Search Results for "create"

Go library for building event-driven applications. Our goal was to create a tool that is easy to understand, even by junior developers. It doesn't matter if you want to do Event-driven architecture, CQRS, Event Sourcing or just stream MySQL Binlog to Kafka. Watermill was designed to process hundreds of thousands of messages per second. Every component is built in a way that allows you to configure it for your needs.

Apache Pulsar is a cloud-native, distributed messaging and streaming platform originally created at Yahoo! and now a top-level Apache Software Foundation project. Easy to deploy, lightweight compute process, developer-friendly APIs, no need to run your own stream processing engine. Run in production at Yahoo! scale for over 5 years, with millions of messages per second across millions of topics. Expand capacity seamlessly to hundreds of nodes. Low publish latency (< 5ms) at scale with strong...

Build applications that respond immediately to events. Craft materialized views over streams. Receive real-time push updates, or pull current state on demand. Seamlessly leverage your existing Apache Kafka® infrastructure to deploy stream-processing workloads and bring powerful new capabilities to your applications. Use a familiar, lightweight syntax to pack a powerful punch. Capture, process, and serve queries using only SQL. No other languages or services are required. ksqlDB enables you...

...DSPatch is not limited to any particular domain or data type, from reactive programming to stream processing, DSPatch's generic, object-oriented API allows you to create virtually any dataflow system imaginable. *See also:* DSPatcher ( https://github.com/MarcusTomlinson/DSPatcher ): A cross-platform graphical tool for building DSPatch circuits. DSPatchables ( https://github.com/MarcusTomlinson/DSPatchables ): A DSPatch component repository.

...By eliminating infrastructure complexity, going from prototype to production has never been simpler. When we set out to build Wally, we had several high-level goals in mind. Create a dependable and resilient distributed computing framework. Take care of the complexities of distributed computing "plumbing," allowing developers to focus on their business logic. Provide high-performance & low-latency data processing. Be portable and deploy easily (i.e., run on-prem or any cloud). Manage in-memory state for the application. ...

Azure Cosmos DB Spark is the official connector for Azure CosmosDB and Apache Spark. The connector allows you to easily read to and write from Azure Cosmos DB via Apache Spark DataFrames in Python and Scala. It also allows you to easily create a lambda architecture for batch-processing, stream-processing, and a serving layer while being globally replicated and minimizing the latency involved in working with big data.