LakeHold as an Enterprise Data Platform

LakeHold is evolving from a self-hosted lakehouse into a focused Enterprise Data Platform (EDP): one governed place to acquire, store, understand, serve, and operate organisational data. The goal is not to imitate every service in Databricks or Snowflake. It is to give .NET and lean data teams a smaller, private platform with open storage, explicit operations, and an exit path they can prove.

Current boundary: LakeHold already supplies a strong lakehouse. The first managed full-snapshot connector foundation is implemented and verified in source for the next release, but is not included in the current v1.2.0 artifact. LakeHold is not yet a complete EDP. Incremental adapters, searchable governance, end-to-end lineage, a semantic layer, mature BI compatibility, and an adapter ecosystem remain planned work.

What an EDP does

An Enterprise Data Platform normally brings six responsibilities together:

Responsibility	Typical use	LakeHold direction
Acquire	Bring operational, SaaS, file, event, and database data into governed storage	Managed connectors, browser imports, CDC, and future incremental adapters
Store and process	Keep durable analytical data and execute transformations and queries	DuckLake tables, open Parquet, DuckDB compute, snapshots, and saved SQL
Govern	Define ownership, contracts, quality, classification, policy, and lineage	Connector contracts in current source; searchable asset governance and lineage planned
Serve	Make trusted data available to applications, analysts, BI, and AI	HTTP, PostgreSQL wire, EF Core, MCP, and future semantic/open-engine interfaces
Operate	Schedule, observe, recover, optimise, and prove service health	Leases, audit, telemetry, maintenance, backup/restore, and verified eject
Secure	Enforce identity, tenant boundaries, secrets, and controlled egress	Scoped tokens, OIDC, roles, DNS-pinned egress, and external secret providers planned

What LakeHold provides

The distinction below is deliberate: the lakehouse capabilities are available in v1.2.0, while managed connectors are implemented in source for the next release but are not yet in a published artifact.

Available on the main branch: governed lakehouse foundation

PostgreSQL control and DuckLake metadata with DuckDB execution and open Parquet data.
Tenant/catalog identity, scoped API tokens, OIDC, owner/editor/reader roles, and audit history.
Atomic table publication, snapshots and time travel, saved-query publication, maintenance, and multi-node leases.
Backup/restore and signed, row-count-attested eject bundles that prove the exit path.

Implemented in source for the next release: managed ingestion

REST JSON-array and NDJSON full-snapshot connectors.
A small server-streaming gRPC full-snapshot contract.
Durable connector definitions, interval schedules, manual runs, run lineage, safe failure evidence, quality gates, target ownership, and fenced publication.

The managed connector contract and operator settings are documented in CONNECTORS.md.

Available on the main branch: data movement

Browser-local CSV and XLSX imports with bounded, owner-only scratch space.
Typed CDC pull and signed at-least-once webhooks for downstream change consumption.

Available on the main branch: consumption

Browser Workbench, HTTP APIs, MCP resources/tools, EF Core integration, and direct SQL through the PostgreSQL wire endpoint.
psql, DBeaver, and Npgsql work through the wire endpoint. Power BI remains blocked by the documented PostgreSQL type-catalogue compatibility gap.

Typical enterprise uses

Consolidate departmental APIs and extracts into governed analytical tables.
Publish reusable data products with an owner, description, tags, contract, quality evidence, and retained refresh history.
Give applications, analysts, SQL tools, and AI agents access to the same catalog and authorization decisions.
Operate a private lakehouse in a VM, Kubernetes, an air-gapped network, or infrastructure governed by organisational data-residency policy.
Replace opaque warehouse lock-in with open Parquet, ordinary SQL metadata, tested backup/restore, and a signed export path.

What is not complete

LakeHold should not yet be presented as a broad, finished EDP. The following capabilities remain open:

Incremental source checkpoints and resumable database/SaaS connectors.
A versioned adapter SDK, adapter manifest, mappings, transforms, and explicit schema-evolution decisions.
OAuth renewal, mTLS, and an external secret-provider abstraction.
Searchable enterprise catalog, column classification, policy administration, freshness status, and navigable upstream/downstream lineage.
Governed metrics and semantic models.
Power BI compatibility, a supported JDBC/ODBC strategy, and live open-engine access through an Iceberg-compatible catalog.
A connector administration experience in the Workbench.
Connector-specific retry/backoff, service objectives, alerting, and resource/cost reporting.

Delivery plan and status

The status-controlled plan is maintained in ENTERPRISE-DATA-PLATFORM-ROADMAP.md. It separates source implementation from capabilities available in a published release and work that remains unimplemented.