Pusher VS Apache Flink

Pusher Reviews

Apache Flink Reviews

Pusher mentions (50)

• Build a nice Realtime notification with Laravel Jetstream (InertiaJS / Vue 3 stack).

  Now let's push the notification to pusher. First you have to go to Https://pusher.com/ login create an app an get API keys. Then fill them in your .env file. - Source: dev.to / 14 days ago

• A list of SaaS, PaaS and IaaS offerings that have free tiers of interest to devops and infradev

  Pusher.com — Realtime messaging service. Free for up to 100 simultaneous connections and 200,000 messages/day. - Source: dev.to / 3 months ago

• Chat system sockets vs ajax?

  Another tool is pusher but have a high cost https://pusher.com/. Source: 5 months ago

• Custom vs. off-the-shelf React web notification systems: Which is better?

  Pusher specializes in realtime WebSockets and offers a straightforward way to integrate realtime features into your React app. It's a reliable choice for apps that need to send notifications based on realtime events. - Source: dev.to / 7 months ago

• Is this a viable approach to a chat microservice?

  Why are you considering building your own websocket service instead of using something like https://pusher.com/ ? Source: 10 months ago

Apache Flink mentions (27)

• Top 10 Common Data Engineers and Scientists Pain Points in 2024

  Data scientists often prefer Python for its simplicity and powerful libraries like Pandas or SciPy. However, many real-time data processing tools are Java-based. Take the example of Kafka, Flink, or Spark streaming. While these tools have their Python API/wrapper libraries, they introduce increased latency, and data scientists need to manage dependencies for both Python and JVM environments. For example,... - Source: dev.to / 26 days ago

• Choosing Between a Streaming Database and a Stream Processing Framework in Python

  Other stream processing engines (such as Flink and Spark Streaming) provide SQL interfaces too, but the key difference is a streaming database has its storage. Stream processing engines require a dedicated database to store input and output data. On the other hand, streaming databases utilize cloud-native storage to maintain materialized views and states, allowing data replication and independent storage scaling. - Source: dev.to / 3 months ago

• Go concurrency simplified. Part 4: Post office as a data pipeline

  Also, this knowledge applies to learning more about data engineering, as this field of software engineering relies heavily on the event-driven approach via tools like Spark, Flink, Kafka, etc. - Source: dev.to / 5 months ago

• Five Apache projects you probably didn't know about

  Apache SeaTunnel is a data integration platform that offers the three pillars of data pipelines: sources, transforms, and sinks. It offers an abstract API over three possible engines: the Zeta engine from SeaTunnel or a wrapper around Apache Spark or Apache Flink. Be careful, as each engine comes with its own set of features. - Source: dev.to / 5 months ago

• Getting Started with Flink SQL, Apache Iceberg and DynamoDB Catalog

  Due to the technology transformation we want to do recently, we started to investigate Apache Iceberg. In addition, the data processing engine we use in house is Apache Flink, so it's only fair to look for an experimental environment that integrates Flink and Iceberg. - Source: dev.to / 5 months ago