The Feldera Blog
An unbounded stream of technical articles from the Feldera team
LATENESS in streaming programs
Designing a new programming language is fraught with peril. Reusing an existing language, especially a well-known language, is always preferable. Streaming systems started by designing custom languages, but gradually adopted SQL for stream processing. An important goal in adapting SQL for stream processing is to minimally modify SQL such that standard SQL programs have the exact same behavior as in normal databases. In this post we have presented a type annotation called LATENESS which can be used to filter out of order data, and we have given a very precise definition of its behavior.
Incremental Update 7
Log Endpoints, N-Way Merging, and More! A quick overview of what's new in v0.27.
A year of magic
Announcing our rebrand, new website, and introducing Fred.
Where was Waldo (when his card was swiped)?
What was the stock price at the exact moment of the transaction? How far was the credit card swiped from the last known user's location at the time of purchase? What was the account balance just before the money transfer? These types of queries are common in time series analytics problems, such as real-time fraud detection. Such queries can be expressed in SQL using a specialized form of the join operator, the as-of join.
Incremental Update 6 at Feldera
We’re excited to announce the release of v0.26, which represents a significant step forward for Feldera. This release includes over 200 commits, adding 25,000 lines of new code and documentation. Let's dive into the highlights!
Feldera performance on Nexmark versus Flink
Feldera is up to 6.2X faster than Flink for Nexmark queries
Incremental Update 5 at Feldera
A quick overview of what's new in v0.25.
Analyzing query performance in Feldera
Profiling tools offer a scientific approach to performance.
Incremental Update 4 at Feldera
A quick overview of what's new in v0.24.