Based on our record, Apache Kafka seems to be a lot more popular than Apache Hive. While we know about 120 links to Apache Kafka, we've tracked only 8 mentions of 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.
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
In today’s fast-paced digital landscape, effective data management and analysis are essential for businesses aiming to stay ahead of the curve. Fortunately, modern tools like Apache Kafka and RudderStack have revolutionized the way we handle and derive insights from large datasets. In this blog post, we’ll explore our experience implementing the Kafka Sink Connector to facilitate seamless event data transfer to... - Source: dev.to / about 2 months ago
Stream-processing platforms such as Apache Kafka, Apache Pulsar, or Redpanda are specifically engineered to foster event-driven communication in a distributed system and they can be a great choice for developing loosely coupled applications. Stream processing platforms analyze data in motion, offering near-zero latency advantages. For example, consider an alert system for monitoring factory equipment. If a... - Source: dev.to / 3 months ago
Apache Kafka is a distributed streaming platform capable of handling high throughput of data, while ReductStore is a databases for unstructured data optimized for storing and querying along time. - Source: dev.to / 3 months ago
*Push data *(original source image, GPS, timestamp) in a common place (Apache Kafka,...). - Source: dev.to / 3 months ago
RabbitMQ comes with administrative tools to manage user permissions and broker security and is perfect for low latency message delivery and complex routing. In comparison, Apache Kafka architecture provides secure event streams with Transport Layer Security(TLS) and is best suited for big data use cases requiring the best throughput. - Source: dev.to / 3 months ago
Apache Spark - Apache Spark is an engine for big data processing, with built-in modules for streaming, SQL, machine learning and graph processing.
RabbitMQ - RabbitMQ is an open source message broker software.
Apache Doris - Apache Doris is an open-source real-time data warehouse for big data analytics.
Apache ActiveMQ - Apache ActiveMQ is an open source messaging and integration patterns server.
ClickHouse - ClickHouse is an open-source column-oriented database management system that allows generating analytical data reports in real time.
StatCounter - StatCounter is a simple but powerful real-time web analytics service that helps you track, analyse and understand your visitors so you can make good decisions to become more successful online.