Send data from Clockify to SQL Server

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Send Clockify Data to SQL Server

Connecting Clockify to SQL Server takes just minutes with Kondado’s no-code platform. Select your data source, authenticate your account, and choose SQL Server as your destination. You can then pick which pipelines to enable and set your preferred update frequency, whether every 5 minutes or daily. The automated process handles the data transfer so your time tracking information flows directly into your database without manual exports or engineering resources.

Once your data lands in SQL Server, you can combine Clockify time tracking with financial records, CRM data, or project management information from other sources. This creates a unified analytics environment where you can build custom reports analyzing billable hours, project profitability, and team productivity. Analysts can query the replicated data using standard SQL to generate insights that drive better resource allocation and client billing decisions.

Kondado provides automated data replication between Clockify and SQL Server, delivering workspace configuration and project billing data on a configurable schedule without requiring manual exports or technical setup.

Our prices start from $19 USD/month, and you can try Kondado for free for 14 days with no credit card required

Available Clockify Pipelines for SQL Server

The Workspaces pipeline delivers organizational settings including admin permissions, week start configurations, and default hourly rates directly into your SQL Server database. Meanwhile, the Projects pipeline captures billable status indicators, time estimates, and project categorizations that enable sophisticated profitability analysis. With this data in SQL Server, you can join Clockify records with accounting system tables to calculate actual versus estimated hours, identify budget overruns early, and generate client invoices based on precise time entries stored in your own environment. This setup supports complex SQL queries that blend time tracking with financial metrics for comprehensive agency management.

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Clockify data available for SQL Server

2
available pipelines
115
extractable fields

Available integrations

Integration Description
Workspaces Includes fields such as id, name, and admin permissions, along with settings like week start time and hourly rate.
Projects Contains information such as id, name, color, and whether the project is billable, along with details about time estimate and hourly rate.
Workspaces
Includes fields such as id, name, and admin permissions, along with settings like week start time and hourly rate.
Projects
Contains information such as id, name, color, and whether the project is billable, along with details about time estimate and hourly rate.
See all available data →

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How to send Clockify data to SQL Server

Sync data automatically — no code, no manual exports.

1
Add Your Clockify Account

Navigate to the data sources section and select Clockify from the available options. Enter your API credentials to establish the connection and grant access to your workspace and project information.

2
Configure SQL Server Destination

Enter your SQL Server connection details including server address, database name, and authentication credentials. Specify the target schema where your Clockify pipelines will reside, ensuring proper access permissions for automated data loading.

3
Select Pipelines and Schedule

Choose which pipelines to enable from the available Workspaces and Projects options, then set your update frequency to every 5 minutes, hourly, or daily. Activate the replication to begin automated data transfers that keep your SQL Server database synchronized with your latest time tracking records.

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Send data from Clockify to other destinations

Looker Studio

Clockify > Looker Studio
Power BI

Clockify > Power BI
Other visualizations
Other visualizations
Amazon S3

Clockify > Amazon S3
BigQuery

Clockify > BigQuery
Excel

Clockify > Excel
Google Sheets

Clockify > Google Sheets
MySQL

Clockify > MySQL
PostgreSQL

Clockify > PostgreSQL
Redshift

Clockify > Redshift
SQL Server

Clockify > SQL Server

Choose a tool to visualize your Clockify data

If the software you need is not listed, drop us a messagem. You can use almost every tool

Airtable
Clockify > Airtable
Alteryx
Clockify > Alteryx
Amazon Quicksight
Clockify > Amazon Quicksight
BIMachine
Clockify > BIMachine
Cortex
Clockify > Cortex
Data Studio
Clockify > Data Studio
Geckoboard
Clockify > Geckoboard
Grafana
Clockify > Grafana
IBM Cognos Analytics
Clockify > IBM Cognos Analytics
Klipfolio
Clockify > Klipfolio
Looker Studio
Clockify > Looker Studio
Looker
Clockify > Looker
Looqbox
Clockify > Looqbox
Metabase
Clockify > Metabase
Microstrategy
Clockify > Microstrategy
Pentaho
Clockify > Pentaho
Power BI
Clockify > Power BI
Qlik Cloud Analytics
Clockify > Qlik Cloud Analytics
Qlik Sense
Clockify > Qlik Sense
Qlik
Clockify > Qlik
QlikView
Clockify > QlikView
Redash
Clockify > Redash
Superset
Clockify > Superset
Tableau
Clockify > Tableau
BI TOTVS
Clockify > BI TOTVS
Zoho Analytics
Clockify > Zoho Analytics

Frequently Asked Questions (FAQ)

Answers about sending Clockify data to SQL Server automatically

How does Kondado replicate Clockify data to SQL Server without coding? ▼
Kondado uses a direct connection to the Clockify API to extract workspace and project information, then loads it into your SQL Server instance through standard database protocols. You configure the connection through a visual interface by selecting your data source and destination, then mapping the available pipelines to your database schema. The platform handles authentication, data type conversion, and automated updates based on your chosen schedule.
What Clockify data fields are available in SQL Server through Kondado? ▼
Kondado makes 115 fields available across two pipelines: Workspaces includes identifiers, names, admin permissions, week start times, and hourly rates, while Projects contains IDs, names, colors, billable flags, time estimates, and billing rates. These fields arrive as structured columns in SQL Server, ready for joins with your existing business tables. You can query project profitability, filter by workspace settings, or analyze time allocation using standard T-SQL commands.
How often can I update Clockify data in my SQL Server database? ▼
You can configure replication to run every 5 minutes, 15 minutes, hourly, or daily depending on your reporting needs and data freshness requirements. Near-real-time updates every 5 minutes work well for live project dashboards, while daily syncs suit monthly billing reconciliation processes. The schedule runs automatically once configured, keeping your SQL Server environment current without manual intervention.
Can I combine Clockify time tracking data with other business sources in SQL Server? ▼
Yes, SQL Server acts as a central repository where Clockify records can join with information from your CRM, accounting software, or project management tools. Create unified views that connect billable hours to client revenue, or send consolidated datasets to Power BI or Looker Studio for executive dashboards. This blending enables cross-functional analysis that isolated time tracking cannot provide, showing true project costs alongside time investments.
What data types does Clockify data use when stored in SQL Server? ▼
Kondado converts Clockify API fields into appropriate SQL Server data types such as VARCHAR for project names and workspace identifiers, DECIMAL for hourly rates and time estimates, and BIT fields for boolean values like billable status indicators. Date and timestamp fields maintain proper datetime formats for accurate time-series analysis. This standardization ensures your existing SQL queries, stored procedures, and reporting tools work seamlessly with the replicated time tracking data.
Do I need to manually create database structures in SQL Server before replicating Clockify data? ▼
No, Kondado automatically provisions the necessary database structure for your selected pipelines when you first configure the replication. The platform creates columns matching Clockify's field structure, including proper data types and indexing recommendations for the Workspaces and Projects pipelines. You can customize destination names and schema organization to fit your existing data warehouse standards.
Can I send Clockify data to SQL Server and other destinations simultaneously? ▼
Yes, you can replicate the same Clockify datasets to multiple destinations including BigQuery, PostgreSQL, or Google Sheets while maintaining your SQL Server instance. This multi-destination approach lets analysts use SQL Server for complex T-SQL analysis while marketers access high-level metrics in spreadsheets. Each destination maintains independent update schedules tailored to specific team needs.

Try out all the features for free for 14 days