The infor m3 data extraction tool that ships pre-built support for every MMS/CMS/CRS/OOL/MMO/MITMAS table family plus full ION Connect API coverage. Parallel jobs, OAuth2 + read-only JDBC, modified-since deltas, audit-signed manifests. Source-of-truth extraction for migration, archival and analytics.
M3 BE schemas run to thousands of tables. ION BODs come with their own quirks. Multi-CONO joining is non-trivial. Multi-language fan-outs trip up junior developers. An infor m3 data extraction tool that ships pre-built coverage saves the team three months of bespoke development before the first row is even staged.
Most M3 customers run between 5,000 and 12,000 active tables across the BE schema, with non-obvious foreign-key relationships, undocumented audit columns, multi-CONO/DIVI joining rules and multi-language fan-outs that turn what looks like a simple item-master extract into a multi-table join across MITMAS, MITBAL, MITWHL, MITALO, CMS-style description tables and CRS-style classification tables.
Custom JDBC clients always start with an item-master query and finish with a 4,000-line tangled mess that nobody on the team can debug. Syntra ETL's infor m3 data extraction tool replaces that with pre-built support for the canonical prefix families (MMS, CMS, CRS, OOL, MMO, MITMAS), every documented join pattern, every audit-column convention, every multi-CONO scenario. The extractor is the product, not the script.
The same engine handles three modes: full historical extract for one-time migration, delta extract on a schedule (hourly, daily, weekly) for parallel-run and ongoing analytics, and event-driven extract triggered by ION publish-events for near-real-time downstream integration. Every mode produces the same hash-signed manifests and the same SOC 2-grade audit trail.
No more bespoke SQL hunting through Infor KB articles. Just configure scope, run, reconcile.
GL postings with full voucher chain (FGL001/FGL010), AP open and history (FAP110/APS series), AR open and history (FSL/ARS series), fixed assets (FAS), inter-company (CRS165) — multi-CONO aware.
Item master (MITMAS) with extensions, warehouse balances (MITWHL), location balances (MITBAL), lot/serial detail (MITLOC), allocations (MITALO), classification (MITCLS). Multi-language descriptions preserved.
Manufacturing orders (MMO), work orders (MWO), BOMs (MBM), routings (MRT), shop floor reporting (MWS), quality (QMS). Lot/serial genealogy preserved end-to-end for FDA Part 11.
Purchase orders (MPL), supplier master (CIDMAS), agreements (PPS), receipts (MGRECP), invoice match history. Trading-partner context preserved for OIC remap.
Sales orders (OOL/OOS/OOH), customer master (OCUSMA), pricing (OPS), distribution orders (DOL series), invoice history (OIS) — full O2C extraction with CONO/DIVI tagging.
Item, Supplier, Customer, Invoice, PurchaseOrder, SalesOrder, ShipmentNotice plus vertical BODs (FoodAndBeverage, Fashion, Distribution). OAuth2 scoped, paginated, rate-limit-aware.
Six stages from kickoff to production-grade scheduled extraction.
Define in-scope tables, BODs, CONOs and historical window. Provision read-only DB user (or ION OAuth2 client) with SELECT grants on scoped tables. KMS-encrypted credential storage configured.
Extractor crawls M3 BE schema, identifies active tables in scope, profiles row counts and update-frequency, maps multi-CONO/DIVI partitioning. Output: extract topology with size estimate and parallelism plan.
Single-CONO single-FY test extract validates schema, join patterns, multi-language and multi-currency handling, audit-column behaviour. Output: validated test dataset with hash-signed manifest.
Full historical extract for all CONOs, fiscal years and in-scope entities. Run in parallel with 8–16 concurrent workers, throttled to M3 BE response-time SLAs. Output: complete Parquet dataset with per-partition manifests.
Modified-since watermarks configured per table, ION publish-event subscriptions established, scheduled jobs deployed. Output: production delta-extract schedule running on cron.
Monitoring dashboards configured (extract success rate, row counts vs trend, DB load impact), runbooks documented, on-call rotation established. Handover to operations team.
Built for regulated environments — finance, pharma, food, defense supply chain.
Read-only DB user with SELECT-only grants on scoped tables. No schema mods, no triggers, no admin shortcuts. ION uses OAuth2 client_credentials with minimal scope.
Every extract produces a manifest signed with a private key in cloud KMS. Tamper-evident — auditors can verify what was extracted, when, by whom and that nothing was modified.
Every query, every row count, every byte read logged with timestamp and user identity. SOC 2-grade audit trail accepted by Big 4 firms for SOX, SAF-T, HGB and Part 11 evidence.
ION BOD rate limits respected automatically (429 back-off transparent). DB load monitored continuously — parallelism throttled if M3 BE response times degrade.
Every extract is fully replayable from the manifest. Failed jobs resume from the last checkpoint, not from zero. Idempotent — re-running an extract produces identical output.
For strict change-window environments, extracts run against an isolated DB read replica or snapshot clone. Zero touch on live M3 BE during extraction windows.
