




JD Edwards EnterpriseOne is a modular ERP suite offering financials, manufacturing, supply chain, asset lifecycle and project management for large and mid-sized organizations.
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Makini supports over 2,000 industrial systems across ERP, CMMS, and WMS categories. This includes major platforms like SAP (ECC, S4/HANA, Business One), Oracle NetSuite, Microsoft Dynamics, IBM Maximo, and specialized industrial systems. We support both cloud-based and on-premises installations. If you need to connect to a system we don't currently support, we're committed to building that integration for you at no additional charge—most new integrations are completed within one business day. You can view our full list of supported systems at makini.io/integrations.
Makini's unified API acts as a common denominator across all connected systems. We map each system's data structure to a standardized data model, exposing consistent endpoints regardless of the underlying platform. This means you write the same code to retrieve purchase orders from SAP, NetSuite, or Dynamics—the API calls and response formats are identical. You always get data in the same structure, making it easy to build consistent business logic. The unified approach eliminates the need to learn each system's unique API, manage multiple authentication methods, or handle varying data formats.
Yes, Makini supports both cloud-based and on-premises systems. For on-premises installations, connections require double the connection credits compared to cloud systems. The connection process typically requires opening specific ports and whitelisting Makini's IP addresses in your firewall configuration. For some on-premises systems, VPN tunnels may be necessary. We provide detailed technical requirements during implementation planning. In cases where security policies prohibit external connections, we offer self-hosted deployment options where Makini runs entirely within your infrastructure, eliminating the need for external network access to on-premises systems.
Makini uses cursor-based pagination for retrieving large datasets. API responses include a `next_cursor` field when additional results are available. To retrieve the next page, include the cursor value in your next request: `GET /api/v1/purchase-orders?cursor=CURSOR_VALUE`. Cursor-based pagination is more reliable than offset-based pagination because it handles data changes between requests—if records are added or deleted while you're paginating, you won't miss records or see duplicates. Page size is configurable up to a maximum limit (typically 100-500 records per page depending on entity type). For optimal performance, use the largest page size your application can handle efficiently. The API response also includes total count when available from the source system.
