Every record & field
Pull the full Manatal data model - employees, payroll, time, absences, and recruiting - not just a fixed preset, so your people reports are never missing a field.
Manatal
Manatal
HR & PeopleDataddo extracts the full Manatal data set - employees, payroll, time, absences, recruiting - and delivers it wherever your team needs it: into AI tools and agents, your warehouse like Snowflake and BigQuery, BI dashboards, and back into your finance and ops tools. Blend it with finance and ops data, backfill full history, and keep it fresh on your schedule - all fully managed, with the data plane running where you choose. No pipelines to build, no lock-in.
YOUR PEOPLE SOURCE OF TRUTH
Turn Manatal into people reporting your whole team trusts
People data is only useful when it's complete, clean, and current. Dataddo extracts the full Manatal data model, governs it, and serves it to every warehouse, dashboard, AI tool, and downstream system - continuously and without manual exports.
Blend with finance & ops
Combine Manatal with your finance and operations data so headcount, cost, and workforce analytics live in one place.
Backfill full history
Load historical Manatal data beyond the platform's export limits, so trend, tenure, and attrition analysis holds up.
Model, clean & mask before load
Normalize departments, roles, and currencies, and let the Data Quality Firewall stop bad rows while automatic PII detection masks sensitive employee fields before Manatal data reaches your reports.
Fresh on your schedule
Incremental, scheduled syncs keep Manatal data current - as often as hourly - without manual exports or full reloads.
Governed & monitored
Delivery alerts and quality checks catch gaps in Manatal data early, so people dashboards never silently break.
DATASETS
What you can pull from Manatal
The Manatal connector provides a list of curated datasets - ready-made sets of records, fields, and metrics you can extract on a schedule. Need something specific? Any dataset can be forked and customized, or built from scratch, with our Universal Connector.
List of curated datasets
IDid
string
Full namefull_name
sensitivestring
Display namedisplay_name
sensitivestring
E-mailemail
sensitivestring
Picturepicture
string
Phone numberphone_number
sensitivestring
Descriptiondescription
string
Organizationorganization
string
Creatorcreator
sensitivestring
Created Atcreated_at
datetime
Need a dataset, metric, or attribute you don't see?
Tell us what's missing and we'll add it to the connector.
WITH VS. WITHOUT
Who carries the load when things change
Keep Manatal data flowing to every warehouse, dashboard, and tool - and see who owns it when an API or schema changes:
| Without Dataddo |
With Dataddo
|
Outcome for you | |
|---|---|---|---|
| API or auth change | You discover the breakage and scramble to fix it. | We update the connector and restore the pipeline - often before you notice. | Syncs from Manatal keep flowing |
| Schema drift | Columns change and pipelines break or corrupt data silently. | Detected automatically and handled by configurable rules. | Only clean Manatal data lands in reports |
| Endpoint deprecated | You re-engineer the integration. | We own the update - the data contract holds. | Your Manatal reporting keeps working |
| Missing connector | You build and maintain a custom integration. | We build it and maintain it, under a ~4-week SLA. | Any Manatal data you need, on request |
| Silent degradation | You find out when a report or model run fails. | Proactive monitoring catches anomalies and delays first. | Gaps caught before dashboards break |
| Debugging | You dig through logs across disconnected tools. | Run histories, payload inspection, and end-to-end lineage in one place. | Faster root-cause, fewer reporting gaps |
Data residency by design
Choose where Manatal data is processed - same cloud, region, or sovereign
Manatal is a cloud API, so the question isn't on-prem vs cloud - it's which region your data flows through. With Dataddo you run the data plane in the region you choose, so Manatal payloads move straight to your destinations without transiting a third-party SaaS. Pin it to an EU or US region for compliance, or self-host when a downstream target lives inside your own network.
