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Data warehouse ⇄ Developer tools

BigQuery to Ldap integration — real-time, two-way sync

Keep BigQuery and Ldap 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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Why teams connect BigQuery and Ldap

Close the gap between analytics and operations: BigQuery holds the record while Ldap runs the day-to-day work, and Stacksync keeps the two in step in real time, in both directions.

BigQuery is the central store where teams keep Partitioned tables, Clustered tables, Datasets, Projects for reporting and analysis; Ldap runs the operational side of engineering work — tracking issues, moving messages and events, watching systems, and managing users and access. The two overlap wherever the same operational data matters to both: the Entries, Person entries (inetOrgPerson / user), Groups (groupOfNames / posixGroup), Organizational units (ou) produced in Ldap are exactly what analysts want to measure in BigQuery, and the curated rows in BigQuery are what should drive the next action in Ldap. When that overlap is bridged by nightly ETL or hand-written scripts, dashboards lag a day behind reality and the tools that should react to warehouse signals never see them.

Stacksync syncs Partitioned tables, Clustered tables, Datasets, Projects in BigQuery with Entries, Person entries (inetOrgPerson / user), Groups (groupOfNames / posixGroup), Organizational units (ou) in Ldap field by field, in real time, and in both directions. You decide which system owns which fields; Stacksync matches records on a stable external key, keeps every copy consistent, and resolves conflicts by rules you set — so analytics and operations work from the same current data instead of two drifting copies.

Common use cases

  • 01 Activate modeled BigQuery tables by syncing computed attributes back into sales and marketing tools
  • 02 Maintain a customer master table in BigQuery joined across CRM, billing, and support sources
  • 03 Incrementally sync changed entries by polling modifyTimestamp, keeping a downstream store fresh without dumping the whole directory each cycle.
  • 04 Keep group member and uniqueMember attributes aligned with application entitlement tables so directory access reflects the right teams as they change.

Common sync patterns

Keep user and access records aligned

Where Ldap manages users, directory, or access data, those records stay current in BigQuery — and can be provisioned back from it — so ownership and permissions match across both.

Operational data lands in BigQuery for analytics

Records created in Ldap — issues, events, messages, metrics, or user changes — replicate into BigQuery tables as they happen, so reporting runs on current data instead of last night's export.

Warehouse signals reach Ldap

A row scored, flagged, or enriched in BigQuery creates or updates the matching record in Ldap, so the operational tool acts on the same data the analysts already see.

What you can sync between BigQuery and Ldap

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.

BigQuery objects Ldap objects How this pairing syncs
Clustered tables Supported; clustering is transparent to the sync. Entries The fundamental unit of an LDAP directory, each addressed by a distinguished name (DN) and typed by its objectClass; synced two-way as records, with the DN driving upserts and attribute-level updates. Clustered tables is specific to BigQuery and Entries to Ldap — each maps to any object or custom field on the other side.
Datasets Organizational container — you pick which dataset’s tables to sync. Person entries (inetOrgPerson / user) People held under objectClasses such as inetOrgPerson, person, or Active Directory user; synced two-way to create accounts and update attributes like mail, cn, and telephoneNumber. Datasets is specific to BigQuery and Person entries (inetOrgPerson / user) to Ldap — each maps to any object or custom field on the other side.
Projects Connection scope: the service account grants access per project. Groups (groupOfNames / posixGroup) Group entries whose member or uniqueMember attributes list DNs; synced two-way to add and remove membership as teams and entitlements change. Projects is specific to BigQuery and Groups (groupOfNames / posixGroup) to Ldap — each maps to any object or custom field on the other side.
Tables The syncable unit: only tables can be synced per the Stacksync docs. Organizational units (ou) Container entries that structure the DIT and scope which subtree a sync reads or writes; used to limit a sync to a branch such as ou=People,dc=corp,dc=com. Tables is specific to BigQuery and Organizational units (ou) to Ldap — each maps to any object or custom field on the other side.
Partitioned tables Synced like regular tables; partition columns map to target fields. Attributes The typed name/value pairs on each entry (cn, mail, memberOf, objectClass); the schema defines which attributes each objectClass allows, and mappings are built per attribute. Partitioned tables is specific to BigQuery and Attributes to Ldap — each maps to any object or custom field on the other side.

