1.1. What is GeoMesa?¶
GeoMesa is an Apache licensed open source suite of tools that enables large-scale geospatial analytics on cloud and distributed computing systems, letting you manage and analyze the huge spatio-temporal datasets that IoT, social media, tracking, and mobile phone applications seek to take advantage of today.
GeoMesa does this by providing spatio-temporal data persistence on top of the Accumulo, HBase, and Cassandra distributed column-oriented databases for massive storage of point, line, and polygon data. It allows rapid access to this data via queries that take full advantage of geographical properties to specify distance and area. GeoMesa also provides support for near real time stream processing of spatio-temporal data by layering spatial semantics on top of the Apache Kafka messaging system.
Through a geographical information server such as GeoServer, GeoMesa facilitates integration with a wide range of existing mapping clients by enabling access to its databases and streaming capabilities over standard OGC (Open Geospatial Consortium) APIs and protocols such as WFS and WMS. These interfaces also let GeoMesa drive map user interfaces and serve up data for analytics such as queries, histograms, heat maps, and time series analyses.
GeoMesa features include the ability to:
- Store gigabytes to petabytes of spatial data (tens of billions of points or more)
- Serve up tens of millions of points in seconds
- Ingest data faster than 10,000 records per second per node
- Scale horizontally easily (add more servers to add more capacity)
- Support Spark analytics
- Drive a map through GeoServer or other OGC Clients
There are many reasons that GeoMesa can provide the best solution to your spatio-temporal database needs:
- You have Big Spatial Data sets and are reaching performance limitations of relational database systems. Perhaps you are looking at sharding strategies and wondering if now is the time to look for a new storage solution.
- You have very high-velocity data and need high read and write speeds.
- Your analytics operate in the cloud, perhaps using Spark, and you want to enable spatial analytics.
- You are looking for a supported, open-source alternative to expensive proprietary solutions.
- You are looking for a Platform as a Service (PaaS) database where you can store Big Spatial Data.
- You want to filter data using the rich Common Query Language (CQL) defined by the OGC.
1.2. Community and Support¶
The GeoMesa website may be found at http://www.geomesa.org/. For additional information, see:
- The tutorials on the main GeoMesa website: http://www.geomesa.org/tutorials/
- The GeoMesa FAQ: http://www.geomesa.org/faq/
- The GeoMesa Users (https://locationtech.org/mhonarc/lists/geomesa-users/) and Dev (https://locationtech.org/mhonarc/lists/geomesa-dev/) mailing list archives
README.mdfiles provided under most modules
- The chat at https://gitter.im/locationtech/geomesa/.
GeoMesa is a member of the LocationTech working group of the Eclipse Foundation.