An infor m3 data extraction tool is a piece of software that authenticates against an Infor M3 Business Engine environment — either by reading the underlying database (Oracle or SQL Server, depending on M3 deployment) or by calling ION Connect APIs (BODs, REST endpoints) — and streams the resulting data to a destination of your choice. Syntra ETL's M3 extractor supports both modes: it ships pre-built JDBC table extractors for the canonical MMS/CMS/CRS/OOL/MMO/MITMAS prefix families, an ION Connect API client with OAuth2 for everything API-fronted, parallel job orchestration, modified-since watermarks for delta runs, and audit-signed manifests for every output. Output formats include Parquet for analytics, JSON Lines for downstream ETL, and FBDI/HDL for direct Oracle Fusion loading.
Custom M3 extractors always start cheap and end expensive. M3 BE schemas run to thousands of tables with non-obvious relationships (the link between MITMAS item master and the dozen extension tables that hold UOM conversions, classification codes and pricing is documented across multiple Infor KB articles), multi-CONO/DIVI joining rules are non-trivial, multi-language CMS-style fan-outs trip up junior developers, and ION BODs come with their own pagination and rate-limit quirks. A custom script that works for items falls over on lot/serial chains, then breaks again on inter-company postings. Syntra ETL's infor m3 data extraction tool ships pre-built support for every prefix family, every BOD pattern, every multi-CONO scenario — backed by an SLA.
All of them in production use. M3 BE tables: full FGL/FAP/FSL/FAS finance families, MPL/PPS procurement, OOL/OOS/OOH/DOL sales and distribution, MMO/MWO/MBM/MRT manufacturing, MITMAS/MITBAL/MITWHL/MITLOC/MITALO inventory and traceability, CRS reference (including CRS055 rates and CRS630 COA), OCUSMA and CIDMAS partner masters. ION BODs: Item, Supplier, Customer, BOD-Acknowledge, Invoice, PurchaseOrder, SalesOrder, ShipmentNotice, plus the long tail of vertical-specific BODs (FoodAndBeverage, Fashion, Distribution). ION Connect REST endpoints where they exist. New schemas get folded in via quarterly extractor releases tracking M3's own roadmap.
Syntra ETL supports both Oracle and SQL Server M3 backends with read-only DB users provisioned with SELECT-only grants on the tables in scope — no schema modifications, no triggers, no admin shortcuts. Connection credentials are stored in cloud KMS, every query is logged with timestamp, user and row count for SOC 2 audit, and the read-only user can be revoked instantly. For customers with stricter security postures, extracts can run against an isolated DB read replica or a snapshot-based clone — neither of which touches the live M3 BE. ION Connect API access uses OAuth2 with scoped client credentials and token rotation. Customers in regulated sectors (food, pharma, defense supply chain) routinely pass internal security review on the first attempt.
Yes. Syntra ETL's M3 extractor supports cron-style scheduling, event-driven triggers (ION publish-events, DB CDC watermarks) and one-shot manual runs. Common scheduling patterns include nightly full extracts during the assessment phase, hourly delta extracts during cutover parallel-run, and weekly archive-window extracts after go-live for any long-tail historical capture. The scheduler handles dependency graphs (extract item master before lot detail, extract customer master before sales orders) and respects rate limits and DB load windows automatically. Failed jobs are retried with exponential back-off and full audit trail is captured for compliance review.
M3 BE tenants commonly hold 5–15 years of transactional history across dozens of CONOs — single-threaded extracts can run for days. Syntra ETL's infor m3 data extraction tool partitions large tables (FGL postings, MITLOC lot detail, OOH sales history) by CONO, fiscal year and record-status, then runs partitions in parallel — typically 8–16 concurrent workers depending on M3 backend capacity. A full historical extract for a multi-CONO tenant with 10 years of finance, sales, manufacturing and inventory history that would take 5 days single-threaded completes in 6–10 hours. Database load is monitored continuously and parallelism is throttled back if M3 BE response times degrade.
Every extract run produces a manifest: the list of tables/BODs/APIs hit, row counts per table per partition, byte counts, content-hash per file, start/end timestamps, and the read-only user identity that performed the extract. The manifest is signed with a private key held in cloud KMS, producing a tamper-evident record. When the data lands in Fusion or in long-term archive, the reconciliation process re-verifies the manifest signature — meaning auditors can confirm what was extracted, when, by whom and that nothing was modified post-extract. SOX, SAF-T, HGB, FDA Part 11 and ISO 27001 auditors all accept this evidence pattern.
Yes — and many customers do. After the migration cuts over to Fusion, the same infor m3 data extraction tool continues to pull from the M3 BE (kept read-only as the historical archive source-of-truth) or from the Syntra cloud archive (where M3 has been fully decommissioned), feeding the downstream analytics stack: Snowflake, BigQuery, Databricks, or back into OTBI for unified historical-plus-current reporting. The same Parquet output, the same hash-signed manifests, the same audit trail — used now for finance analytics, supply-chain dashboards and recall-traceability queries rather than for one-time migration loads.
Book a 30-minute walkthrough. We'll connect to a sample M3 BE, run a multi-CONO extract live, and show you the manifest, the reconciliation output and the audit trail.