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Kinetica vs Alteryx

Pick the right tool for the job. Consider Kinetica for analysis of large volumes of streaming data, geospatial data, and for ad-hoc queries and visualization across large datasets.

What is Kinetica?

Kinetica is a real-time analytics database with best-in-class location intelligence, powered by a cutting-edge vectorized architecture. With Kinetica, you can realize the full benefits of streaming data by fusing it with other data, providing full context and allowing you to use more history than with a streaming platform alone.
Kinetica Features »

What is Alteryx?

Alteryx is a tool designed to make data analytics more accessible within organizations. Its platform provides building blocks to automate various elements of the analytics process. First released in 2006, Alteryx has gained popularity for data access, data cleansing, ETL, and other activities related to BI.

What is Kinetica Good for?

Kinetica is best used for analytics (OLAP) workloads, and stands out when used with large volumes IoT data, such as that from moving sensors, where there are frequent updates of location.

Gaining value from sensor data requires blending spatial, time series, and graph analytics. Kinetica has over 100 spatial functions including geo-joins, point in polygon, and map matching, and can create interactive visualizations with billions of geospatial data points. Kinetica combines this with advanced time series functions and allows you to seamlessly use relational data in a native graph context for understanding relationships.
What can you build with Kinetica?

What is Alteryx good for?

Alteryx is good for ease of use by all different personas in an organization with both code-free and expert modes. Alteryx’s Analytics Process Automation (APA) provides an easy way to automate components of the end to end analytics process. Users with no coding experience can build automated data pipelines and save time on running repetitive reports. Alteryx provides an intuitive way to design custom workflows and obtain self-service analytics.

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What are Alteryx limitations?

While Alteryx is useful for dealing with repetitive manual processes, it is not as powerful as using a full-fledged analytic database. It’s meant for overnight batch reporting, not for when you need real time answers or to run a model many times over the course of a day.

Complex workflows on Alteryx will require significant hardware to run efficiently. This generally leads customers to spend a far higher amount on Alteryx than originally anticipated. Alteryx price points come in at the higher end of the market compared to other analytics tools.

Alteryx is not designed for today’s more advanced analytics use cases that require cutting-edge streaming or machine learning capabilities, or leveraging high-volume IoT data at scale. The Alteryx UI is outdated and does not provide much in the way of data visualization.

 

Case Study

From Days with Alteryx, to Seconds on Kinetica

Recently, a top 3 global retailer was able to reduce run times for a strategic analytic application from days on Alteryx to just 22 seconds using Kinetica.

The retailer sought to optimize supply chain logistics and operations, with the aim of identifying faster and more profitable delivery routing, and to identify optimal store locations. Kinetica was able to dramatically reduce the time taken to calculate most probable paths (MPP) and point-to-point (P2P) drive times at scale.

Read the Case Study »

Kinetica solved 1 million P2P drive times in approximately 22 seconds, exceeding the 4 hour best-case SLA stretch target by a significant margin.

How is Kinetica Being Used?

Kinetica customers are able to obtain real-time geospatial analytics at huge scale, such as the U.S. Postal Service, which uses Kinetica to combine millions of streaming location events from vehicle transmitters with billions of historical events, all available for dynamic route optimizations.

Proven as scale with:

White Paper

Vectorization: The New Era of Big Data Parallelism

Every five to 10 years, an engineering breakthrough emerges that disrupts database software for the better. Vectorization is the newest breakthrough gaining momentum towards widespread adoption. Early adopters are using fully vectorized databases to foster new applications and reap lower costs.

Learn more about vectorization in this white paper.

Download the White Paper
Vectorization White Paper