How changes propagate between BigQuery and Ldap

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.

BigQuery Ldap Sub-second propagation

DetectionChanges in BigQuery are captured at the source via change data capture — no polling loop against its API. Real-time notification service deployed into your Google Cloud project: Eventarc ("a notification service that enables real-time updates to happen").

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

Ldap BigQuery Interval-based propagation

DetectionStacksync polls Ldap for changes on an incremental schedule, reading only records changed since the previous pass. No universal native change feed.

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

Rate-limit considerations

  • BigQuery: Subject to Google Cloud quotas on queries, DML, and streaming; DML is supported but the platform favors append-heavy batch and streaming loads over row-at-a-time writes.
  • Ldap: LDAP defines no request quota; throughput is bounded by the server's sizelimit and timelimit administrative limits, connection and thread caps, and the CPU/IO it shares with live authentication traffic, so large syncs can contend with production lookups and must page results.
What ships with BigQuery ⇄ Ldap

Connect BigQuery and Ldap for flexible, real-time data sync.

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

Real-time

Two-way sync

Changes in BigQuery or Ldap instantly reflect in both systems. No stale data, no manual imports.

No-code + pro-code

Workflow automation

Trigger automated workflows whenever BigQuery or Ldap 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 BigQuery or Ldap record.

Observability

Monitoring

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

Trading partners

EDI

Transform legacy EDI complexity into simple database interactions between BigQuery and Ldap.

How the BigQuery and Ldap connectors work

BigQuery

Integration surface
GoogleSQL via the BigQuery REST API, client libraries, JDBC/ODBC drivers, and the Storage Read/Write APIs
Authentication
Google Cloud service account: create a dedicated service account, grant roles (BigQuery Data Editor, BigQuery Job User, Cloud Functions Service Agent, Cloud Run Developer, Eventarc Event Receiver
Change detection
Real-time notification service deployed into your Google Cloud project: Eventarc ("a notification service that enables real-time updates to happen") with a Cloud Run "secure portal for real-time notification service in
Capabilities
read · write · CDC
Rate limits
Subject to Google Cloud quotas on queries, DML, and streaming; DML is supported but the platform favors append-heavy batch and streaming loads over row-at-a-time writes
BigQuery setup guide

Ldap

Integration surface
LDAPv3 protocol (RFC 4511) over TCP, typically LDAPS on port 636 or StartTLS on 389; reaches any LDAPv3 directory server - OpenLDAP, Microsoft Active Directory, 389 Directory Server, Oracle Unified Directory, PingDS/ForgeRock, NetIQ eDirectory, Apache Directory.
Authentication
A bind DN and password (simple bind), typically over TLS, using a service account with rights to the target subtree. SASL mechanisms - GSSAPI/Kerberos, DIGEST-MD5, or EXTERNAL with a client certificate - are available where the server supports them.
Change detection
No universal native change feed. Incremental sync polls the modifyTimestamp operational attribute (or entryCSN / uSNChanged on servers that expose them) for entries changed since the last cursor; detecting deletes needs a server changelog or tombstones because a plain search cannot see removed entries. Some servers add Persistent Search or RFC 4533 content-sync (syncrepl), but that support is server-specific. No webhooks.
Capabilities
read · write
Rate limits
LDAP defines no request quota; throughput is bounded by the server's sizelimit and timelimit administrative limits, connection and thread caps, and the CPU/IO it shares with live authentication traffic, so large syncs can contend with production lookups and must page results.
How it works

How to connect BigQuery to Ldap — 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 BigQuery and Ldap 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
    BigQuery connected
    Ldap connected
    OAuth 2.0
    SSH tunnel
    SSL certificate
    VPC peering
  2. 02

    Choose tables

    Pick the BigQuery and Ldap 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 · BigQuery ⇄ Ldap
    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
    BigQuery Ldap
    Company company_name text
    Email email text
    Amount amount numeric
    Created created_at timestamp
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FAQ

BigQuery and Ldap 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 421 integrations available for BigQuery and Ldap.

Popular · 8 of 421
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