Real-time
Two-way sync
Changes in Elasticsearch or Gatekeeper instantly reflect in both systems. No stale data, no manual imports.
Database ⇄ Business productivity
Elasticsearch to Gatekeeper integration — real-time, two-way sync
Keep Elasticsearch and Gatekeeper in sync without custom scripts. Cut weeks of integration work, eliminate silent data drift, and give your team a single, reliable source of truth.
- SOC 2 and 6 other compliance frameworks
- POC with real engineers in minutes
Adopted by fast-scaling companies moving mission-critical data in real time
Case study
Migrated from MuleSoft
Case study
Migrated from Celigo
Migrated from Heroku Connect
Migrated from Matillion
Case study
Migrated from Fivetran
Case study
Migrated from Celigo
Why teams connect Elasticsearch and Gatekeeper
Mirror Gatekeeper's data into Elasticsearch so your own code can read and write it like any other table, with changes flowing both ways in seconds.
Engineers integrate with tools like Gatekeeper through APIs, which means auth, pagination, rate limits, webhooks, and retry logic, all maintained forever and all different for every tool. Meanwhile the data would be trivial to use if it simply lived in Elasticsearch.
Stacksync mirrors Vendors (Suppliers), Files, Workflow form data, Custom data groups from Gatekeeper into Index templates, Indices, Documents, Index mappings in Elasticsearch and keeps both sides in sync in real time. Your services query the database directly, and inserts or updates your code makes flow back into Gatekeeper, so the tool and the database never disagree.
Common use cases
- 01 Two-way sync Contracts between Gatekeeper and an ERP or warehouse so value, renewal dates, owner, and status stay current without manual re-keying.
- 02 Sync Vendors (Suppliers) with a CRM or ERP so counterparty, compliance, contact, and spend records match across the VCLM and the systems of record.
- 03 Mirror support tickets into an index used for full-text search and agent-assist tooling.
- 04 Feed enriched customer records into an index used for vector or hybrid search in AI applications.
Common sync patterns
React to changes as they happen
Updates in Gatekeeper arrive as row changes in Elasticsearch, so triggers, jobs, and services can respond in near real time.
One integration pattern for the whole stack
Every synced tool looks the same from the database, so each new integration is configuration, not a new codebase.
Read Gatekeeper with a query
Records from Gatekeeper are ordinary rows in Elasticsearch; join them, index them, and use them in application logic without touching the vendor API.
What you can sync between Elasticsearch and Gatekeeper
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.
| Elasticsearch objects | Gatekeeper objects | How this pairing syncs | |
|---|---|---|---|
| Aliases Stable read/write names that let a sync cut over between index versions without downtime. | Vendors (Suppliers) Company records for counterparties and suppliers with onboarding status, compliance, risk, contacts, and spend; read and written to keep vendor master data aligned with a CRM or ERP. | Aliases is specific to Elasticsearch and Vendors (Suppliers) to Gatekeeper — each maps to any object or custom field on the other side. | |
| Data streams Append-only targets for time-series or event data pushed from source systems. | Files Document files attached to contracts and vendors - executed PDFs, certificates, and compliance evidence; read to pull signed files and evidence out, or written to push generated documents in. | Data streams is specific to Elasticsearch and Files to Gatekeeper — each maps to any object or custom field on the other side. | |
| Ingest pipelines Server-side transforms applied to documents as a sync writes them. | Workflow form data The structured data captured on Gatekeeper workflow forms (intake requests, vendor onboarding, risk assessments); exposed by the API since 2025 so form results sync into an operational database, not only contract and vendor records. | Ingest pipelines is specific to Elasticsearch and Workflow form data to Gatekeeper — each maps to any object or custom field on the other side. | |
| Index templates Reusable settings and mappings applied automatically to new indices a sync creates. | Custom data groups Customer-configured custom fields and data groups; because the JSON:API and its docs are dynamic, any custom data added in Configuration exposes the same read/write endpoints as the standard objects and syncs the same way. | Index templates is specific to Elasticsearch and Custom data groups to Gatekeeper — each maps to any object or custom field on the other side. | |
| Indices Target containers for synced records; each holds a table-like collection of JSON documents. | Users Gatekeeper user and team records governed by role-based access; read to map contract and vendor owners, approvers, and internal contacts to CRM or HR records. | Indices is specific to Elasticsearch and Users to Gatekeeper — each maps to any object or custom field on the other side. | |
| Documents The unit of sync; JSON records created, updated, and deleted by _id. | Categories The classification taxonomy applied to contracts and vendors (type, department, business unit); synced so categorization stays consistent between Gatekeeper and downstream reporting or ERP dimensions. | Documents is specific to Elasticsearch and Categories to Gatekeeper — each maps to any object or custom field on the other side. |
How changes propagate between Elasticsearch and Gatekeeper
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.
Elasticsearch Gatekeeper Interval-based propagation
DetectionStacksync polls Elasticsearch for changes on an incremental schedule, reading only records changed since the previous pass. Polling on timestamp or sequence fields.
DeliveryEach detected change is written to Gatekeeper through its API, with automatic retries and rate-limit backoff.
Gatekeeper Elasticsearch Interval-based propagation
DetectionStacksync polls Gatekeeper for changes on an incremental schedule, reading only records changed since the previous pass. No native developer webhook subscription API and no database change-data-capture log.
DeliveryEach detected change is written to Elasticsearch through its API, with automatic retries and rate-limit backoff.
Rate-limit considerations
- Elasticsearch: No fixed request quota; throughput is bounded by cluster sizing, thread pools, and bulk queue capacity.
