Streaming Data Integration for On-Prem and Cloud
Striim Platform makes it easy to ingest, process, and deliver real-time data across diverse environments in the cloud or on-premise, helping you rapidly adopt a modern data architecture.
An End-to-End Platform
Connect with your Data
Real-time data integration starts with our wizards. You can search and select from hundreds of templates to simplify building data flows.
The wizard will then lead you through the process of connecting to your source. As part of this process it will verify the source is configured correctly. In the case of CDC source, the verification includes permissions, and checking the database is set up to support CDC.
Control it like never before
The end result of a wizard is a data flow application – you can also create data flows from scratch. The data flow defines how to collect, process, and deliver data. The simplest data flow just has a source, a stream, and a target.
This is suitable for use-cases where the data being delivered to the target is the same as the source. However, in many cases you will need to perform some processing on that data. This is achieved through continuous SQL queries optimized for streaming, real-time data.
Understand the journey
Striim can also validate that it has been delivered and provide visibility into the end-to-end lag. This level of visibility is essential for mission-critical systems that may have SLAs regarding how current the data is.
You can also drill down on any of the components in a data flow to see detailed statistics that includes read/write rate, lag, latency, cpu usage and many other metrics.
Alert and automate
Striim offers out-of-the-box alerts that can be configured for a variety of metrics, keeping you up to date on the status and performance of your data flows.
In the case of errors, or failures, you can also automate workflows to perform corrective actions. By tapping into error or status streams you can trigger compensating data flows to start, or perform other actions to remediate problems.