geo-time data within the Accumulo key-value data store so that those data can be indexed and queried at scale … Read More
CCRi was delighted to host the second meeting of the Cville Data Science group earlier this month. A full house packed our conference room, and a good time was had by all. The lineup for the talks included three CCRi … Read More
When building web based data visualization applications, you usually want to defer rendering and styling to as late as possible in the request lifecycle. This gives your users the most flexibility when composing and customizing intelligent visualizations of data. For … Read More