METL's value proposition to ETL is similar to Low Code programming tools. Our design wizards guide users by extracting schema information to populate a data dictionary style repository. The data dictionary is extended with simple tags to implement all types of ETL functionality like data cleansing, validation, data transformations etc. METL's customizable intelligent rules engine implements the ETL from the metadata.

The declarative programming paradigm is an extremely popular methodology to simplify and automate all types of  technologies. It's main goal is to separate the business requirements of an application (what needs to be done) from it's technical implementation. METL has separated it's metadata into two categories. The data dictionary to support the business requirements and additional metadata to implement various data architectures.

Managing data is inherently more cost effective than managing custom programming code. We maintain the data dictionary in a metadata database. This metadata is a combination of the data model, schema and ETL requirements. Using our declarative ETL we are able to keep the data dictionary simple. We support ad hoc SQL for mass updates to the metadata. The metadata can also be managed as a master data management solution, something we call Master Schema Management. This allows application developers to synchronize with data integration. There are countless value propositions to data managed ETL.

Since we're data managed with metadata you can choose between a design time ETL designer wizards or a dynamically managed, rules based ETL server. These concepts work well together. Start with you initial design, then as new schema changes occur at the source they can be automatically added to the data dictionary. Schema changes can also be applied to the destination.

Our foundation is a Java platform with rules classes and a workflow to implement ETL. These are preconfigured for you. You choose one for your use case. Example include NoSQL to SQL, data warehousing, dimensional modeling, Salesforce etc. The metadata completes the ETL configuration. The platform supplies a multi-threaded ETL engine plus management of metadata, job/batch, schema, errors and cache. Our Java technology can leverage nearly any Java library to connect to almost any data connection.