Make your data beautiful again

Smart Matching Technology - Master Data Foundations (MDM)

Multi Platform Support

MonsterDB is built on 100% Java technology, which means that we support any platform that can handle Java 1.8. 

Including Linux (Ubuntu, Suse, RH, Oracle) Windows 7,8, 10, Server – 2008R2, 2012R2 ,2016, 2019) ,Server, Solaris, OSX.


Optimised Queries

We support query optimisation and indexing across multiple data formats and types. This means that the optimiser will pick the best path to evaluate your query based upon the fuzzy and normal indexes available to it.

API Support

The API is based around the MongoDB style of API where each query is not written in SQL but in a document oriented query language. Client and server communication is done using Thrift and this gives us APIs in the following languages:

CPP, C#, JAVA,  CL, D, DART, PHP, PERL, HAXE, plus we will release more in the future.

Source Data Support

To get data in we connect with Relation Technology such as Oracle, MYSQL, or SQLServer using JDBC. Native loaders for CSV and other delimited and flat files. Plus huge (multi-GB) XML file support for loading complex files such as GLEIF.


Fuzzy Matching

Fuzzy matching is at the core of what we do, that is why we built it into the core of the database, so rather than building a fuzzy matching solution around the database like most MDM solutions we built it into the database and storage mechanisms.

Command Line

Command line access to the monsterDB  provides you with access to the entire API and can allow you to query, insert, delete, create and drop databases and collections. Plus it enables you to load data from a multitude of data file types

Cluster Replication

Full support for range based replication that distributes documents across nodes based on value, hash based replication to evenly distribute data or simple replication to keep multiple copies of the database on many nodes.


Quality Analytics

Using monsterDB you can do simple queries to determine the level of matches in your dataset without having to build a MDM schema and solution around it. Simply use the loader and run a query asking the optimiser to estimate the number of tasks you get at each level.

MongoDB-"Like" Pipelines

We support the vast majority of the mongoDB aggregate pipeline in the api and command line, this means that you can query, fuzzy, match, join, filter, project, bucket and export your pipeline output to a new collection. Check out some of the pipeline examples where we analyse data and create tasks.

“monsterDB enables its users to create their own Master Data Management solution without the inherent high cost of current technology solutions”

Register your interest in our Beta Program