Apache Doris
ClickHouse
StarRocks
Apache Hive
Presto DB
PostgreSQL
Greenplum Database
MySQL
Apache Airflow
Make.com
ifttt
Microsoft Power Automate
Pipefy
Pushwoosh
Kissflow
Process Street
Apache Doris Apache AirflowApache Airflow is recommended for data engineers, data scientists, and IT professionals who need to automate and manage workflows. It is particularly suited for organizations handling large-scale data processing tasks, requiring integration with various systems, and those looking to deploy machine learning pipelines or ETL processes.
No Apache Doris videos yet. You could help us improve this page by suggesting one.
Based on our record, Apache Airflow seems to be a lot more popular than Apache Doris. While we know about 75 links to Apache Airflow, we've tracked only 6 mentions of Apache Doris. 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.
Like in many databases, Apache Doris shards data into partitions, and then a partition is further divided into buckets. Partitions are typically defined by time or other continuous values. This allows query engines to quickly locate the target data during queries by pruning irrelevant data ranges. - Source: dev.to / 10 months ago
What makes a modern database system? The three key modules are query optimizer, execution engine, and storage engine. Among them, the role of execution engine to the DBMS is like the chef to a restaurant. This article focuses on the execution engine of the Apache Doris data warehouse, explaining the secret to its high performance. - Source: dev.to / 10 months ago
For most people looking for a log management and analytics solution, Elasticsearch is the go-to choice. The same applies to InfluxDB for time series data analysis. These were exactly the choices of NetEase, one of the world's highest-yielding game companies but more than that. As NetEase expands its business horizons, the logs and time series data it receives explode, and problems like surging storage costs and... - Source: dev.to / 11 months ago
This is an in-depth introduction to the workload isolation capabilities of Apache Doris. But first of all, why and when do you need workload isolation? If you relate to any of the following situations, read on and you will end up with a solution:. - Source: dev.to / about 1 year ago
Apache Doris is an all-in-one data platform that is capable of real-time reporting, ad-hoc queries, data lakehousing, log management and analysis, and batch data processing. As more and more companies have been replacing their component-heavy data architecture with Apache Doris, there is an increasing need for a more convenient data migration solution. That's why the Doris SQL Convertor is made. - Source: dev.to / about 1 year ago
Is this really true? Something that can be supported by clear evidence? I’ve seen this trotted out many times, but it seems like there are interesting Apache projects: https://airflow.apache.org/ https://iceberg.apache.org/ https://kafka.apache.org/ https://superset.apache.org/. - Source: Hacker News / 3 months ago
Apache Airflow offers simplicity when it comes to scheduling, authoring, and monitoring ML workflows using Python. The tool's greatest advantage is its compatibility with any system or process you are running. This also eliminates manual intervention and increases team productivity, which aligns with the principles of Platform Engineering tools. - Source: dev.to / 4 months ago
Data orchestration tools are key for managing data pipelines in modern workflows. When it comes to tools, Apache Airflow, Dagster, and Flyte are popular tools serving this need, but they serve different purposes and follow different philosophies. Choosing the right tool for your requirements is essential for scalability and efficiency. In this blog, I will compare Apache Airflow, Dagster, and Flyte, exploring... - Source: dev.to / 5 months ago
Data pipelines: Apache Kafka and Airflow are often used for building data pipelines that can continuously feed data to models in production. - Source: dev.to / 5 months ago
This article demonstrates how to work with near real-time and historical data using the dlt package. Whether you need to scale data access across the enterprise or provide historical data for post-event analysis, you can use the same framework to provide customer data. In a future article, I'll demonstrate how to use dlt with a workflow orchestrator such as Apache Airflow or Dagster.``. - Source: dev.to / 7 months ago
ClickHouse - ClickHouse is an open-source column-oriented database management system that allows generating analytical data reports in real time.
Make.com - Tool for workflow automation (Former Integromat)
StarRocks - StarRocks offers the next generation of real-time SQL engines for enterprise-scale analytics. Learn how we make it easy to deliver real-time analytics.
ifttt - IFTTT puts the internet to work for you. Create simple connections between the products you use every day.
Apache Hive - Apache Hive data warehouse software facilitates querying and managing large datasets residing in distributed storage.
Microsoft Power Automate - Microsoft Power Automate is an automation platform that integrates DPA, RPA, and process mining. It lets you automate your organization at scale using low-code and AI.
