Alteryx vs Databricks comparison

Alteryx can be used to speed up or automate your business processes and enables geospatial and predictive solutions. Its platform helps organizations answer business questions quickly and efficiently, and can be used as a major building block in a digital transformation or automation initiative. With Alteryx, you can build processes in a more efficient, repeatable, and less error-prone way. Unlike other tools, Alteryx is easy to use without an IT background. The platform is very robust and can be used in virtually any industry or functional area.

With Alteryx You Can:

• Prep, blend, and analyze data
• Deliver faster, better business outcomes
• Automate analytics and data science
• Embed intelligent decisioning
• Deploy and share analytics in hours

Alteryx Features Include:

Some of the most valuable Alteryx features include:

Scalability, stability, flexibility, fast performance, no-code analytics, data processing, business logic wrapping, scheduling, ease of use, data blending from different platforms, geo-referencing, good customization capabilities, drag and drop functionality, intuitive user interface, connectors, machine learning, macros, simple GUI, integration with Python, good data transformation, good documentation, multiple database merging, and easy deployment.

Alteryx Can Be Used For:

• Combining and manipulating data within spreadsheets: Alteryx can be used in situations where complex data manipulation occurs. It can handle large data quickly, and the process is much simpler to see and understand.
  
  
• Database access and supplementing SQL development: Alteryx has several sets of database connectors and functions, including many functions that your average database does not. Alteryx can work with data from multiple databases or areas within a database. It allows users to filter, sort, calculate, etc. as they would commonly do in SQL or an ETL tool.
  
• API, cloud, and hybrid access: Alteryx can read and write data in databases, files, REST APIs, and a myriad of other locations (with the correct permissions). When a workflow is published, you can also call a workflow through a REST API to start it.
  
  
• Data science: Alteryx provides pre-built models that are extremely useful for data scientists who may have limited programming skills and also gives you the ability to add R or Python code directly within a workflow.
  
  
• Geospatial analysis: Alteryx gives users drag-and-drop tools to geocode, plot, and map locations, customers, competitors, or anything that has a location (employee, truck, pipeline, etc.).
  
  
• Reports and dashboards: Alteryx provides built-in tools that enable the building of reports and dashboards.

Alteryx Benefits

Some of the benefits of using Alteryx include
:

• Saves time: Alteryx helps shorten the time required to start analyzing data and looking for insights, minimizing the tasks that do not add value to the business and maximizing the analysis phase.
  
  
• Clear tool configurations: Alteryx provides simple and concise tool configurations that are quick and easy to set.
  
  
• Excellent workflow compatibility.
  
  
• Reduced development time: Alteryx has an extensive gallery of user-developed analytic applications that helps to reduce development time.
  
  
• Fast data loading: Alteryx has tools that make it very effective when working with big data sets.
  
  
• No-code, low-code analytic building blocks: You can prep, blend, and analyze data to enable highly configurable and repeatable workflows.
  
  
• Machine learning: Alteryx allows you to quickly create properly trained algorithms that are ready to deploy.

Reviews from Real Users

"Automation is the most valuable aspect for us. The ability to wrap business logic around the data is very helpful." - Theresa M., Senior Capacity Planner at a financial services firm

"Alteryx has made us more agile and increased the speed and effectiveness of decision making." - Richard F., Director, Digital Experience & Media at Qdoba Restaurant Corporation

"The scheduling feature for the automation is excellent." - Data Analytics Engineer at a tech services company

"The product is very stable and super fast, five-star. It's significantly more stable than its nearest competitor." - Director at a non-tech company

“A complete solution with very good user experience and a nice user interface.” - Solutions Consultant at a tech services company

"There are a lot of good customization capabilities." - Advance Analytics PO at a pharma/biotech company

Databricks is an industry-leading data analytics platform which is a one-stop product for all data requirements. Databricks is made by the creators of Apache Spark, Delta Lake, ML Flow, and Koalas. It builds on these technologies to deliver a true lakehouse data architecture, making it a robust platform that is reliable, scalable, and fast. Databricks speeds up innovations by synthesizing storage, engineering, business operations, security, and data science.

Databricks is integrated with Microsoft Azure, Amazon Web Services, and Google Cloud Platform. This enables users to easily manage a colossal amount of data and to continuously train and deploy machine learning models for AI applications. The platform handles all analytic deployments, ranging from ETL to models training and deployment.

Databricks deciphers the complexities of processing data to empower data scientists, engineers, and analysts with a simple collaborative environment to run interactive and scheduled data analysis workloads. The program takes advantage of AI’s cost-effectivity, flexibility, and cloud storage.

Databricks Key Features

Some of Databricks key features include:

• Cloud-native: Works well on any prominent cloud provider.
  
• Data storage: Stores a broad range of data, including structured, unstructured, and streaming.
  
• Self-governance: Built-in governance and security controls.
  
• Flexibility: Flexible for small-scale jobs as well as running large-scale jobs like Big Data processing because it’s built from Spark and is specifically optimized for Cloud environments.
  
• Data science tools: Production-ready data tooling, from engineering to BI, AI, and ML.
  
• Familiar languages: While Databricks is Spark-based, it allows commonly used programming languages like R, SQL, Scala, and Python to be used.
  
• Team sharing workspaces: Creates an environment that provides interactive workspaces for collaboration, which allow multiple members to collaborate for data model creation, machine learning, and data extraction.
  
• Data source: Performs limitless Big Data analytics by connecting to Cloud providers AWS, Azure, and Google, as well as on-premises SQL servers, JSON and CSV.

Reviews from Real Users

Databricks stands out from its competitors for several reasons. Two striking features are its collaborative ability and its ability to streamline multiple programming languages.

PeerSpot users take note of the advantages of these features. A Chief Research Officer in consumer goods writes, “We work with multiple people on notebooks and it enables us to work collaboratively in an easy way without having to worry about the infrastructure. I think the solution is very intuitive, very easy to use. And that's what you pay for.”

A business intelligence coordinator in construction notes, “The capacity of use of the different types of coding is valuable. Databricks also has good performance because it is running in spark extra storage, meaning the performance and the capacity use different kinds of codes.”

An Associate Manager who works in consultancy mentions, “The technology that allows us to write scripts within the solution is extremely beneficial. If I was, for example, able to script in SQL, R, Scala, Apache Spark, or Python, I would be able to use my knowledge to make a script in this solution. It is very user-friendly and you can also process the records and validation point of view. The ability to migrate from one environment to another is useful.”