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Peliqan

One-click data pipelines for Google Sheets to AWS S3

Easily sync data from Google Sheets to AWS S3, explore your data with the rich Data Explorer and transform your Google Sheets data with SQL.

Google Sheets Writeback
AWS S3


Google Sheets Writeback

Google Sheets Writeback is a productivity and collaboration platform centralizing project management, documents, and team workflows. Native reporting covers project basics but cannot join task data with finance or operational systems without a warehouse. Peliqan provides a managed Google Sheets Writeback connector that syncs projects, tasks, and team data into your warehouse for delivery analytics and capacity planning.


AWS S3

AWS S3 is a cloud data warehouse used as a central destination for analytical workloads, separating storage from compute for scalable performance. It supports SQL-native exploration of large datasets and is the standard target for unified analytics. Peliqan loads AWS S3 from upstream business applications through managed ELT connectors with incremental syncs and schema management.

Common Google Sheets Writeback to AWS S3 use cases

Project delivery and capacity reporting
Cross-team workload visibility
Time tracking and billable hours analysis
Document and meeting volume metrics
Joining Google Sheets Writeback with finance and HR data
Engineering and product velocity dashboards

Instant ELT pipeline & data warehouse loading

Peliqan brings ETL pipelines, data transformations and reverse ETL together in one integrated platform. Connect your favorite BI tool and activate your data with SQL and low-code Python.

Built-in Data Warehouse

Direct-to-warehouse sync

Sync Google Sheets data into AWS S3 with a few clicks. Or choose any other data warehouse or database as a destination.

One-Click BI Integration

One-click pipeline setup

Deploy production-ready ELT pipelines with automatic schema detection and incremental updates. Your Google Sheets data flows into AWS S3 continuously.

AI-Powered SQL Analytics

AI-driven data management

Transform your data during sync with SQL or Python. Use AI to generate transformation logic from plain-English descriptions – clean, validate and enrich data before it lands in AWS S3.

RAG & AI Agents

Multi-source integration

Combine Google Sheets with 250+ other data sources in AWS S3. Create unified datasets for analytics, reporting and machine learning – all in your centralized warehouse.

Python Data Apps

Python & SQL processing

Run custom Python or SQL transformations on your Google Sheets data before loading into AWS S3. Perfect for data checks, business logic, and complex transformations.

Data Sync & Activation

Reverse ETL & orchestration

After processing your data in AWS S3, sync enriched data back to Google Sheets or other systems (writeback). Complete the loop with bidirectional sync.

How to connect Google Sheets and AWS S3

1. Connect in 30 Seconds

Authenticate your source (Google Sheets)
via OAuth or API key – no complex setup.

Your data appears in the Peliqan data warehouse with automatic schema detection and optimization for analytics.

Or bring your own data warehouse (Snowflake, Redshift, Bigquery, Clickhouse, Fabric).

Use SQL, natural language queries, or the Peliqan data explorer and analyze your unified data.

Connect your favorite BI tool to the Peliqan data warehouse, build Python apps, and sync insights back to your business applications.

Turn on AI Agents (RAG and text-to-SQL) to answer business queries, generate SQL, or trigger downstream actions (e.g., create a CRM task).

Connect in 30 Seconds

Data Flows Automatically

Query & Analyze

Activate Insights

Beyond simple sync

A cloud data platform designed for the systems and workflows modern data and business teams use every day.

Incremental pipelines

Efficiently sync only new & changed records from Google Sheets to AWS S3 using incremental loading strategies.

Schema evolution management

Automatically handle schema changes in Google Sheets – new fields, renamed columns, and type changes are detected and propagated to AWS S3.

Data quality & validation

Built-in data quality checks ensure clean data in AWS S3. Set validation rules, detect anomalies, and get alerts for data quality issues.

Enterprise orchestration

Schedule complex workflows, dependencies, and multi-step pipelines. Use built-in orchestration capabilities.

Warehouse-native optimization

Leverage AWS S3-specific features like partitioning, clustering, and materialized views for optimal query performance.

Developer platform

REST APIs, Python SDK and a custom connector framework for advanced data engineering workflows.

Technical Specifications

Peliqan provides a high-performance ELT engine optimized for modern cloud data warehouses.
Load, transform and orchestrate data reliably with warehouse-native speed and security.

Supported Data Types

Supported Data Types

Performance & scale

Performance & scale

Security features

Security features

More destinations for Google Sheets Writeback

Send data out

Sync your Google Sheets Writeback data into these databases and warehouses.

Google Sheets Writeback

MongoDB

MongoDB

Google Sheets Writeback

Postgres

Postgres

Google Sheets Writeback

MS SQL Server

MS SQL Server

Google Sheets Writeback

Elastic Search

Elastic Search

Google Sheets Writeback

MySQL

MySQL

Google Sheets Writeback

Qdrant

Qdrant

More sources for AWS S3

Bring data in

Sync data from these business apps into AWS S3 dashboards.

AWS S3

Tally

Tally

AWS S3

Customer.io

Customer.io

AWS S3

HubSpot

HubSpot

AWS S3

Pipedrive

Pipedrive

AWS S3

Salesforce

Salesforce

AWS S3

Voucherify

Voucherify

SaaS Data Cockpit

Connect your apps, then work with the data in a spreadsheet, in SQL, or in plain English. No pipelines to maintain.

Built with enterprise-grade security and compliance.

SOC 2 Type II
GDPR-compliant
HIPAA compliant
ISO 27001

G2 Badges 2026

Frequently asked questions

Yes, you can connect multiple instances of Google Sheets and unify the data, or you can customize field mappings for each connection.

You control the sync frequency: as often as every 15 minutes on the Pro plan, or hourly, daily and custom schedules. Some source systems set their own limits – Exact Online, for example, defaults to every 6 hours.

Yes. Transform data with SQL or low-code Python before or after it lands in the warehouse. You can clean fields, join across sources and reshape tables without touching the source system.

Peliqan handles enterprise-scale data volumes. Our distributed architecture processes millions of records efficiently with automatic scaling based on your needs.

Our team builds custom connectors, typically within 2 weeks. You can also build your own pipelines with low-code Python.

Ready to get instant access to all your company data ?

Connect Google Sheets to AWS S3 in minutes, and build the reports and dashboards your team actually needs.