Affordable Big Data
Low IO requirements, efficient usage of disk space, low memory footprint.
Low IO requirements, efficient usage of disk space, low memory footprint.
Snappy achieves compression rates up to 5 times increasing disk IO efficiency and saving storage cost.
“Write once – read many”, one batch of data is an atomic write with the instant rollback, replacement or combination possibility and delivery versioning included.
Schema flexibility for rapid application development.
For batch processing, aggregation and indexing of your data. Example: jumboDB allows writes up to 500.000 JSON documents per second on a single AWS m1.xlarge instance (document size being 420 bytes).
Optimized querying even for large result sets through multithreading and efficient data streaming. Example: 100.000 JSON documents returned in less than a second on a single m1.xlarge AWS instance.
Easy to integrate into any JVM based application.
Dedicated to cost efficient Big Data.
Working on Big Data projects with Telefonica Digital, Carsten Hufe and the Comsysto Reply Team started looking for an efficient and affordable way to store and query large amounts of data being delivered in large batches through Apache Hadoop. Our goal was to build a data visualization app for end users issuing different kinds of selective queries on already processed data. Some of the queries were returning large result sets of up to 800.000 JSON documents representing data points for browser visualisation.
We faced three major challenges:Do with jumboDB:
Don’t:
About TDI
Telefónica Dynamic Insights provide near real-time data, collected 24 hours a day, 7 days a week, 365 days a year and present it through simple web interfaces to enable visualisation and understanding. We fuse this data with the best consumer preference, attitude and behavioural insight through our global partnership with GfK. Find out more about TDI.
About Comsysto Reply
Comsysto Reply is a Munich-based software company specialized in lean business and technology development. While supporting all three steps of a well known Build-Measure-Learn lean feedback loop, Comsysto Reply focuses on open source frameworks and software as major enablers of short, agile Build-Measure-Learn iterations and fast gains in validated learning. Powerful MongoDB technology provides the needed flexibility and agility for turning ideas into products as well as performance for handling Big Data while turning data into knowledge. We also enjoy developing with Spring framework and its subprojects, Apache Wicket, Gradle, Git, Oracle DB and Oracle BI. Comsysto Reply is dedicated to eliminating waste in both business and technology since 2005. Find out more about Comsysto Reply.