Samsara customers can collect vast amounts of data and gain valuable insights into their connected operations using Samsara’s dashboard, Open APIs, and Webhooks. Integrating, replicating, and streaming this data to other systems is possible but can require work. You might have to export CSV files from the Samsara dashboard and import them into other systems manually, or you might have to engage technical resources to write code against Samsara’s APIs and Webhooks. Samsara’s Data Connectors make this easy to accomplish via plug-and-play UI-driven connections that don’t require arduous manual processes or heavy investments in technical resources. There are 4 distinct types of connectors that are tailored to your different needs.Documentation Index
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Power BI Connector
For your organization’s data analytics and data visualization needs, you may use Power BI. Power BI can install Power Query Connectors to access data from different systems, such as Samsara, right within Power BI. Samsara offers a plug-and-play Power BI Connector that allows you to directly connect your Samsara data with Power BI without needing to write any code. Learn more about the connector here.Kafka Streaming Connector
For your organization’s data streaming needs, you may use Kafka. Kafka is a data streaming solution that allows you to consume dense data in real-time, especially dense data such as asset locations. Samsara offers a Kafka Connector that allows you to stream your Samsara operations data in real-time to easily build a historical data lake that can enable you to run AI/ML models, power real-time analytics, and enable custom applications. Learn more about the connector here. Additional Details- A Kafka cluster comprises servers known as brokers that manage and store streamed data.
- In this setup, data is organized into topics, which serve as distinct categories or feeds. Typically, each type of data has its own topic, allowing for a structured and organized data streaming environment. Each topic is further divided into partitions to enable parallel processing, with each partition potentially hosted on different brokers for enhanced distribution and scalability.
- Producers (including Samsara’s Kafka Connector) publish data to specific topics, and consumers (e.g., downstream databases or apps) subscribe to topics to retrieve and process the data. This framework facilitates real-time data processing, efficiently managing high throughput with low latency, and providing a well-organized, scalable platform for handling streaming data.
- For a deeper dive on these concepts, read this article.
| Serverless-like Kafka | Kafka as a Service | Self-managed Kafka | Local Kafka |
|---|---|---|---|
| Upstash Apache Kafka | Confluent Cloud | Confluent Platform | Test Containers |
| Amazon MSK Serverless | Red Hat Openshift Streams | Red Hat AMQ Streams (Strimzi) | Quarkus Dev Services (Red Panda) |
| Heroku Apache Kafka | Cloudera Data Platform | EmbeddedKafkaCluste |