Sync
Salesforce → Snowflake
Full load on the first run, then incremental merges on LastModifiedDate. Tables and types are created for you.
lht · open source · Apache 2.0
Your warehouse is your data platform.
Salesforce is a view into it. lht keeps them in sync, in both directions, on infrastructure you already own. Bring Your Own Data Warehouse.
$ pip install lht
Salesforce data needs a home
Anyone who has spent meaningful time with Salesforce knows the challenges with data. We built lht to close that gap.
Our clients don't want to go all-in on the Salesforce ecosystem just to make Salesforce fit, and many can't afford to. They don't want Data Cloud's consumption pricing and the surprise bills that can come with it, or MuleSoft, which is complex to deploy and needs a dedicated team to run.
Use the warehouse you already own
Using the warehouse they already own, my team and I have delivered truly disruptive capabilities for our customers at a fraction of the cost of the conventional tools.
- Open source. Read it, run it, fork it. Apache 2.0.
- Runs on your infrastructure. Your credentials, your schedule. Your data never passes through us.
- Built on the Salesforce Bulk API 2.0. Large objects move without burning through your API limits.
What lht does
Reverse ETL
Snowflake → Salesforce
Upsert, insert, update or delete Salesforce records from any Snowflake SELECT: scores, enrichment, cleanup.
Merge
Dedupe inside Salesforce
Find duplicates with SQL, then merge Accounts, Contacts or Leads in Salesforce, with a dry run first.
Get started in minutes
lht needs Python 3.9 or newer, a Salesforce app with OAuth, and a Snowflake user with a key pair.
# install
pip install lht
# save your connections (prompts for each value)
lht create-connection --snowflake
lht create-connection --salesforce
# sync an object; run it again to load only what changed
lht sync --sobject Account --table ACCOUNT --schema RAWComing next: visualization and AI
lht also opens the door to powerful data visualization and AI on your Salesforce data. We'll publish examples of how the Lakehouse Tools team does this in the coming months.
To hear when they're out, watch the GitHub repo or follow Announcements.
Try lht
Download it, tell us what you think, and contribute code if you can. We'd love to hear your success stories.