osodevops/kafka-connect-salesforce-oss — explained in plain English
Analysis updated 2026-05-18
Stream Salesforce record changes into Kafka in real time as they happen.
Backfill historical Salesforce data and switch smoothly into live streaming.
Write Kafka data back into Salesforce as record updates or platform events.
Migrate an existing Confluent Salesforce connector setup with a verified, no-data-loss process.
| osodevops/kafka-connect-salesforce-oss | akarshsatija/beast | alexeygrigorev/codeforces-solutions-java | |
|---|---|---|---|
| Stars | 1 | 1 | 1 |
| Language | Java | Java | Java |
| Last pushed | — | 2021-02-17 | 2020-10-03 |
| Maintenance | — | Dormant | Dormant |
| Setup difficulty | hard | hard | easy |
| Complexity | 4/5 | 4/5 | 1/5 |
| Audience | ops devops | data | developer |
Figures from each repo's GitHub metadata at analysis time.
Requires a running Kafka Connect worker plus Salesforce API credentials for production use, though local testing needs no real Salesforce org.
This project connects Salesforce and Apache Kafka, a system many companies use to move large streams of data between different parts of their software in real time. It is built as a free, open source alternative to a similar paid connector sold by Confluent, aiming to offer the same core capabilities without a commercial license. In practice, it offers four separate connector pieces. One watches a Salesforce account for changes, such as a new lead or an updated contact, and streams those changes into Kafka as they happen, using Salesforce's modern Pub or Sub API rather than an older method. It can also pull in a full historical snapshot of existing records first, then switch smoothly into live streaming without missing or duplicating anything. Two other connectors write data back into Salesforce from Kafka, either updating standard records or publishing what Salesforce calls platform events, which can trigger automated workflows inside Salesforce itself. A fourth connector supports an older Salesforce streaming method for accounts that do not have access to the newer API. The project pays attention to real world operational concerns: it tracks Salesforce's daily API usage limits and slows itself down before hitting them, it can recover automatically if it temporarily loses its place in the stream of changes, and it can run on any standard Kafka setup, including managed cloud services. It also includes a documented, tested process for migrating an existing Confluent based setup over to this project, including a way to verify afterward that no data was lost in the switch. Developers can test the whole system locally without needing an actual Salesforce account, since the project ships a fake version of Salesforce's APIs for testing. It requires Java 17 or newer and Maven to build from source, and is released under the Apache 2.0 license, making it suitable for companies wanting to avoid vendor lock-in on their Salesforce data pipeline.
An open-source, Apache-2.0 set of Kafka connectors that stream Salesforce data changes in real time and can also write data back into Salesforce.
Mainly Java. The stack also includes Java, Apache Kafka, Kafka Connect.
Apache 2.0 license: free to use, modify, and distribute, including commercially, with patent protection and attribution required.
Setup difficulty is rated hard, with roughly 1h+ to a first successful run.
Mainly ops devops.
This repo across BitVibe Labs
Verify against the repo before relying on details.