- Gatekeeper: Gatekeeper publishes no fixed public per-minute request quota; throughput is governed per key by its endpoint permissions, and every call is recorded (parameters, payload, response) under API Logs for monitoring. Pace bulk writes and use JSON:API pagination on list endpoints.
What ships with Elasticsearch ⇄ Gatekeeper
Connect Elasticsearch and Gatekeeper for flexible, real-time data sync.
Real-time sync, workflow automation, event queues, EDI, and monitoring, for every Elasticsearch–Gatekeeper connection.
No-code + pro-code
Workflow automation
Trigger automated workflows whenever Elasticsearch or Gatekeeper 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 Elasticsearch or Gatekeeper record.
Observability
Monitoring
Track your Elasticsearch ⇄ Gatekeeper sync health, view errors, and replay failed events in one click.
Trading partners
EDI
Transform legacy EDI complexity into simple database interactions between Elasticsearch and Gatekeeper.
How the Elasticsearch and Gatekeeper connectors work
Elasticsearch
- Integration surface
- REST API (JSON over HTTP)
- Authentication
- API keys or basic authentication; Elastic Cloud also issues service account tokens
- Change detection
- Polling on timestamp or sequence fields; Elasticsearch does not expose a native change feed or webhooks
- Capabilities
- read · write
- Rate limits
- No fixed request quota; throughput is bounded by cluster sizing, thread pools, and bulk queue capacity
Gatekeeper
- Integration surface
- RESTful API following the JSON:API specification, tenant-scoped with interactive docs at {tenant}.gatekeeperhq.com/api_docs and a published Postman collection. The API is dynamic: it exposes the standard Contract and Vendor objects plus any custom data groups and workflow-form data configured in the tenant.
- Authentication
- API keys created and managed under Configuration > API Keys and passed as a token; each key carries granular per-endpoint permissions set to read-only or write, so access is scoped per object. Multiple keys can be issued and revoked independently.
- Change detection
- No native developer webhook subscription API and no database change-data-capture log; detect changes by polling the JSON:API list endpoints filtered and sorted on updated-at timestamps. Gatekeeper's own event automation - Workflow Engine phase transitions and Interconnect process orchestration - runs inside the platform rather than as a subscribable webhook stream.
- Capabilities
- read · write
- Rate limits
- Gatekeeper publishes no fixed public per-minute request quota; throughput is governed per key by its endpoint permissions, and every call is recorded (parameters, payload, response) under API Logs for monitoring. Pace bulk writes and use JSON:API pagination on list endpoints.
How it works
How to connect Elasticsearch to Gatekeeper — 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.
- 01
Connect your apps
Authenticate Elasticsearch and Gatekeeper with each platform's native method — OAuth, API keys, or service accounts — plus secure options like SSH tunneling, IP whitelisting, and VPC peering.
Elasticsearch
connected
Gatekeeper
connected
OAuth 2.0SSH tunnelSSL certificateVPC peering - 02
Choose tables
Pick the Elasticsearch and Gatekeeper 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.
objects · Elasticsearch ⇄ GatekeeperCustomers 12,480Sales Orders 8,213Invoices 5,902Items 1,344 - 03
Map fields
Fields map automatically even when names and types differ. Stacksync handles transformation and type casting for you, zero configuration required.
Elasticsearch GatekeeperCompany company_name textEmail email textAmount amount numericCreated created_at timestamp
FAQ
Elasticsearch and Gatekeeper integration FAQ
-
Yes. Stacksync provides a managed, real-time two-way integration between Elasticsearch and Gatekeeper: authenticate both systems, choose the objects to sync (such as Elasticsearch's Aliases and Data streams), map fields visually, and changes propagate both ways in milliseconds — no code required.
-
Gatekeeper: Write access is per API key per endpoint: when you create a key you choose read-only or write for each object, so the API is write-capable and can create and update records rather than only export them. Elasticsearch: Writes are addressed by document _id, so upserts map directly onto the index API, and the _bulk endpoint batches many operations in a single request. Stacksync's field mapping accounts for these differences between Elasticsearch and Gatekeeper without custom code.
-
Stacksync is SOC 2 Type II and ISO 27001 certified with HIPAA BAA support. Data is encrypted in transit, and a zero-persistent-storage architecture means Elasticsearch and Gatekeeper records are not retained after a sync operation.
-
Stacksync pricing is usage-based and starts at $1,000/month, including the managed Elasticsearch and Gatekeeper connectors, real-time two-way sync, monitoring, and support. That replaces building and maintaining a custom Elasticsearch–Gatekeeper integration in-house.
-
Yes — Stacksync ships production-grade connectors for both Elasticsearch and Gatekeeper. The connectors handle authentication, schema detection, rate limits, and retries; you configure the sync, and Stacksync operates it.
-
Change detection on Elasticsearch: Polling on timestamp or sequence fields; Elasticsearch does not expose a native change feed or webhooks. On Gatekeeper: No native developer webhook subscription API and no database change-data-capture log; detect changes by polling the JSON:API list endpoints filtered and sorted on updated-at timestamps. Gatekeeper's own event automation - Workflow Engine phase transitions and Interconnect process orchestration - runs inside the platform rather than as a subscribable webhook stream. Each detected change propagates to the other side in milliseconds, with field-level conflict resolution and an inspectable event log.
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.
SOC 2 Type II
ISO 27001
HIPAA BAA
GDPR
CCPA
CSA STAR
DPF US-EU-UK-CH
→ SECURITY WITH BENEFITS
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:
Related integrations
Every pair below is a real-time, two-way sync. Search all 421 integrations available for Elasticsearch and Gatekeeper.
Popular · 2 of 421
No integrations match .
