Based on our record, DynamoDB should be more popular than Apache Spark. It has been mentiond 104 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.
DynamoDB is a powerful NoSQL database provided by AWS, designed to handle large amounts of data efficiently. However, for newcomers, understanding the nuances of querying DynamoDB tables can be challenging, particularly when it comes to the differences between KeyConditionExpression and FilterExpression. This blog post aims to clarify these concepts and provide practical examples of their usage. - Source: dev.to / 8 days ago
Event Producers: Generate streams of events, which can be implemented using straightforward microservices with AWS Lambda (for serverless computing), Amazon DynamoDB Streams (to captures changes to DynamoDB tables in real-time), Amazon S3 Event Notifications (Notify when certain events occur in S3 buckets) or AWS Fargate (a serverless compute engine for containers). - Source: dev.to / 24 days ago
The first is AWS DynamoDB which is going to act as our NoSQL database for our project which we’re also going to pair with a Single-Table design architecture. - Source: dev.to / 23 days ago
DynamoDB - 25GB NoSQL DB EC2 - 750 hours per month of t2.micro or t3.micro(12mo). 100GB egress per month. - Source: dev.to / 4 months ago
After two years, I moved to a Web3 startup where I was given a lead software engineer role. This new role gave me more hands-on experience with AWS, where I've learned to implement serverless technologies like Lambda and DynamoDB. - Source: dev.to / 6 months ago
Recently I had to revisit the "JVM languages universe" again. Yes, language(s), plural! Java isn't the only language that uses the JVM. I previously used Scala, which is a JVM language, to use Apache Spark for Data Engineering workloads, but this is for another post 😉. - Source: dev.to / 3 months ago
Consume data into third party software (then let Open Search or Apache Spark or Apache Pinot) for analysis/datascience, GIS systems (so you can put reports on a map) or any ticket management system. - Source: dev.to / 4 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
A JVM based framework named "Spark", when https://spark.apache.org exists? - Source: Hacker News / 11 months ago
AWS Lambda - Automatic, event-driven compute service
Apache Flink - Flink is a streaming dataflow engine that provides data distribution, communication, and fault tolerance for distributed computations.
MongoDB - MongoDB (from "humongous") is a scalable, high-performance NoSQL database.
Apache Airflow - Airflow is a platform to programmaticaly author, schedule and monitor data pipelines.
Redis - Redis is an open source in-memory data structure project implementing a distributed, in-memory key-value database with optional durability.
Hadoop - Open-source software for reliable, scalable, distributed computing