Product

Your data's journey, in one platform: connect it, prepare it, reuse it, and automate the reporting you used to do by hand. Insights and AI are the next chapters, tracked openly.

See the full roadmap →

01 · Connect

Connect to your systems

PostgreSQL is live today. The same visual workflow works with any connector as it ships — here’s the full breadth of what’s coming across databases, files, cloud storage, and business apps.

Databases

PostgreSQL
MySQL
SQL Server
MongoDB
Redis
Snowflake
BigQuery
Azure SQL
Oracle
Amazon Redshift

Files

CSV
Excel
JSON
Parquet

Cloud Storage

Amazon S3
Azure Blob Storage
Google Cloud Storage

Business Apps

Salesforce
HubSpot
SAP
ServiceNow

APIs

REST API
GraphQL

AI Platforms

OpenAI
Anthropic
MCP Servers

How you connect

Connections

Save, test, and manage PostgreSQL database connections your workflows and imports can reuse — credentials encrypted at rest.

Input

The starting point of every workflow. Pick a saved Platform Dataset or configure a PostgreSQL connection to bring data onto the canvas.

Import Wizard

Bring a CSV/XLSX file or a PostgreSQL connection into DataQloo as a reusable dataset, with column profiling before you commit.

02 · Transform

Prepare it any way you need

Clean, combine, and reshape data without writing scripts.

Core transformations available today

FilterSummarizeSort

Expanding continuously

FormulaCleanReplaceSampleJoinUnionLookupAppendBranchGroup ByDeduplicateFuzzy MatchPivotUnpivotWindowRankSQLSub-WorkflowAI TransformPython

Available transformations, in depth

Filter

Narrows a dataset down to the rows that matter with a single condition — equals, contains, greater than, in a list, and more.

Summarize

Groups and aggregates rows — SUM, COUNT, AVG, MIN, MAX, and COUNT DISTINCT — to turn raw rows into a business-readable metric.

Sort

Orders results by a column, ascending or descending, so the most relevant rows surface first.

03 · Reuse

Build once. Reuse it every time the data changes.

Save a workflow’s result as a reusable dataset — the input to another workflow, or a table you rerun in one click instead of rebuilding from scratch. This is one of DataQloo’s biggest differences from a one-off script: the workflow itself is the reusable asset.

Output

The terminal node that saves a workflow's results as a reusable Platform Dataset, so it can be used as the Input to another workflow.

Browse

A terminal node that previews your workflow's results — the table, inferred schema, column profile, generated SQL, and any configuration messages, all in one panel.

04 · Automate

Turn manual, repetitive reporting into one click

This is what makes DataQloo a data automation platform, not just a one-off script: turn a report you rebuild by hand every week into a workflow you rerun on demand today. Scheduled, unattended runs are on the roadmap — see the roadmap for current status. Role-based access keeps automation safe as more of your team relies on it.

Roles & Permissions

Workspace-scoped role-based access control — workspace admin, member, and viewer roles govern who can do what across connections, datasets, and settings.

For data engineering teams:a lot of engineering time goes to fulfilling one-off requests — “filter this by region,” “total this by month.” DataQloo lets teammates build those requests themselves on the canvas, against a connection your team controls, with the underlying query visible to review if you want to. It's not a replacement for your orchestration layer or existing ETL pipelines — see DataQloo vs. Airflow.

05 · Insights

Planned

Gain insights, built on data you already trust

Once your data is connected and prepared, the natural next step is turning it into dashboards, KPIs, and plain-language summaries. Not built yet.

See the roadmap →

06 · AI

Planned

Use AI once your data is connected and trusted

Describe what you want to transform, review the suggested workflow, and approve before anything runs. Nothing executes without you. Not built yet.

See the roadmap →