Connect to the databases you already have
Relational, document, cloud, big data and mainframe. Each source connects once and becomes available to the platform's four capabilities.
Supported engines
Relational, document, cloud, big data, mainframe and SaaS.
| Engine | Type |
|---|---|
| PostgreSQL | Open source |
| MySQL | Open source |
| MariaDB | Open source |
| MongoDB | Open source |
| Azure DB | Cloud |
| Firebase | Cloud |
| DynamoDB | Cloud |
| Amazon DB | Cloud |
| Oracle | Commercial |
| SQL Server | Commercial |
| Engine | Type |
|---|---|
| Sybase | Commercial |
| Hadoop | Big data |
| Cassandra | Big data |
| HBase | Big data |
| Neo4j | Big data |
| CouchDB | Big data |
| DB2 zOS | Mainframe |
| DB2 iSeries | Mainframe |
| Salesforce | SaaS |
Licensing models → · Don't see your engine? Tell us which one →
One connection per source, configured once
The source, through a tap
Each database connects as a tap. From there the schema is read and a limited sample is analyzed, within the scope you define.
The processing, in your infrastructure
Analysis and transformations run inside your perimeter, with SSH tunnels and encrypted protocols to connect.
The destination, independent of the source
Datasets are loaded into the configured destination databases or downloaded as SQL, JSON or CSV.
Questions about connecting
What is a tap?
A tap is the inbound connection to a data source. From it, Gigantics imports the metadata and analyzes the schema to classify personal information.
Can I deliver the data to a different engine than the source?
Destinations (sinks) are configured independently from the source, and the dataset can also be downloaded as SQL, JSON or CSV. Tell us your specific combination and we will confirm how it fits.
My database is not on the list?
Write to us with the engine and version. Architectures with mixed sources or unlisted engines are assessed in each proposal.
Does your architecture fit?
We confirm it in a technical session on your own engines.