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Business productivity ⇄ Data warehouse

Agiloft to Databricks integration — real-time, two-way sync

Keep Agiloft and Databricks in sync without custom scripts. Cut weeks of integration work, eliminate silent data drift, and give your team a single, reliable source of truth.

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Adopted by fast-scaling companies moving mission-critical data in real time

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Why teams connect Agiloft and Databricks

Get the data locked inside Agiloft into Databricks as live tables, and send results back where Agiloft can use them, without writing a pipeline.

Whatever Agiloft is used for, it accumulates data the rest of the company wants to analyze, and that data usually sits behind an API rather than in the warehouse. Building and babysitting an extraction pipeline is the tax most teams pay for it.

Stacksync syncs Contracts, Companies, People, Attachments from Agiloft into tables in Databricks continuously, handling schema, rate limits, and retries. Because the sync is bi-directional, results computed in Databricks can also be written back into fields in Agiloft where the tool can use them.

Common use cases

  • 01 Two-way sync Contracts between Agiloft and an ERP or warehouse so value, renewal dates, and status stay current without manual re-keying.
  • 02 Push generated documents and executed PDFs into Agiloft Attachments from a document system, or pull signed contracts out for archival.
  • 03 Land CRM and ERP records in Delta tables continuously so lakehouse models work from current operational data.
  • 04 Use Change Data Feed to propagate only changed rows to downstream apps instead of full-table scans.

Common sync patterns

Cross-tool reporting

Combine Agiloft's data with data from every other synced system to answer questions no single tool can.

Where Agiloft accepts updates: operational write-back

Segments, scores, or reference values computed in Databricks sync back onto records in Agiloft, putting analysis where the work happens.

History that outlives the tool

A continuously synced copy in Databricks preserves a queryable record even as data ages out of Agiloft or gets changed inside it.

What you can sync between Agiloft and Databricks

Representative objects on each side — any object or custom field can map to any target. Schemas are auto-detected; types are converted between the two systems.

Agiloft objects Databricks objects How this pairing syncs
Clause Library Reusable, approved contract clauses with metadata and categories; read to feed clause content into other systems or reporting, or maintained from an external source of truth. Change Data Feed Row-level change records on Delta tables that drive incremental reads. Clause Library is specific to Agiloft and Change Data Feed to Databricks — each maps to any object or custom field on the other side.
Custom tables Agiloft is a no-code platform, so any customer-built table (NDAs, SOWs, vendor risk, renewals) exposes the same REST and SOAP CRUD and syncs like the standard CLM tables. Catalogs Top level of the Unity Catalog namespace, scoping which schemas a sync can address. Custom tables is specific to Agiloft and Catalogs to Databricks — each maps to any object or custom field on the other side.
Contracts The core table holding contract records with value, key dates, status, type, and linked parties; created and updated two-way so contract data moves between Agiloft and a database, ERP, or CRM. Schemas Group tables and views; syncs typically target a dedicated schema per source system. Contracts is specific to Agiloft and Schemas to Databricks — each maps to any object or custom field on the other side.
Companies Records for every organization - counterparties, vendors, customers - linked to contracts and people; read and written to keep account master data aligned with a CRM or ERP. Delta Tables The primary read and write target; operational data lands here as managed or external tables. Companies is specific to Agiloft and Delta Tables to Databricks — each maps to any object or custom field on the other side.
People Parent table for individuals, split into Employees (internal users) and Contacts (external company contacts); synced to map signers, approvers, and account owners to CRM or HR records. Views Curated read-only projections used as sync sources for downstream tools. People is specific to Agiloft and Views to Databricks — each maps to any object or custom field on the other side.
Attachments File records holding the executed contract PDFs and supporting documents linked to a contract; read to pull signed files out, or written to push generated documents in. Materialized Views Precomputed results read on a schedule for reverse-ETL style syncs. Attachments is specific to Agiloft and Materialized Views to Databricks — each maps to any object or custom field on the other side.

How changes propagate between Agiloft and Databricks

Each direction of the sync is driven by what the source system can signal and what the destination accepts — detection, delivery, and expected latency below.

Agiloft Databricks Sub-second propagation

DetectionAgiloft notifies Stacksync of record changes through webhook events. Native webhook subscriptions (POST /ewws/webhooks) fire on record create, edit, or delete after a GET handshake verifies the callback URL.

DeliveryEach detected change is applied to Databricks as a row-level write, with types converted between the two schemas.

Databricks Agiloft Sub-second propagation

DetectionChanges in Databricks are captured at the source via change data capture — no polling loop against its API. Delta Lake Change Data Feed for row-level changes.

DeliveryEach detected change is written to Agiloft through its API, with automatic retries and rate-limit backoff.

