The Easiest, Fastest Way to Get MongoDB Data Into RDBMS

MongoDB to Postgres, SQL Server, MySQL, Oracle, HPVertica, SQLite

4 Simple Steps To Seeing Your MongoDB Data As Tidy Tables and Rows

Step 1: Simple Setup

MongoSluice streams data from MongoDB to any RDBMS. All you need is a MongoDB instance, MongoSluice — which only requires Java Runtime — and a SQL destination.

Step 2: Configure MongoSluice

MongoSluice make configuration a simple task. From the command line, simply set connection strings for your source and your target. That will take you about two minutes.

Step 3: Run MongoSluice

Type a few lines to execute one of the most powerful tools in Big Data.

Step 4: See your NoSQL as SQL -- and Get to Work

MongoSluice interrogates the data inside your NoSQL store and builds a schema in memory. It then streams the data into a SQL repository. In the end, you get tables and relationships — inside the RDBMS framework of your choice. No more slog. You can now get to work.

Get Faster Results. And Get Better Results.

MongoSluice takes the time-consuming and expensive slog out of working with big data. It figures out what an unstructured or NoSQL database would look like if it were SQL — and then actually turns it into (and streams it to) SQL or any other RDBMs datastore.

This new patent-pending technology exponentially expedites the time it takes to bring big data into business intelligence systems, providing clients with near real-time insight.

MongoSluice to Participate in Phorum Philly 2015

MongoSluice to Participate in Phorum Philly 2015

by | Mar 26, 2015 | Data, News

We are proud to announce that our incubating company MongoSluice, will be included in this year’s Phorum Philly event. MongoSluice streams MongoDB to any RDBMS. Simply point MongoSluice to a MongoDB collection and any RDBMS data store and hit enter: watch data stream...

Sluicing 30 Years of NBA Data

Sluicing 30 Years of NBA Data

by | Jan 14, 2015 | Case Studies

The Source: NBA Game Stats Since 1985-1986 We are always on the look out for complex (nasty!) datasets to sharpen MongoSluice's teeth.  Valeri Karpov (aka The Code Barbarian) created one that suits us well!. It's data from NBA games over 30...