Apache Hive
Apache Hive (by apache)
beam
Apache Beam is a unified programming model for Batch and Streaming data processing. (by apache)
| Apache Hive | beam | |
|---|---|---|
| 14 | 30 | |
| 5,370 | 7,582 | |
| 1.4% | 1.7% | |
| 9.6 | 10.0 | |
| 2 days ago | 6 days ago | |
| Java | Java | |
| Apache License 2.0 | Apache License 2.0 |
The number of mentions indicates the total number of mentions that we've tracked plus the number of user suggested alternatives.
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
Apache Hive
Posts with mentions or reviews of Apache Hive.
We have used some of these posts to build our list of alternatives
and similar projects. The last one was on 2023-03-16.
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Apache Iceberg as storage for on-premise data store (cluster)
Trino or Hive for SQL querying. Get Trino/Hive to talk to Nessie.
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In One Minute : Hadoop
Hive, A data warehouse infrastructure that provides data summarization and ad hoc querying.
- Visionary French entrepreneur, David Gurle, launches new venture – Hive
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DeWitt Clause, or Can You Benchmark %DATABASE% and Get Away With It
Apache Drill, Druid, Flink, Hive, Kafka, Spark
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Apache Spark, Hive, and Spring Boot — Testing Guide
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.
- Apache Hive in the vein!
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Jinja2 not formatting my text correctly. Any advice?
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.'),
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Understanding SQL Dialects
Apache Hive takes in a specific SQL dialect and converts it to map-reduce.
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The Data Engineer Roadmap 🗺
Apache Hive
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Open Source SQL Parsers
Apache Calcite is a popular parser/optimizer that is used in popular databases and query engines like Apache Hive, BlazingSQL and many others.
beam
Posts with mentions or reviews of beam.
We have used some of these posts to build our list of alternatives
and similar projects. The last one was on 2024-01-24.
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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/97814.... 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 https://beam.apache.org very much is. Nowadays people often use "map reduce" as a shorthand for whatever batch processing system they're building on top of.
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beam VS quix-streams - a user suggested alternative
2 projects | 7 Dec 2023
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How do Streaming Aggregation Pipelines work?
Apache Beam is one of many tools that you can use
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Releasing Temporian, a Python library for processing temporal data, built together with Google
Flexible runtime ☁️: Temporian programs can run seamlessly in-process in Python, on large datasets using Apache Beam.
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Kafka cluster loses or duplicates messages
To perform the tests I'm using a Kafka cluster on Kubernetes from the Beam repo (here).
- Apache Beam
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Real Time Data Infra Stack
Apache Beam: Streaming framework which can be run on several runner such as Apache Flink and GCP Dataflow
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Google Cloud Reference
Apache Beam: Batch/streaming data processing 🔗Link
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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.
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Pub/Sub parallel processing best practices
That being said, there is a learning curve in understanding how Apache Beam works. Take a look at the beam website for more information.
What are some alternatives?
When comparing Apache Hive and beam you can also consider the following projects:
superset - Apache Superset is a Data Visualization and Data Exploration Platform
Apache Arrow - Apache Arrow is a multi-language toolbox for accelerated data interchange and in-memory processing
ObjectBox Java (Kotlin, Android) - Java and Android Database - fast and lightweight without any ORM
Apache Hadoop - Apache Hadoop
HikariCP - 光 HikariCP・A solid, high-performance, JDBC connection pool at last.
Scio - A Scala API for Apache Beam and Google Cloud Dataflow.
Apache Phoenix - Apache Phoenix
Apache Spark - Apache Spark - A unified analytics engine for large-scale data processing
Flyway - Flyway by Redgate • Database Migrations Made Easy.
Airflow - Apache Airflow - A platform to programmatically author, schedule, and monitor workflows
Presto - The official home of the Presto distributed SQL query engine for big data
Apache Accumulo - Apache Accumulo