NEW YORK, NY and SAN FRANCISCO, CA--(Marketwired - Mar 17, 2015) - (SPARK SUMMIT EAST, 2015) -- MemSQL (www.memsql.com), the leader in real-time databases for transactions and analytics, today announced new geospatial capabilities for its in-memory, distributed, SQL-based database. By bringing together geospatial and operational data in the same high speed database, customers can achieve unprecedented agility for geospatial analysis. Unlike segregated solutions, MemSQL integrates geospatial data as a primary data type, making it as easy to use and operate at scale with as much speed and high throughput as any other class of data.
MemSQL Brings Geospatial Analysis to In-Memory, Distributed Databases - Click to tweet
No more segregation: All data created equal in-memory
Previously, enterprises were forced to segregate their geospatial data into separate data stores. With the rise of IoT and mobility, nearly all data is location-specific. As data volume increases, maintaining geolocation information outside of the primary datastore leads to longer latency and synchronization challenges.
By integrating geospatial functions, MemSQL enables enterprises to achieve greater database efficiency with a single database that is in-memory, linearly scalable and supports the full range of relational SQL and geospatial functions. With MemSQL, geospatial data no longer remains separate and becomes just another data type with lock-free capabilities and powerful manipulation functions.
Geospatial in action: NYC taxi data can drive smarter urban planning
Working with MemSQL and Apache Spark, Esri, the leading provider of geographic information systems (GIS), analyzed data compiled from 170 million real-world NYC taxi rides around the GPS coordinates of pickups and dropoffs, as well as distance and travel time.
Slicing by hour of the day, Esri can calculate the average speed of a taxi ride and find the best and worst places for traffic jams. Slicing by day of the week, the ebb and flow of traffic during workdays and weekends becomes visible. For a city planner, this data insight can be used to redirect traffic at specific times in an effort to unclog traffic congestion. For the taxi business, this data can improve efficiency with supply and demand of cabs during times of high or low traffic for any given region.
"MemSQL is enabling companies to consolidate many niche solutions into fewer, more capable multi-purpose solutions. By making geospatial data a primary part of in-memory, operational databases, our customers can rely on one solution to make their data more valuable," said Eric Frenkiel, MemSQL co-founder and CEO. "We're delivering on our promise of easy access to database innovation and are quickly becoming the go-to-company to help enterprises operationalize analytics."
See it in person at Spark Summit East
MemSQL will showcase the MemSQL, Apache Spark and Esri demonstration at Spark Summit East 2015 on March 18-19, 2015 at The Sheraton New York Times Square Hotel. Visit MemSQL at Booth 13 during show expo hours. More details on the demonstration can be found here: http://www.memsql.com/releases/geospatial-media-alert/.
The early access MemSQL geospatial capabilities are available now and will be generally available in calendar Q2. Read the technical blog post here: http://blog.memsql.com/geospatial-intelligence/.
About MemSQL
MemSQL is the leader in real-time databases for transactions and analytics.
As a purpose built database for instant access to real-time and historical data, MemSQL uses a familiar SQL interface and a horizontally scalable distributed architecture that runs on commodity hardware or in the cloud.
Innovative enterprises use MemSQL to better predict and react to opportunities by extracting previously untapped value in their data to drive new revenue.
MemSQL is proven in production environments across hundreds of nodes in high velocity Big Data environments.
Based in San Francisco, MemSQL is a Y Combinator company funded by prominent investors including Accel Partners, Khosla Ventures, First Round Capital and Data Collective. Follow us @MemSQL or visit at www.memsql.com.