Based on our record, ifttt should be more popular than Apache Flink. It has been mentiond 179 times since March 2021. We are tracking product recommendations and mentions on various public social media platforms and blogs. They can help you identify which product is more popular and what people think of it.
What I've done instead is, for any recurring event that isn't really due on that date, like "book a haircut" or "fertilize roses", I add an event on a Google Calendar called "Tickler" with the desired recurrence. I then have an IFTTT (https://ifttt.com/explore) integration that creates a Todoist event in my inbox whenever that event shows up on my calendar. It doesn't show up with a due date so I can schedule it... Source: 11 months ago
Or head to the Explore page and see if anything grabs your attention. Source: about 1 year ago
Slack has a feature to schedule messages, also a bunch of bots that do various scheduling tasks… Also you could use a email marketing tool like Mailchimp that could allow you scheduling Mails far a head. But any service you choose should be around somewhat longterm right? It will probably require some money and a bit of luck for the service or app of choice to stay around for a while. So ideally something relying... Source: over 1 year ago
I don’t know about the air tag nativity, which it probably does. But you can do that with any smartphone they has gps; with an app / website called ifttt. Source: over 1 year ago
There's also some automation that you can do with something like https://ifttt.com/explore. Source: over 1 year ago
You should let the Apache Flink team know, they mention exactly-once processing on their home page (under "correctness guarantees") and in their list of features. [0] https://flink.apache.org/ [1] https://flink.apache.org/what-is-flink/flink-applications/#building-blocks-for-streaming-applications. - Source: Hacker News / 4 days ago
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 / about 1 month ago
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
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
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
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