GeoMesa is an open-source, distributed, spatio-temporal database built on a number of distributed cloud data storage systems, including Accumulo, HBase, Cassandra, and Kafka. Leveraging a highly parallelized indexing strategy, GeoMesa aims to provide as much of the spatial querying and data manipulation to Accumulo as PostGIS does to Postgres.
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Through GeoServer, GeoMesa facilitates integration with a wide range of existing mapping clients over standard OGC (Open Geospatial Consortium) APIs and protocols such as WFS and WMS. GeoMesa supports Apache Spark for custom distributed geospatial analytics.
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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 is an open-source, distributed, spatio-temporal database built on a number of distributed cloud data storage systems, including Accumulo, HBase, Cassandra, and Kafka. Leveraging a highly parallelized indexing strategy, GeoMesa aims to provide as much of the spatial querying and data manipulation to Accumulo as PostGIS does to Postgres.

GeoMesa - Suite of tools for working with big geo-spatial data in a distributed fashion

Atlas was developed by Netflix to manage dimensional time series data for near real-time operational insight. Atlas features in-memory data storage, allowing it to gather and report very large numbers of metrics, very quickly. Atlas captures operational intelligence. Whereas business intelligence is data gathered for analyzing trends over time, operational intelligence provides a picture of what is currently happening within a system.

Atlas - In-memory dimensional time series database

FlockDB is much simpler than other graph databases such as neo4j because it tries to solve fewer problems. It scales horizontally and is designed for on-line, low-latency, high throughput environments such as web-sites. Twitter uses FlockDB to store social graphs (who follows whom, who blocks whom) and secondary indices. As of April 2010, the Twitter FlockDB cluster stores 13+ billion edges and sustains peak traffic of 20k writes/second and 100k reads/second.

FlockDB - A distributed, fault-tolerant graph database from Twitter

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GeoMesa - Suite of tools for working with big geo-spatial data in a distributed fashion

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GeoMesa - Suite of tools for working with big geo-spatial data in a distributed fashion

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FlockDB - A distributed, fault-tolerant graph database from Twitter

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