Very happy with its offers, it has a full suite of tools. Also the user experience is great. I am not sure about the privacy though. I am not confident enough to use it for sending and receiving confidential documents.
I used to use Gmail until 4 months ago. I was really happy with this mail, it is easy to handle and, being a Google member, there are many tools available to use. However, I started to learn about the security and privacy offered by Google, which is NONE. We are selling our information and personal data to a technological giant and, many times, we are not even aware of it.
This is why I deleted all but one of my Google-related accounts. As most people are still not aware of this, when working or contacting certain people for the first time, it is essential to do it through Gmail.
Today, there are a few alternatives to solve this lack of privacy. After doing an intensive search and reading comments, I decided to get an account with Mailfence and, honestly, I'm very happy with their service. It's an easy to use email, with end-to-end encryption, digital signatures, calendar, document saving capabilities, ... I really recommend it for all those who are starting in the world of privacy and security. The best thing is that you can create a free account and, if you are happy with the service or need more storage space, you can switch to a paid account.
I hope my opinion helps everyone, especially those who are thinking about whether it is really worth giving all our information in exchange for a free email.
Based on our record, Apache Flink seems to be more popular. It has been mentiond 27 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.
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 / 28 days 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
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
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