Amazon Elasticsearch Service VS Apache Flink

This change triggered a response from Amazon Web Services, which offered OpenSearch (data store and search engine) and OpenSearch Dashboards (visualization and user interface) as Apache2.0 licensed open-source projects. - Source: dev.to / 2 months ago

Amazon OpenSearch Service allows you to deploy a secured OpenSearch cluster in minutes. - Source: dev.to / 9 months ago

If yes to these, then OpenSearch is where you are looking. I rarely ever use OpenSearch on its own but usually pair it with DynamoDB. The performance of DDB and the power of searching with OpenSearch make a nice combination. And as with most things with Serverless, pick the right tool for the job. And when it comes to Data, there are so many choices because each one of these is specific to the problem it solves. - Source: dev.to / 10 months ago

Have you looked into Amazon OpenSearch Service (https://aws.amazon.com/opensearch-service/)? You should be able to load the log files into that service and then query it there. Should simplify things a lot. Source: about 1 year ago

Elasticsearch (analytics) An open-source, real-time distributed search and analytics engine used for full-text search, structured search, and analytics. OpenSearch was developed by the Elastic company. Amazon OpenSearch Service (OpenSearch Service) is an AWS-managed service for deploying, operating and scaling OpenSearch in the AWS Cloud. Https://aws.amazon.com/opensearch-service/. - Source: dev.to / over 1 year 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 / 15 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 / 4 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 / 4 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 / 4 months ago