BridgeQL is a SQL-Graph hybrid query language built in Rust for enterprise Salesforce. Connect unlimited orgs and query them as if they were one database. No ETL. No data warehouse. Real-time results.
You didn't plan to have dozens of Salesforce orgs. But M&A, regional compliance, and sandbox sprawl got you here.
Every acquisition brings more orgs. Each with different schemas, data quality, and conventions.
EMEA, APAC, Americas each have their own orgs. Finance wants a unified pipeline report. Good luck.
Data warehouses are expensive and stale. ETL pipelines are fragile. MuleSoft costs more than Salesforce.
Standard SQL syntax combined with graph traversal patterns. Designed specifically for Salesforce's relationship-heavy data model.
SELECT, JOIN, WHERE, GROUP BY, ORDER BY. No learning curve. Just point it at your orgs.
SELECT Name, Industry, AnnualRevenue FROM Account WHERE Industry = 'Technology' ORDER BY AnnualRevenue DESC LIMIT 100
Cypher-inspired syntax for traversing relationships. Express complex multi-hop queries that would be painful in SQL.
MATCH (a:Account)-[:HAS_CONTACT]->(c:Contact) -[:OWNS]->(o:Opportunity) WHERE a.Name = 'Acme Corp' RETURN c.Name, o.Name, o.Amount
The @org prefix lets you query across org boundaries. JOINs, UNIONs, and aggregations work exactly as you'd expect.
-- Find accounts in prod but not sandbox SELECT p.Name, p.Industry FROM @prod.Account p LEFT JOIN @sandbox.Account s ON p.External_ID__c = s.External_ID__c WHERE s.Id IS NULL -- Aggregate pipeline across all regions SELECT Region, SUM(Amount) AS Pipeline FROM ( SELECT 'Americas' AS Region, Amount FROM @americas.Opportunity UNION ALL SELECT 'EMEA', Amount FROM @emea.Opportunity UNION ALL SELECT 'APAC', Amount FROM @apac.Opportunity ) GROUP BY Region
Zero-copy. Real-time. No data movement required.
If you have more than one Salesforce org, you have these problems.
Unified pipeline dashboards across all regions without a data warehouse.
Identify duplicates, map records, and plan mergers across orgs.
Assess acquired org data quality and schema differences before integration.
Query across orgs to find PII, verify data residency, track access patterns.
Intelligent sync between production and lower environments with field masking.
Quickly identify data and schema differences between environments.
We didn't find a tool that could query across Salesforce orgs the way we needed. So we built one from scratch.
No crashes, no buffer overflows. The compiler catches memory bugs before they reach production.
10x faster than Python/Java for parsing and transformation. Critical when processing millions of records.
Async execution across multiple orgs simultaneously. Fearless concurrency without data races.
If it compiles, it works. Rust's type system catches entire categories of bugs at compile time.
Let us show you how it works with your Salesforce environment.
Request Demo tyler@colbysdatamovers.com