And We’re Live…
MongoSluice is a new software tool we developed that makes it easy and fast to stream data between MongoDB and traditional relational database systems. The tool solves the problems most enterprise developers face: how to pull insight from giant datasets stored in Mongo quickly and reliably — without building disposable one-off solutions.
- Developed entirely in Scala, the solution is fully cross-platform and executable on Linux, Windows, and MacOSX.
- Ensures full data fidelity between platforms, all data type information is preserved.
- No data is landed to disk during processing, all data is streamed directly from source to target.
- Simple Command-line API, easy to incorporate into a batch process. In addition to MongoDB and RDBMS connectivity, it only requires only a JVM and a single jar to run.
- Dynamic schema generation: MongoSluice analyzes MongoDB source data along with it’s BSON data types and generates a corresponding strongly typed RDBMS schema, simply point MongoSluice to the MongoDB collection you wish to export, and point to a source RDBMS, and MongoSluice will do all the work! MongoSluice can even account for schema inconsistencies between documents, all data will be accounted for and exported. Mongosluice also has an optional feature which can resize and pad RDBMS String columns once they are extracted from MongoDB.
- Mongosluice will maintain the relational integrity of nested MongoDB data, such as nested Mongo objects and arrays – Is compatible with all RDBMS systems with a JDBC drivers, this includes MySQL, MariaDB, Oracle, SQL Server, Netezza, and Postgres.
- Upcoming feature enhancements include a programmatic API to define complex extraction processes, and a concurrency framework for increased speed and efficiency of exporting. This will allow the end user to build complex nested structures using database queries and export those structures directly into MongoDB.
The Source: Business Service Providers It is an impressive feat for MongoSluice to be able to produce multiple tables that are linked together by foreign and primary keys. But can MongoSluice perform the same when data begins to get more complex? The answer is YES! ...read more
The Source: Movie Data Since 1951 Movies are cool, but this dataset was nasty: arrays, nested documents, and lots of different fields. Normally, this would be a nightmare to do any useful SQL type analysis on. However, MongoSluice bridges the gap by pushing it to...read more
Finally, the tool you’re looking for to get not only faster results, but better results! MongoDB to RDBMS – Postgres, SQL Server, MySQL, Oracle, HPVertica, SQLite…read more