MongoDB vendor 10gen has enhanced its Hadoop connector to make it easier for enterprises to incorporate its database into their Big Data environments. The refreshed connector masks the platform as a Hadoop-compatible file system so that real time data can be read and processed using native MapReduce jobs.

Results can also be written back to MongoDB, which means that users are now able to leverage the database for Hadoop-based data warehouses, ETL workflows and near real time processes that serve large volumes of dynamic data. Other improvements include support for MongoDB BSON (Binary JSON) backup files in HDFS, a feature that increases performance by reducing data movement between Hadoop, local file systems and and cloud-based solutions such as Amazon S3. Users can retrieve these BSON files using SQL-like queries from Apache Hive, which was not supported prior to the update.

“We are seeing strong market adoption of MongoDB for real-time operational big data and Hadoop for deep, offline analytics. The community has been asking us to make these tools interoperate seamlessly, so they can focus on building value in their applications,” stated Max Schireson, the chief executive officer of 10gen. “The latest upgrades to the MongoDB Connector for Hadoop provide this interoperability.”

The changes expand 10gen’s rapidly growing ecosystem, which includes dozens of big wig clients such as MetLife, Goldman Sachs and Parse, a cross-platform mobile development firm that was recently acquired by Facebook for an estimated $85 million.

MongoDB also caught the attention of big name vendors such as IBM, which is currently collaborating with 10gen to create a new mobile standard for enterprises. Once complete, the framework will empower corporate developers to integrate mobile apps with their organizations’ backend environments.