SlamData 2.1.9 release: SQL, analytics, & visualizations on MongoDB

[John De Goes]

Hi folks,

I'm a contributor to SlamData, an Apache 2-licensed open source analytics platform that's tailored for MongoDB.

SlamData lets you answer questions on your data, visualize your data, and create interactive reports and dashboards that run live off MongoDB.

We just released 2.1.9, which may interest some users in this group:

• Download 2.1.9
• Getting Started Guide
• SlamData User Manual
• SlamData User Group
• Github Open Source Repositories
• Atlassian JIRA bug tracker
• JDBC Driver
• Gitter Chat Room

SlamData is powered by SQL^2, which is ordinary SQL with extensions for dealing with subdocuments and arrays.

SlamData converts SQL queries to one or more MongoDB queries, and is guaranteed to execute every query 100% in-database.

For example, the following SQL query:

select value * volume as product, symbol from "/db/stocks" where symbol in ('AAPL', 'GOOG') and product > 100

...is converted to the following aggregation framework query:

db.stocks.aggregate(
  [
    {
      "$match": {
        "$and": [
          { "symbol": { "$in": ["AAPL", "GOOG"] } },
          { "product": { "$gt": NumberLong(100) } }]
      }
    },
    {
      "$project": {
        "product": { "$multiply": ["$value", "$volume"] },
        "symbol": "$symbol",
        "_id": false
      }
    }]);

Notice that $match is the first operation in the pipeline and both predicates in the WHERE clause are pulled to the front of the pipeline, to take advantage of indexes that may exist on the fields symbol and product.

See SlamData in action at http://slamdata.com. I'm happy to hear your feedback and answer any questions you might have.

Note: We are actively looking for more contributors to the open source project. If you are a Java or Scala developer, and would like to contribute to the project, please see the Github repository and the JIRA instance. You can chat with other contributors to the project on Gitter.

Regards,

John