MongoDB: Case Study with KPMG

  • NoSQL(Not Only SQL) database

SQL Databases

The idea behind relational relationships is that data is stored in tables, which are organized into columns, and each column stores one type of data with each instance table data in rows.

Growth of NoSQL

NoSQL databases don’t have such structured schema.The Not Only SQL or NoSQL database is an approach that works towards managing data as well as database design which may come in handy for huge sets of distributed data.


MongoDB is a source-available cross-platform document-oriented database program. Classified as a NoSQL database program, MongoDB uses JSON-like documents with optional schemas.

  • Secondary Indexes: Indexes speed up the queries significantly, but they also slow down writes. Secondary indexes are a first-class construct in MongoDB. This makes it easy to index any property of an object stored in MongoDB even if it is nested. This makes it really easy to query from the database based on these secondary indexes.
  • Replication and high availability: MongoDB supports a “single master” model. This means you have a master node and a number of slave nodes. In case the master goes down, one of the slaves is elected as master. This process happens automatically but it usually takes time, before the 3.2 release, 10–40 seconds were taken but after the release of MongoDB 3.2 and later, failures are detected faster and a new leader elected in under 2–10 seconds.

The KPMG story

Data Lake

All raw accounting data from the customers’ business systems, such as sales data, invoices, bank statements, cash transactions, expenses, payroll and so on, is ingested from Microsoft SQL Server into MongoDB. This data is then accessible to the CPAs to generate the customer’s KPIs. A unique capability they have developed for the customers is financial benchmarking. They can use the data in the MongoDB data lake to allow our customers to benchmark their financial performance against competitors operating in the same industries within a specified geographic region.

Metadata Management

Another unique feature of the accounting suite is the ability to customize reporting for each customer, based on specific criteria they want to track. For example, a restaurant chain will be interested in different metrics than a construction company. KPMG enable this customization by creating a unique schema for each customer which is inherited from a standard business application schema, and then written to MongoDB.

Logging Layer

KPMG also use MongoDB to store all the Loop application’s millions of clients requests each day. This enables them to build Tableau reports on top of the logs to troubleshoot production performance issues for each user session, and for each of the 220 regional KPMG sites spread across France.



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