Unified Data Intelligence for Your ERP Ecosystem
Odoo DataLake consolidates and continuously synchronizes data from across your Odoo instance, including multiple instances spanning versions V15 through V19, into a single clean, JSON-formatted layer on your own infrastructure. It decouples analytical workloads from your live ERP so heavy queries never slow down day-to-day operations, and feeds BI dashboards, enterprise search, and RAG pipelines from one consistent source.
FAQ
Fragmented ERP Data
Odoo's modular design distributes critical business data across 200+ models with varying schemas, relationships, and access patterns.
What should be a single analytical query becomes a programmatic orchestration problem.
Data structures don't map cleanly between V15 through V19 instances.
Duplicated integration effort introduces maintenance debt.
Large-scale extraction degrades operational performance.
Consolidated Data Container
An extraction-normalization-persistence layer that decouples analytical workloads from operational systems.
Incremental extraction using write_date field for change detection.
Consistent output schemas regardless of source Odoo version.
Organized by model and extraction timestamp with compression.
Discover available data assets and detect schema evolution.
Consolidate operational data into one addressable location. Data consistency is enforced at extraction time.
JSON output with predictable schemas. Relational references resolve to embedded objects.
Heavy analytical queries execute without impacting Odoo ERP responsiveness.
Consistent output schemas regardless of source version (V15 through V19).
Integration points decrease from N×M to N+M.
Extraction runs during off-peak windows.
JSON stores replicate independently of Odoo backups.
Clean JSON serves as direct input for ML pipelines.
SQL-compatible query engines operate directly on JSON.
Immutable snapshots provide audit trails.
Configure extraction scope from individual models to complete database mirrors. Pattern matching for module-specific extraction.
Change detection minimizes extraction overhead. Failed runs resume from last successful batch.
Automatic schema detection and validation. Breaking changes trigger alerts.
Aggregate from multiple Odoo instances with instance tagging for filtered querying.
Export hooks feed vector embedding services. Parquet and JSONL output formats.
RESTful and GraphQL interfaces. Webhook notifications on extraction completion.
Connect SQL-compatible analytics platforms directly to normalized JSON through query engines like DuckDB, Trino, or Presto. Build cross-functional dashboards combining sales, inventory, accounting, and manufacturing data without Odoo query complexity. Visualization platforms including Metabase, Superset, and PowerBI integrate without custom connectors.
Index normalized records into full-text search engines such as Elasticsearch, OpenSearch, or Meilisearch. Enable organization-wide ERP content search spanning partners, products, orders, documents, and communications. Faceted search filters by model type, date ranges, company, and custom field values.
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Vectorize normalized content for Retrieval-Augmented Generation systems using vector stores like pgvector, Pinecone, or Qdrant. Enable natural language queries against ERP data. LLM responses from Claude, GPT-4, or local models ground in actual business data with source attribution.
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Feed enterprise data warehouses from normalized JSON exports through orchestration platforms like Airflow, Dagster, or Prefect. Data engineering teams consume cleaned Odoo data without Odoo-specific extraction logic. Destination warehouses including Snowflake, BigQuery, and Redshift receive consistent, typed data.
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Multiple Odoo instances (V15-V19) with independent databases.
RPC client pool with incremental sync and error recovery.
Field resolution, relation flattening, version mapping.
Model-organized collections with versioned snapshots.
Cron-based, webhook-triggered, or manual.
Change detection and batch fetching.
Field values, relational references, type standardization.
Write documents, update catalog, compress.
| Component | Requirement |
|---|---|
| Odoo Connectivity | XML-RPC or JSON-RPC access |
| Supported Versions | V15, V16, V17, V18, V19 |
| Storage Backend | Local, S3, Azure Blob |
| Scheduling | Cron, webhook, manual |
| Resources | 2GB RAM minimum |
Extract res.partner, res.company, res.users.
Add sales, purchase, accounting models.
Connect BI and search infrastructure.
Implement vectorization and RAG interface.
Transform fragmented ERP data into unified business intelligence.
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