Are Snowflake costs soaring because there is a lack of control over your data pipeline? Reduce your costs by only sending the exact data you need to Snowflake, Fivetran, or any other Data Cloud.
Along with native indexing in data science-friendly formatting, Streamdal allows you to operate on and filter your data.
Lower your pipeline costs, Snowflake resource requirements, and reduce bulky transfers.
Save on Snowflake Storage
Using Streamdal as your Data Lake means that you unlock the power of an all-in-one streaming data management platform. Automatically convert any data encoding into human-readable data, stored in Snowflake-friendly parquet format.
Save on Data Transfers To Snowflake
Pipe your data to Streamdal then filter, transform, and push only the data your team needs.
Save on Virtual Warehousing In Snowflake
Reduce the resource requirements and runtime of your queries by only transferring the data you need into Snowflake. Why import the whole payload when only 10% of the data is needed? Reducing the amount of data that needs to be queried means less resources and less warehouse runtime.
An All-In-One Data Platform
Tap Data Streams
See inside any event driven architecture at any scale. Enable teams to deliver complex features faster, less bug-prone, and improve their SLOs.
Anomaly Detection Engine
Detect PII, ensure data uses expected types and has valid contents. Use serverless functions to implement custom anomaly checks on pre-decoded data.
We support a huge, ever-evolving list of integrations for most data-related systems. All integrations have first-class support and are ready for production-grade use.
Define functions in any language to perform complex monitoring tasks, strip sensitive information from in-flight data or create a one-time function to fix data in our Smart DLQ.
Smart Dead Letter Queue
Stage dead-lettered data, perform one-off or mass-fixes using custom functions on pre-decoded data and replay the results to any destination.
Monitor & Alert
See beyond performance metrics, and answer exactly why something is breaking. Give your DevOps teams split second reaction times when things go bad.