Apache ActiveMQ Reviews

Temporal Reviews

Apache ActiveMQ mentions (7)

• Why Kafka? A Developer-Friendly Guide to Event-Driven Architecture

  Before Kafka, traditional message queues like RabbitMQ and ActiveMQ were widely used, but they had limitations in handling massive, high-throughput real-time data streams. - Source: dev.to / over 1 year ago

• Hosting Services – The Short and Mid-Term Solution Before Transition to the Public Cloud

  Consume open-source queuing services – customers can deploy message brokers such as ActiveMQ or RabbitMQ, to develop asynchronous applications, and when moving to the public cloud, use the cloud providers managed services alternatives. - Source: dev.to / over 1 year ago

• Top 6 message queues for distributed architectures

  Apache ActiveMQ is an open-source Java-based message queue that can be accessed by clients written in Javascript, C, C++, Python and .NET. There are two versions of ActiveMQ, the existing “classic” version and the next generation “Artemis” version, which is currently being worked on. - Source: dev.to / about 3 years ago

• Data Engineering and DataOps: A Beginner's Guide to Building Data Solutions and Solving Real-World Challenges

  For real-time streaming, we have other frameworks and tools like Apache Kafka, ActiveMQ, and AWS Kinesis. - Source: dev.to / over 3 years ago

• Interview for JetBrains: Why Localazy developers ️ Kotlin?

  The back-end is designed as a set of microservices communicating through a message broker, ActiveMQ, with a custom configuration to support delayed delivery and other features. - Source: dev.to / about 4 years ago

Temporal mentions (17)

• Temporal in Production: Sharp Edges & Good Practices

  When a team moves from a monolith into microservices and event-driven, asynchronous systems, it inherits a class of problems that used to be someone else's: work that fails halfway through, steps that must not run twice, calls that return before the work is done. Temporal is a durable execution engine that handles a lot of this - you define a multi-step process, and it guarantees the process runs to completion... - Source: dev.to / 16 days ago

• Your Agent Bills While It Waits. Here's the Fix.

  Durable execution — the pattern implemented by Temporal, Inngest, Rivet Actors, and now Cloudflare Workflows — treats waiting as a continuation rather than a loop:. - Source: dev.to / 21 days ago

• Compiler as Custodian

  Two specific moves stand out in Duncan's account. The first is durable execution, via Temporal — Mercury replaced fragile cron-and-database state machines with workflow code whose failure semantics are platform-handled (replay, retry, timeout, cancellation). Mercury open-sourced its hs-temporal-sdk, which wraps Temporal's official Rust Core SDK via FFI and provides a Haskell-native API. The dovetail with Haskell's... - Source: dev.to / about 2 months ago

• How we turned our workflow editor into a real SDK

  We picked Temporal as the first reference engine on purpose. Temporal has the strictest execution model we know of – a V8 sandbox, determinism constraints, replay-driven recovery. If our port contract holds up against that, easier engines – an in-memory test double, a BullMQ queue, or JSON-first platforms like Inngest or Restate – plug in through the same two interfaces. We're shipping Temporal first; the rest is... - Source: dev.to / 2 months ago

• Three days debugging a missing trace

  The trick is to find whatever metadata channel the queue already gives you and use that and thankfully, almost every mature queue has one (probably because of this scenario). SQS has message attributes, Temporal has context propagators built into the SDK, and Hatchet (which we use to run our workflows) has a metadata field called additionalMetadata. - Source: dev.to / 4 months ago