slamdata 3.0 makes live mongodb data display without ETL


Earlier we discussed about availability of slamdata a non-ETL solution to display live data from mongodb. It is interesting to know that slamdata has undergone rapid development over the pat two years and is currently at stable version 3.0
Slamdata makes it possible to display live data from mongodb database without using ETL tool. Hassle of extraction, transformation.loading, ETL mapping is being rid of using slamdata
Here are some interesting features of slamdata 3.0 that makes it a better choice to access live data from mongodb

1) Powerful API’s for developers – Utilizing the API’s charts can be easily embedded into mongodb applications. I remember working on reporting tool with mysql backend, perl libraries to chart the data in front-end. Now, this is a piece of cake utilizing slamdata API’s
2) Easy analytics using API’s – Analytics can be easily embedded into mongodb applications. If you are currently using panda python packages for your predictive analytics, you might be aware of power of analytics in predictive analytics of social media like twitter, facebook, linkedin etc. Try slamdata to easily implement predictive analytics in a mongodb application
3) Brand-new user interface with best look and feel – This is easy to use, brand new, extremely powerful
4) Dashboard types supported – This version supports both static and dynamic dashboard creation. Dashboard is created in user interface
5) Enhanced framework – The framework has become more extensible making ti possible to write connectors for databases beyond mongodb including Couchbase, MarkLogic, postgresql etc
6) Gallery of charts – A detailed roster of charts are supported including basic area, basic line, irregular line, area, line,stacked area, line, bar, scatter, candlestick,pie, radar, chord,fd charts ,maps,eventriver, heatmap,venn,tree,treemap,wordcloud etc
7) Powerful documentation from slamdata makes it the best analytic tool for mongodb

Get MongoDB Articles for FREE:

Delivered by FeedBurner

For storing Bigdata NoSQL databases like mongoDB come handy. These databases can easily store petabytes of data, can be scaled via sharding
Download slamdata 3.0 for free