MySQL VS Apache Flink

MySQL Reviews

Apache Flink Reviews

MySQL mentions (4)

• I have a recurring issue with a MySQL DB where I continually run out of disk space due to logs being filled. I've tried everything I can think of. Can anyone think of anything else I should try?

  So, I did a quick read through the mysql reference and found a bunch of flush related commands. I tried:. Source: 11 months ago

• MMORPG design resources

  MySQL: Any SQL or DB knock-off, really... mysql.com - mariadb.org - sqlite.org. Source: over 1 year ago

• Probably a syntax error

  15 years and five strokes ago. I was a Unix sysadmin. ALthough I was never an actual programmer, I did maintenance/light enhancement for the organization's website, in php. Now, as self-administered cognative therapy, I'm going back to it. This is an evil HR application that uses the mysql.com employees sample database. The module below enables the evil HR end user to generate a list of the oldest workers so... Source: almost 3 years ago

• An absolute nightmare with mysql 8.0.25

  I always use the packages from mysql.com, that way I don't have to deal with strange configuration stuff along those lines, but anyway, I'm afraid I'm out of ideas. Surely someone else would have run in to the same issue here though. Source: almost 3 years 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 / 25 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