| Data Plane location | Typical data sensitivity | Why this setup |
|---|---|---|
|
Public cloud 
AWS
Microsoft Azure
Google Cloud
|
Low to moderate - general business, marketing, and product data; sources that are already cloud-native. | Fastest to stand up and scales elastically. Best when the data has no residency restriction and often already lives in the same public cloud. |
|
Regional & EU sovereign clouds
EU sovereign clouds
Regional providers
Private cloud
|
Regulated / residency-bound - PII, financial, and health data governed by GDPR or local law. | Keeps processing inside a specific jurisdiction to meet data-residency and sovereignty rules, while still running as managed infrastructure. |
|
On-premises 
Kubernetes
Red Hat OpenShift
VMware Tanzu
|
Highly sensitive / restricted - data that contractually or legally cannot leave the corporate perimeter. | Data never leaves your network. Required for air-gapped, classified, or locked-down environments; the Control Plane still manages it via metadata only. |
DATA DELIVERY
Every way to deliver Manatal data
People data rarely has one home. Dataddo feeds Manatal into AI and agents, loads it into your warehouse for workforce analytics, syncs records back into finance and ops tools, and delivers files to storage - all governed the same way.
| Transport type | What it does | Typical destinations | Typical business use cases |
|---|---|---|---|
| Data to AI & Agents | Feed Manatal data into vector databases, LLMs, and AI agents so people copilots can reason over your workforce data. | Load Manatal records into vector stores for retrieval-augmented HR assistants, Give AI agents and copilots governed access to live Manatal people data | |
| ETL / ELT to your warehouse | Load Manatal records and metrics into your warehouse for headcount and workforce analytics. | Centralize Manatal alongside finance and ops data in Snowflake, BigQuery, or Redshift, Backfill Manatal history for tenure and attrition analysis | |
| Sync back to finance & ops | Push modeled records built from Manatal data back into finance, payroll, and ops systems. | Sync headcount and cost records from Manatal into finance and planning tools, Keep Manatal people data aligned across systems | |
| Files to storage & partners | Deliver raw or modeled Manatal extracts to object storage and partners. | Archive raw Manatal exports to S3, GCS, or Azure storage, Send scheduled Manatal extracts to partners over SFTP |
Claude
OpenAI
Gemini
Mistral AI
Snowflake
BigQuery
Amazon Redshift
PostgreSQL
Salesforce
HubSpot
Monday
Google Sheets
Google Cloud Storage
Azure Blob Storage
SFTP
Case Studies
See what people and data teams build with Dataddo
65,000 Social Media Accounts. One Platform. Zero Manual Authorizations.
Beauty & Consumer Goods
How Livesport Activates Data, Saves Engineering Resources with BigQuery and Dataddo
Entertainment
How ID&T Group Activates Data from 1M+ Festival Fans and Dozens of Social Accounts
Entertainment
How Sensire Accelerated Migration of a Proprietary On-Premise Data Infrastructure to the Cloud with Dataddo
Healthcare
How Ringside.ai Builds a Data Product Better and Faster Using Dataddo
Marketing
How Publicis Groupe Brasil Uses Dataddo's API to Scale a Data Product
Advertising
FAQ
Manatal as a source + Dataddo, answered
Where can I send Manatal data?
To any of Dataddo's 150+ destinations - warehouses like Snowflake and BigQuery, BI dashboards, CRMs and marketing tools, object storage, and AI or vector stores - plus custom destinations on request.
Do I have to maintain the pipeline?
No. Dataddo is fully managed: we maintain the Manatal connector, adapt to API and schema changes, and alert you if anything needs attention. There is no pipeline code for you to write or fix.
How is sensitive employee data handled?
Dataddo can mask or hash PII in Manatal data before it lands, and if you run the data plane on-premises, payload data never leaves your network. Combined with SOC 2 Type II and ISO 27001 certification and EU or US residency, that keeps people data compliant end to end.
What if Manatal changes their API?
That's on us, not you. Dataddo's team proactively tracks Manatal API and schema changes and updates the connector before they break your pipeline. Continuous monitoring watches every sync, and if anything needs attention you get an alert - so your Manatal data keeps flowing without you touching a thing.
Which Manatal data and fields are available?
The full Manatal data model - employees, payroll, time, absences, and recruiting - not a fixed subset. If a field you need isn't exposed yet, we add it on request, usually at no extra cost.
How is my data secured?
Dataddo is SOC 2 Type II and ISO 27001 certified. Data is encrypted in transit and at rest, PII can be masked or hashed, and EU or US data residency is available. Self-host the data plane and payload data never leaves your network.
Will API rate limits be a problem?
Dataddo handles Manatal pagination, rate limits, and retries for you, and pulls incrementally on a schedule so you stay within API quotas without impacting your source.
Am I locked in?
No. Pipelines are source- and destination-agnostic - you can add or switch destinations without rebuilding, and data lands in native formats you own.