Amazon EMR
Google BigQuery
Google Cloud Dataflow
Google Cloud Dataproc
Databricks
Qubole
Snowflake
HortonWorks Data Platform
VeloDB
Snowflakepowe.red
ClickHouse
Presto
PostgreSQL
VeloDB is a modern real-time data warehouse powered by open source Apache Doris for lightning-fast data analytics at scale. It ensures big data ingestion within seconds and outstanding performance in both real-time serving and interactive ad-hoc queries. It is one platform for various analytics workloads, including structured and semi-structured data processing, real-time analytics and batch processing, internal data query and federated queries of external data. It allows elastic scaling for efficient resource management. It can dynamically adjust the computing resources allocated to the workload based on the changing requirements. It supports MySQL protocol and standard SQL for easy integration with other data tools. It also provides open data API to be accessible for various external query engines.
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Based on our record, Amazon EMR seems to be more popular. It has been mentiond 10 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.
There are different ways to implement parallel dataflows, such as using parallel data processing frameworks like Apache Hadoop, Apache Spark, and Apache Flink, or using cloud-based services like Amazon EMR and Google Cloud Dataflow. It is also possible to use parallel dataflow frameworks to handle big data and distributed computing, like Apache Nifi and Apache Kafka. Source: about 1 year ago
I'm going to guess you want something like EMR. Which can take large data sets segment it across multiple executors and coalesce the data back into a final dataset. Source: almost 2 years ago
This is exactly the kind of workload EMR was made for, you can even run it serverless nowadays. Athena might be a viable option as well. Source: almost 2 years ago
Apache Spark is one of the most actively developed open-source projects in big data. The following code examples require that you have Spark set up and can execute Python code using the PySpark library. The examples also require that you have your data in Amazon S3 (Simple Storage Service). All this is set up on AWS EMR (Elastic MapReduce). - Source: dev.to / over 2 years ago
Check out https://aws.amazon.com/emr/. Source: about 2 years ago
Google BigQuery - A fully managed data warehouse for large-scale data analytics.
Snowflakepowe.red - Snowflake Computing is delivering a data warehouse for the cloud.
Google Cloud Dataflow - Google Cloud Dataflow is a fully-managed cloud service and programming model for batch and streaming big data processing.
ClickHouse - ClickHouse is an open-source column-oriented database management system that allows generating analytical data reports in real time.
Google Cloud Dataproc - Managed Apache Spark and Apache Hadoop service which is fast, easy to use, and low cost
Presto - Next generation front-of-house technology
