Spring Batch
Apache Airflow
Apache Spark
Apache Kylin
Databricks
Control-M
fzf
Emuto
Apache Druid
Apache Spark
Apache Flink
Apache Hive
Apache Kylin
Presto DB
ClickHouse
Amazon Athena
Spring Batch Apache DruidBased on our record, Apache Druid should be more popular than Spring Batch. It has been mentiond 9 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.
Batch jobs? Absolutely. https://spring.io/projects/spring-batch. Source: almost 2 years ago
Spring Boot: is my go to for REST APIs or workers https://spring.io/projects/spring-boot Spring Batch: for async/batch work https://spring.io/projects/spring-batch. - Source: Hacker News / almost 3 years ago
Apache Druid: Focused on real-time analytics and interactive queries on large datasets. Druid is well-suited for high-performance applications in user-facing analytics, network monitoring, and business intelligence. - Source: dev.to / 2 months ago
Online analytical processing (OLAP) databases like Apache Druid, Apache Pinot, and ClickHouse shine in addressing user-initiated analytical queries. You might write a query to analyze historical data to find the most-clicked products over the past month efficiently using OLAP databases. When contrasting with streaming databases, they may not be optimized for incremental computation, leading to challenges in... - Source: dev.to / 3 months ago
Spencer Kimball (now CEO at CockroachDB) wrote an interesting article on this topic in 2021 where they created spencerkimball/stargazers based on a Python script. So I started thinking: could I create a data pipeline using Nifi and Kafka (two OSS tools often used with Druid) to get the API data into Druid - and then use SQL to do the analytics? The answer was yes! And I have documented the outcome below. Here’s... - Source: dev.to / over 1 year ago
Apache Druid is part of the modern data architecture. It uses a special data format designed for analytical workloads, using extreme parallelisation to get data in and get data out. A shared-nothing, microservices architecture helps you to build highly-available, extreme scale analytics features into your applications. - Source: dev.to / over 1 year ago
Datadog's product is a bit too close to Apache Druid to have named their design system so similarly. From https://druid.apache.org/ : > Druid unlocks new types of queries and workflows for clickstream, APM, supply chain, network telemetry, digital marketing, risk/fraud, and many other types of data. Druid is purpose built for rapid, ad-hoc queries on both real-time and historical data. - Source: Hacker News / over 1 year ago
Apache Airflow - Airflow is a platform to programmaticaly author, schedule and monitor data pipelines.
Apache Spark - Apache Spark is an engine for big data processing, with built-in modules for streaming, SQL, machine learning and graph processing.
Apache Flink - Flink is a streaming dataflow engine that provides data distribution, communication, and fault tolerance for distributed computations.
Apache Kylin - OLAP Engine for Big Data
Apache Hive - Apache Hive data warehouse software facilitates querying and managing large datasets residing in distributed storage.
Databricks - Databricks provides a Unified Analytics Platform that accelerates innovation by unifying data science, engineering and business.What is Apache Spark?