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All things data

How to Integrate MongoDB with Relational Databases

How to Integrate MongoDB with Relational Databases

Integrating data from MongoDB and a relational database sounds like a major headache. On one hand you have a schemaless NoSQL database containing JSON objects, and on the other, an SQL database with a fully defined schema. How can you easily integrate them? With Xplenty’s data integration on the cloud, of course!

Data Integration on the Cloud with Heroku PostgreSQL and Xplenty

Data Integration on the Cloud with Heroku PostgreSQL and Xplenty

What can you do with data collected on Heroku PostgreSQL? How will you analyze it and integrate it? With Xplenty, of course! Xplenty lets you connect to a PostgreSQL database on Heroku, design a dataflow via an intuitive user interface, aggregate the data, and even save it back to PostgreSQL on Heroku or other databases and cloud storage services.

8 SQL-on-Hadoop Challenges

8 SQL-on-Hadoop Challenges

Introducing Apache Hadoop to the organization can be difficult - everyone is trained and experienced in the old ways of SQL and all the analytics tools integrate with SQL. Certain technologies can help make the transition to Hadoop easier by providing support for SQL on Hadoop.

Integrating Relational Databases with Apache Hadoop

Integrating Relational Databases with Apache Hadoop

Relational databases are here to stay - they are common, integrate with other information systems, do a good job of querying structured data, and people know how to use them. Some believe that adding Apache Hadoop to the organization means death to the good old RDBMS, but that is far from true.