Last Updated: 5/15/2026

Applications

• How Feldera Customers Slash Cloud Spend (10x and beyond) https://www.feldera.com/blog/how-feldera-customers-slash-cloud-spend 

• Batch Analytics at Warp Speed: A User Guide https://www.feldera.com/blog/warpspeed 

• From Traces to Insights: How to Analyze OpenTelemetry Data in Real-Time with SQL https://www.feldera.com/blog/opentelemetry 

• Solving Fine-Grained Authorization by Turning the Problem on its Head https://www.feldera.com/blog/fine-grained-authorization 

• Where was Waldo (when his card was swiped)? https://www.feldera.com/blog/asof-join 

• Real-time fraud detection using Feldera and Hopsworks https://www.feldera.com/blog/hopsworks 

• Real-time feature engineering with Feldera. Part 2. https://www.feldera.com/blog/feature-engineering-part2 

• Real-time feature engineering is hard (but it doesn’t need to be). Part 1. https://www.feldera.com/blog/feature-engineering-part1 

• Who’s accessing your S3 buckets? SecOps solution using CloudTrail, EventBridge and Feldera https://www.feldera.com/blog/eventbridge-and-feldera 

• How to Continuously Analyze Streaming Data from Redpanda https://www.feldera.com/blog/continuously-analyzing-redpanda-data 

Platform capabilities

• Can your incremental compute engine do this? https://www.feldera.com/blog/can-your-incremental-compute-engine-do-this 

• Introducing Feldera Health https://www.feldera.com/blog/introducing-feldera-health 

• The Babel tower of SQL dialects https://www.feldera.com/blog/the-babel-tower-of-sql-dialects 

• Toward Real-Time Medallion Architecture https://www.feldera.com/blog/medallion-architecture 

• Universal IVM: Incremental View Maintenance for the Modern Data Stack https://www.feldera.com/blog/universal-ivm 

• Feldera: three tools for the price of one https://www.feldera.com/blog/feldera-three-tools-for-the-price-of-one 

• Leverage Object Stores in Feldera Pipelines (S3, Azure Blob, GCS) https://www.feldera.com/blog/leverage-object-stores-in-feldera-pipelines 

• Announcing S3-backed Pipelines https://www.feldera.com/blog/s3-backed-pipelines 

• Implementing Batch Processes with Feldera https://www.feldera.com/blog/batch-processes 

• Fault tolerance technical details https://www.feldera.com/blog/fault-tolerance-technical-details 

• Fault tolerance now in preview! https://www.feldera.com/blog/fault-tolerance-preview 

• Recursive SQL queries in Feldera https://www.feldera.com/blog/recursive-sql-queries-in-feldera 

• Inspecting Feldera pipelines https://www.feldera.com/blog/inspecting-feldera-pipelines 

• Feature Wars: SQL vs DSL for Feature Engineering https://www.feldera.com/blog/feature-wars 

• How to Analyze Unbounded Time-Series Data using Bounded State https://www.feldera.com/blog/time-series 

• Feldera performance on Nexmark versus Flink https://www.feldera.com/blog/nexmark-vs-flink 

• Meet the Feldera storage engine https://www.feldera.com/blog/feldera-storage 

• Rolling Aggregates: the Most Important Feature in Your Real-Time Fraud Detection Pipeline https://www.feldera.com/blog/rolling-aggregates 

• Your Streaming Analytics Use Case Needs More State Than You Think https://www.feldera.com/blog/streaming-needs-storage 

• Let’s make streaming analytics boring https://www.feldera.com/blog/lets-make-streaming-boring 

• What do we mean when we say real-time SQL? https://www.feldera.com/blog/real-time-sql 

• Incremental Computation, a bad case of déjà vu https://www.feldera.com/blog/incremental-computation-deja-vu 

• Feldera input and output connectors https://www.feldera.com/blog/communicating-with-dbsp 

Principles, Implementation, and engineering

• Why incremental aggregates are difficult — part 1 https://www.feldera.com/blog/why-incremental-aggregates-are-difficult---part-1 

• Nobody ever got fired for using a struct https://www.feldera.com/blog/nobody-ever-got-fired-for-using-a-struct 

• Introducing Feldera’s Visual Profiler https://www.feldera.com/blog/introducing-feldera’s-visual-profiler 

• Constant folding in Calcite https://www.feldera.com/blog/constant-folding-in-calcite 

• The Dirty Secret of Incremental View Maintenance: You Still Need Batch https://www.feldera.com/blog/backfill-explained 

• Stream integration https://www.feldera.com/blog/stream-integration 

• Cutting Down Rust Compile Times From 30 to 2 Minutes With One Thousand Crates https://www.feldera.com/blog/cutting-down-rust-compile-times-from-30-to-2-minutes-with-one-thousand-crates 

• The Pain That Is Github Actions https://www.feldera.com/blog/the-pain-that-is-github-actions 

• Correctness at Feldera https://www.feldera.com/blog/correctness-at-feldera 

• LATENESS in streaming programs https://www.feldera.com/blog/lateness-in-streaming-programs 

• Analyzing query performance in Feldera https://www.feldera.com/blog/q12 

• RocksDB: Not A Good Choice for a High-Performance Streaming Platform https://www.feldera.com/blog/rocksdb-not-a-good-choice-for-high-performance-streaming 

• Optimizing Kafka input performance https://www.feldera.com/blog/optimizing-kafka-input-performance 

• Streaming queries without compromise https://www.feldera.com/blog/streaming-queries-without-compromise 

• A synchronous streaming model https://www.feldera.com/blog/synchronous-streaming 

• Incremental Database Computations https://www.feldera.com/blog/incremental-database-computations 

• Indexed Z-sets https://www.feldera.com/blog/Indexed-Zsets 

• Database computations on Z-sets https://www.feldera.com/blog/database-computations-on-z-sets 

• Calcite program representations https://www.feldera.com/blog/calcite-irs 

• Desperately Seeking Kafka https://www.feldera.com/blog/seeking-in-kafka 

• Implementing Z-sets https://www.feldera.com/blog/implementing-z-sets 

• Z-sets - Representing Database Changes https://www.feldera.com/blog/z-sets-representing-database-changes 

• Computing with changes https://www.feldera.com/blog/Changes