Datacoves
dbt
Mozart Data
Domo
Zapier
AWS Glue
Helpful Sync
CData Sync
Apache Airflow
ifttt
Microsoft Power Automate
Make.com
Pipefy
Pushwoosh
Kissflow
Process Street
The Datacoves platform helps enterprises overcome their data delivery challenges quickly using dbt and Airflow, implementing best practices from the start without the need for multiple vendors or costly consultants.
Datacoves Apache AirflowNo features have been listed yet.
Datacoves's answer
We provide the flexibility and integration most companies need. We help you connect EL to T and Activation, we don't just handle the transformation and we guide you to do things right from the start so that you can scale in the future. Finally we offer both a SaaS and private cloud deployment options.
Datacoves's answer
Do you need to connect Extract and Load to Transform and downstream processes like Activation? Do you love using VS Code and need the flexibility to have any Python library or VS Code extension available to you? Do you want to focus on data and not worry about infrastructure? Do you have sensitive data and need to deploy within your private cloud and integrate with existing tools? If you answered yes to any of these questions, then you need Datacoves.
Datacoves's answer
Mid to Large size companies who value doing things well.
Datacoves's answer
Our founders have decades of experience in software development and implementing data platforms at large enterprises. We wanted to cut through all the noise and enable any team to deploy an end-to-end data management platform with best practices from the start. We believe that having an opinion matters and helping companies understand the pros and cons of different decisions will help them start off on the right path. Technology alone doesn't transform organizations.
Datacoves's answer
I manage analytics for a small SaaS company. Datacoves unlocked my ability to do everything from raw data to dashboarding all without me having to wrangle multiple contracts or set up an on-prem solution. I get to use the top open source tools out there without the headache and overhead of managing it myself. And their support is excellent when I run into any questions.
Cannot recommend highly enough for anyone looking to get their data tooling solved with a fraction of the effort of doing it themselves.
The most difficult part of any data stack is to establish a strong development foundation to build upon. Most small data teams simply cannot afford to do so and later pay the penalty when trying to scale with a spaghetti of processes, custom code, and no documentation. Datacoves made all the right choices in combining best-in-class tools surrounding dbt, tied together with strong devops practices so that you can trust in your process whether you are a team of one or a hundred and one.
Based on our record, Apache Airflow seems to be a lot more popular than Datacoves. While we know about 67 links to Apache Airflow, we've tracked only 2 mentions of Datacoves. 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.
Dbt Cloud rightfully gets a lot of credit for creating dbt Core and for being the first managed dbt Core platform, but there are several entrants in the market; from those who just run dbt jobs like Fivetran to platforms that offer more like EL + T like Mozart Data and Datacoves which also has hosted VS Code editor for dbt development and Airflow. Source: about 1 year ago
Check out datacoves.com more flexibility. Source: about 1 year ago
An integral part of an ML project is data acquisition and data transformation into the required format. This involves creating ETL (extract, transform, load) pipelines and running them periodically. Airflow is an open source platform that helps engineers create and manage complex data pipelines. Furthermore, the support for Python programming language makes it easy for ML teams to adopt Airflow. - Source: dev.to / 4 days ago
Level 1 of MLOps is when you've put each lifecycle stage and their intefaces in an automated pipeline. The pipeline could be a python or bash script, or it could be a directed acyclic graph run by some orchestration framework like Airflow, dagster or one of the cloud-provider offerings. AI- or data-specific platforms like MLflow, ClearML and dvc also feature pipeline capabilities. - Source: dev.to / 30 days ago
For the third, examples here might be analytics plugins in specialized databases like Clickhouse, data-transformations in places like your ETL pipeline using Airflow or Fivetran, or special integrations in your authentication workflow with Auth0 hooks and rules. - Source: dev.to / 4 months ago
Apache Airflow is an open-source platform to programmatically author, schedule, and monitor workflows. The platform features a web-based user interface and a command-line interface for managing and triggering workflows. Source: 7 months ago
Airflow is the most widely used and well-known tool for orchestrating data workflows. It allows for efficient pipeline construction, scheduling, and monitoring. - Source: dev.to / 7 months ago
dbt - dbt is a data transformation tool that enables data analysts and engineers to transform, test and document data in the cloud data warehouse.
ifttt - IFTTT puts the internet to work for you. Create simple connections between the products you use every day.
Mozart Data - The easiest way for teams to build a Modern Data Stack
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.
Domo - Domo: business intelligence, data visualization, dashboards and reporting all together. Simplify your big data and improve your business with Domo's agile and mobile-ready platform.
Make.com - Tool for workflow automation (Former Integromat)