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A Unified Data Engineering & Analytics Platform

Your entire data stack.

Model, ingest, transform, orchestrate, analyse and explore in one connected workspace, with catalog, lineage and governance across it.

Nodeberries platform architecture. Sources (databases, warehouses, lakehouses) feed the Build layer, a cluster of data model, ingestion, ETL transformation, analytics and orchestration around the nodeberries core, which serves Explore (semantic catalog, analytics, governance, data chat, AI assistant, lineage).
1Platform architecture: connect your sources, build in one place, explore with governance.
Lifecycle · How the nodes connectsources to decisions: choose a stage

Central catalog with lineage. Certified artifacts and governance.

Introspect an existing database, or create a new one.

  • To start immediately, introspect an existing database.
  • Create a new model from scratch, or edit an existing one.
  • Design using UI or YAML code, or a mix of both.
  • Enrich data model with business or technical metadata.
1n1n1ncustomerssales · 4 colsPKcustomer_ididemailshort_textfull_nameshort_textcreated_attimestamp_tzorderssales · 5 colsPKorder_ididFKcustomer_ididorder_datedatetotal_amountmoneystatusshort_textorder_itemssales · 4 colsPKitem_ididFKorder_ididFKproduct_ididquantityintegerproductssales · 3 colsPKproduct_ididnameshort_textpricemoneymodels/sales/orders.ymlconstraints:- type: foreign_key name: fk_orders_customer columns: [customer_id] references: table: customers columns: [customer_id]