Use cases

Start a model
from scratch
Reverse-engineer
an existing instance
Data governance and
regulatory compliance
Migrate from SQL
and denormalize

Start a model from scratch

Dynamically generate forward-engineering scripts and documentation with just a few mouse clicks

When starting a new project, the database model is at the core of your application. With Hackolade, you can get started in no time! With just a few mouse clicks, you generate sample documents, MongoDB or DynamoDB scripts, and HTML or PDF documentation. In an Agile approach, you can engage in a meaningful dialog between analysts, designers, architects, developers and DBAs, playing what-if scenarios. It reduces development costs and increases your chances to deliver an evolving application that responds to your customer’s needs.

How-to video Online documentation

Reverse-engineer an existing instance

Further enrich the model with relationships, descriptions and constraints, then generate PDF or HTML documentation

If you have a running NoSQL instance, you may want to document the data model, share it, and discuss its evolution with application stakeholders who would prefer not looking at code. In just a few mouse clicks, you connect to the instance, select the collections you want, and your base model is created. Our machine-based data discovery and cataloging process includes statistical sampling of documents, followed by a probabilistic inference of the schema.

You can print pretty ER diagrams and tree views of your collection schemas, or distribute HTML or PDF documentation so users easily understand the structure of the data. You may also enrich the model with descriptions, constraints, and comments

How-to video Online documentation

Data governance and regulatory compliance

Automated data discovery in an agile world

With its Command Line Interface (CLI), Hackolade truly supports an agile development approach leveraging the flexibility of NoSQL dynamic schemas. Some Hackolade customers use this capability nightly in a batch process to identify attributes and structures that may have appeared in the data since the previous run.

During a nightly batch of the reverse-engineering function, a much larger dataset can be queried as a basis for document sampling, hence making schema inference more precise.

Such capability can be useful in a data governance context to properly document the semantics and publish a thorough data dictionary for end users. It can also be used in the context of compliance with privacy laws to make sure that the company does not store data that it is not supposed to store.

Online documentation

Suggest denormalization of SQL schema

Based on a relational model, Hackolade can easily reference, embed, and denormalize

Migration from SQL to NoSQL requires a mind shift, and Hacklolade can help in the migration of a schema from a normalized relational model to a model combining embedding and referencing. You generate a Data Definition Language (DDL) file from Oracle, Microsoft SQL Server, MySQL, PostgreSQL, Hadoop Hive, or Sybase. You then reverse-engineer it with Hackolade and generate a relational model of the schema.

Then select an least 2 tables to which denormalization should be applied, choose 2-way referencing or the type of embedding (sub-document in child, array in parent, or both) and the number of cascading levels that should be applied.

You now have a denormalized schema, along with its documentation and forward-engineering scripts.

How-to video Online documentation