Rate-limit considerations

  • Agiloft: Agiloft publishes no fixed per-minute REST quota; throughput is instance-specific and bounded by license seats (Assigned/Floating Power User) and concurrent API sessions. Each SOAP/EWS call runs in its own transaction, and REST logins issue a session token meant to be reused rather than re-authenticated per call.
  • Databricks: Throughput depends on the SQL warehouse size; API calls are subject to workspace rate limits.
What ships with Agiloft ⇄ Databricks

Connect Agiloft and Databricks for flexible, real-time data sync.

Real-time sync, workflow automation, event queues, EDI, and monitoring, for every Agiloft–Databricks connection.

Real-time

Two-way sync

Changes in Agiloft or Databricks instantly reflect in both systems. No stale data, no manual imports.

No-code + pro-code

Workflow automation

Trigger automated workflows whenever Agiloft or Databricks data changes, update records, fire webhooks, or kick off sequences without brittle API scripts.

At scale

Event queues

Handle millions of events per minute without losing a single Agiloft or Databricks record.

Observability

Monitoring

Track your Agiloft ⇄ Databricks sync health, view errors, and replay failed events in one click.

Trading partners

EDI

Transform legacy EDI complexity into simple database interactions between Agiloft and Databricks.

How the Agiloft and Databricks connectors work

Agiloft

Integration surface
REST API (/ewws/rest/{kb}) and SOAP/EWS v2 web services (EWWSv2Service WSDL), plus a native Webhooks subscription API
Authentication
OAuth 2.0 via OAuth2 Client Setup - Authorization Code with PKCE for user-delegated apps and Client Credentials for machine-to-machine; also JWT tokens or Basic Auth with a session token from POST /ewws/rest/{kb}/login
Change detection
Native webhook subscriptions (POST /ewws/webhooks) fire on record create, edit, or delete after a GET handshake verifies the callback URL; otherwise poll each table by its Date Updated / modified-time fields. Agiloft has no database change-data-capture log.
Capabilities
read · write · webhooks
Rate limits
Agiloft publishes no fixed per-minute REST quota; throughput is instance-specific and bounded by license seats (Assigned/Floating Power User) and concurrent API sessions. Each SOAP/EWS call runs in its own transaction, and REST logins issue a session token meant to be reused rather than re-authenticated per call.

Databricks

Integration surface
SQL over JDBC/ODBC via SQL warehouses, plus a REST API including statement execution
Authentication
Personal access tokens or OAuth machine-to-machine credentials for service principals
Change detection
Delta Lake Change Data Feed for row-level changes; otherwise incremental polling on watermark columns
Capabilities
read · write · CDC
Rate limits
Throughput depends on the SQL warehouse size; API calls are subject to workspace rate limits
How it works

How to connect Agiloft to Databricks — three steps, no code

Configure and sync within minutes, no code. Whether you sync 50k or 100M+ records, Stacksync handles the queues, infra, and plumbing. Integrations are non-invasive and need zero setup on your systems.

  1. 01

    Connect your apps

    Authenticate Agiloft and Databricks with each platform's native method — OAuth, API keys, or service accounts — plus secure options like SSH tunneling, IP whitelisting, and VPC peering.

    • OAuth 2.0
    • SSH tunnel
    • VPC peering
    Agiloft connected
    Databricks connected
    OAuth 2.0
    SSH tunnel
    SSL certificate
    VPC peering
  2. 02

    Choose tables

    Pick the Agiloft and Databricks objects to sync — Stacksync auto-detects both schemas, including custom fields where the platform exposes them. Sync to existing tables, or let Stacksync create new ones with ideal data types.

    • Standard objects
    • Custom objects
    • Auto-schema
    objects · Agiloft ⇄ Databricks
    Customers 12,480
    Sales Orders 8,213
    Invoices 5,902
    Items 1,344
  3. 03

    Map fields

    Fields map automatically even when names and types differ. Stacksync handles transformation and type casting for you, zero configuration required.

    • Auto-map
    • Type casting
    • Transforms
    Agiloft Databricks
    Company company_name text
    Email email text
    Amount amount numeric
    Created created_at timestamp
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FAQ

Agiloft and Databricks integration FAQ

SECURITY

Security teams trust Stacksync

As a data company, we understand the importance of keeping your data secure. Stacksync is built with security best practices to keep your data safe at every layer, and is DPF-certified for US, EU, UK and CH data transfers.

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SSO & SCIM

Let your users access Stacksync from your centralized user management systems. Works with Okta, Azure, Google SSO and more.

Alerts

Immediately get alerted about record syncing issues over email, Slack, PagerDuty and WhatsApp. Resolve issues from a centralized dashboard with retry and revert options.

Secure connection options

Securely connects to your systems with:

OAuth 2 SSH Tunnelling SSL certificates IP Whitelisting VPN gateway VPC peering and more

Related integrations

Every pair below is a real-time, two-way sync. Search all 451 integrations available for Agiloft and Databricks.

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