Amazon EMR
Google BigQuery
Google Cloud Dataflow
Databricks
Google Cloud Dataproc
Qubole
Snowflake
HortonWorks Data Platform
Apache Hive
Apache Spark
Apache Doris
ClickHouse
StarRocks
Amazon Redshift
Presto DB
Apache Flink
Amazon EMR Apache HiveAmazon EMR might be a bit more popular than Apache Hive. We know about 10 links to it since March 2021 and only 8 links to Apache Hive. 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: about 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
Trino or Hive for SQL querying. Get Trino/Hive to talk to Nessie. Source: about 1 year ago
Hive, A data warehouse infrastructure that provides data summarization and ad hoc querying. - Source: dev.to / over 1 year ago
In this article, I'm showing you how to create a Spring Boot app that loads data from Apache Hive via Apache Spark to the Aerospike Database. More than that, I'm giving you a recipe for writing integration tests for such scenarios that can be run either locally or during the CI pipeline execution. The code examples are taken from this repository. - Source: dev.to / about 2 years ago
ListItem(name='Apache Hive', website='https://hive.apache.org/', category='Interactive Query', short_description='Apache Hive is a data warehouse software project built on top of Apache Hadoop for providing data query and analysis. Hive gives an SQL-like interface to query data stored in various databases and file systems that integrate with Hadoop.'),. Source: over 2 years ago
Apache Hive takes in a specific SQL dialect and converts it to map-reduce. - Source: dev.to / over 2 years ago
Google BigQuery - A fully managed data warehouse for large-scale data analytics.
Apache Spark - Apache Spark is an engine for big data processing, with built-in modules for streaming, SQL, machine learning and graph processing.
Google Cloud Dataflow - Google Cloud Dataflow is a fully-managed cloud service and programming model for batch and streaming big data processing.
Apache Doris - Apache Doris is an open-source real-time data warehouse for big data analytics.
Databricks - Databricks provides a Unified Analytics Platform that accelerates innovation by unifying data science, engineering and business.What is Apache Spark?
ClickHouse - ClickHouse is an open-source column-oriented database management system that allows generating analytical data reports in real time.
