Apache Druid is a high-performance real-time analytical database. The main value of Druid is its ability to reduce the time spent checking and searching.
Druid’s workflow is designed to quickly query and analyze situations in real time.
Druid has a very powerful UI that allows users to do ad-hoc queries or handle high concurrency.
Think of Druid as an open source solution for database repositories or a range of user use cases.
Ad-Hoc Query
If you’re not sure about the concept and use of ad-hoc Query, do your own research on the technical documentation.
To put it simply: Ad Hoc query (Ad Hoc) is a flexible choice of query conditions by users according to their own needs, and the system can generate corresponding statistical reports according to the choice of users.
The biggest difference between AD hoc query and ordinary application query is that ordinary application query is customized, while AD hoc query is user-defined by users.
AD hoc queries are those defined by the user when using the system according to their needs at the time.
For AD hoc queries, what the user needs to query is not known at the beginning, so queries require more dimensions, and queries are often constructed at run time.
Druid’s queries support AD hoc queries well, but they also introduce some complexity and a learning curve.
Cloud native, stream native analytical database
Druid is designed for workflows that require rapid data query and ingestion. It delivers real-time data visibility, ad-hoc queries, operational analytics, and high concurrency.
Druid can be considered as an open source alternative to many real-world data warehouse solutions.
Visit the Druid Resources Quick navigation page for a brief look at our collection of relevant technical documentation and use cases.
Ease with existing data sources
Druid native supports streaming consumption data from message buses such as Kafka and Amazon Kinesis, as well as batch loading data from storage services such as HDFS and Amazon S3.
Nearly 100 times more efficient than the traditional scheme
Druid’s innovative architecture incorporates and combines the strengths of data warehousing, sequential databases, and retrieval systems.
The solution for traditional data entry and query demonstrated strong performance in completed benchmarks.
Unlocking a new type of workflow
Druid unlocks a new query and workflow for clickstream, APM, supply chain, network monitoring, marketing, and other event-driven types of data analysis designed for fast and efficient AD hoc queries of real-time and historical data.
Strong deployment capability
Druid can be deployed on AWS/GCP/Azure, hybrid Cloud, Kubernetes, and bare metal. Alibaba’s cloud computing platform also offers seamless integration for the Chinese environment. Druid can be easily deployed on any commercial hardware based on a *NIX environment, both in the cloud and on-premise. Deploying Druid is very simple, including expanding or taking clusters offline.
www.ossez.com/t/apache-dr…