Azure Databricks
IBM Cloud Pak for Data
MyAnalytics
Arcadia Enterprise
MicroStrategy
MATLAB
Yandex.Metrica
Splunk Enterprise
Apache Druid
Apache Spark
ClickHouse
Apache Hive
Apache Flink
Apache Kylin
Vertica
MySQL
Azure Databricks Apache DruidBased on our record, Apache Druid should be more popular than Azure Databricks. 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.
In the big data space, Azure offers Azure Databricks. This is an Apache Spark big data analytics and machine learning service over a Distributed File System. The distributed cluster of nodes running analytics and AI operations in parallel allow for fast processing of large volumes of data and integration with popular machine learning libraries such as PyTorch unleash endless possibilities for custom ML. - Source: dev.to / almost 3 years ago
https://azure.microsoft.com/en-us/services/databricks. - Source: Hacker News / about 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 / 4 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 / 5 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 / almost 2 years ago
IBM Cloud Pak for Data - Move to cloud faster with IBM Cloud Paks running on Red Hat OpenShift – fully integrated, open, containerized and secure solutions certified by IBM.
Apache Spark - Apache Spark is an engine for big data processing, with built-in modules for streaming, SQL, machine learning and graph processing.
MyAnalytics - MyAnalytics, now rebranded to Microsoft Viva Insights, is a customizable suite of tools that integrates with Office 365 to drive employee engagement and increase productivity.
ClickHouse - ClickHouse is an open-source column-oriented database management system that allows generating analytical data reports in real time.
Arcadia Enterprise - Arcadia Enterprise is the ultimate native BI for data lakes with real-time streaming visualizations, all without adding hardware or moving data.
Apache Hive - Apache Hive data warehouse software facilitates querying and managing large datasets residing in distributed storage.