Amazon Kinesis VS Apache Beam

Amazon Kinesis Reviews

Apache Beam Reviews

Amazon Kinesis mentions (22)

• AWS DEV OPS Professional Exam short notes

  When you see Amazon Kinesis as an option, this becomes the ideal option to process data in real time. Amazon Kinesis makes it easy to collect, process, and analyze real-time, streaming data so you can get timely insights and react quickly to new information. Amazon Kinesis offers key capabilities to cost effectively process streaming data at any scale, along with the flexibility to choose the tools that best suit... - Source: dev.to / about 2 months ago

• Querying microservices in real-time with materialized views

  RisingWave is an open-source streaming database that has built-in fully-managed CDC source connectors for various databases, also it can collect data from other sources such Kafka, Pulsar, Kinesis, or Redpanda and it allows you to query real-time streams using SQL. You can get a materialized view that is always up-to-date. - Source: dev.to / about 1 year ago

• How Streaming database differs from a Traditional database?

  For example, RisingWave is one of the fastest-growing open-source streaming databases that can ingest data from Apache Kafka, Apache Pulsar, Amazon Kinesis, Redpanda, and databases via native Change data capture connections or using Debezium connectors to MySQL and PostgreSQL sources. Previously, I wrote a blog post about how to choose the right streaming database that discusses some key factors that you should... - Source: dev.to / about 1 year ago

• Query Real Time Data in Kafka Using SQL

  RisingWave is an open-source distributed SQL database for stream processing. RisingWave accepts data from sources like Apache Kafka, Apache Pulsar, Amazon Kinesis, Redpanda, and databases via native Change data capture connections to MySQL and PostgreSQL sources. It uses the concept of materialized view that involves caching the outcome of your query operations and it is quite efficient for long-running stream... - Source: dev.to / about 1 year ago

• How to choose the right streaming database

  You can ingest data from different data sources such as message brokers Kafka, Redpanda, Kinesis, Pulsar, or databases MySQL or PostgreSQL using their Change Data Capture (CDC) which is the process of identifying and capturing data changes. - Source: dev.to / about 1 year ago

Apache Beam mentions (14)

• Ask HN: Does (or why does) anyone use MapReduce anymore?

  The "streaming systems" book answers your question and more: https://www.oreilly.com/library/view/streaming-systems/9781491983867/. It gives you a history of how batch processing started with MapReduce, and how attempts at scaling by moving towards streaming systems gave us all the subsequent frameworks (Spark, Beam, etc.). As for the framework called MapReduce, it isn't used much, but its descendant... - Source: Hacker News / 3 months ago

• How do Streaming Aggregation Pipelines work?

  Apache Beam is one of many tools that you can use. Source: 5 months ago

• Real Time Data Infra Stack

  Apache Beam: Streaming framework which can be run on several runner such as Apache Flink and GCP Dataflow. - Source: dev.to / over 1 year ago

• Google Cloud Reference

  Apache Beam: Batch/streaming data processing 🔗Link. - Source: dev.to / over 1 year ago

• Composer out of resources - "INFO Task exited with return code Negsignal.SIGKILL"

  What you are looking for is Dataflow. It can be a bit tricky to wrap your head around at first, but I highly suggest leaning into this technology for most of your data engineering needs. It's based on the open source Apache Beam framework that originated at Google. We use an internal version of this system at Google for virtually all of our pipeline tasks, from a few GB, to Exabyte scale systems -- it can do it all. Source: over 1 year ago