eSmiley to Databricks integration

Connect eSmiley to Databricks and automatically sync your application data. Weld extracts data from eSmiley, loads it into Databricks, and lets you transform the data using SQL or dbt, no custom scripts required.

4.8 on G2
eSmileySource
WeldWeld
DatabricksWarehouse
Weld · New sync
eSmileySourceeSmileyConnected
Tables to sync
  • registration31 cols
  • account19 cols
  • registration_point16 cols
  • Extract
  • Load
  • Keep in sync
DatabricksDestinationDatabricksReady
esmiley schema
  • esmiley.registrationSynced
  • esmiley.accountSyncing
  • esmiley.registration_pointSynced
eSmiley tables
3
fields, typed
66
relationships kept
3
agent context included
MCP

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How it works

How to set up eSmiley to Databricks in Weld.
In the app, with the API or an agent.

Weld · New eSmiley sync
eSmileyNew connectioneSmileyAuthorised
Connection nameesmiley
AuthorizeOpens eSmiley to grant read access
Use cases

Why sync eSmiley to Databricks?
Ready for analysis.

Centralizing your eSmiley data in Databricks lets you join it with other data sources for cross-platform analytics and deeper insights.

Build reliable dashboards and reports by querying eSmiley data directly in Databricks using SQL or your preferred BI tool.

  • Centralized data warehouse

    Bring eSmiley data into Databricks alongside other sources to create a single source of truth for your organization.

  • Automated reporting

    Replace manual exports and spreadsheet-based reporting with automated pipelines from eSmiley to Databricks. Connect BI tools like Looker, Metabase, or Power BI.

Schema

What data can you sync?
Every eSmiley table, keys intact.

Weld syncs the objects the eSmiley connector exposes into Databricks, and you choose which tables and fields to include. The connector's docs list what is available.

Open the schema explorer
All 3 tables
  • registration
  • account
  • registration_point
Weld MCP server

Ask your agent.
It queries Databricks for you.

Connect Claude, Cursor, ChatGPT or your own agent to Weld over MCP. It reads the eSmiley context, finds the tables it needs and runs the query in Databricks.

Claude CodeOpus 5
>

How many registration_point rows do we have per account? Use our eSmiley data in Databricks.

Reading the eSmiley context first, so the query uses the right tables and keys.

●weld·search_available_references
⎿raw.esmiley.registration_point
raw.esmiley.account
+ 1 more eSmiley tables
●weld·get_reference_schema
⎿registration_point · 16 columns
joins account on account_id
●weld·run_query
⎿select a.id, count(*) from {{raw.esmiley.registration_point}} r
join {{raw.esmiley.account}} a on r.account_id = a.id
group by 1
submitted
●weld·get_query_status
⎿DONE
●weld·get_query_result
⎿rows returned
✓Answered from eSmiley data in Databricks
>Ask about your eSmiley data
Under the hood

Technical considerations.
What to expect.

Incremental syncing
Weld uses incremental syncing where supported by the eSmiley API, loading only new and updated records to minimize data transfer and warehouse costs.
Schema handling
Weld automatically manages schema changes. If eSmiley adds new fields, they're detected and added to the corresponding Databricks tables.
Data freshness
Sync frequency depends on your Weld plan. Most connectors support schedules from every 5 minutes up to daily intervals.
Security
All data is encrypted in transit (TLS) and at rest. Weld is SOC 2 Type II compliant and supports IP whitelisting for database connections.
FAQ

Common questions.
About eSmiley to Databricks.

Start syncing eSmiley to Databricks.

Set up your eSmiley data pipeline in minutes. No credit card required. Free for 14 days.

eSmileySource
WeldWeld
DatabricksWarehouse