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Matillion Data Productivity Cloud vs Teradata comparison

 

Comparison Buyer's Guide

Executive SummaryUpdated on Mar 31, 2025

Review summaries and opinions

We asked business professionals to review the solutions they use. Here are some excerpts of what they said:
 

ROI

Sentiment score
7.3
Matillion Data Productivity Cloud boosts ROI within a year by reducing costs and enhancing efficiency with Snowflake integration.
Sentiment score
8.1
Teradata boosts analytics speed over 100%, enhancing customer service and satisfaction, with high ROI and user approval.
Consequently, we adjusted our processes to use Matillion Data Productivity Cloud only for extraction and ingestion, while Snowflake handled all transformations and jobs.
 

Customer Service

Sentiment score
7.6
Matillion Data Productivity Cloud offers excellent, responsive support with comprehensive resources, exceeding user expectations through proactive engagement.
Sentiment score
7.1
Teradata's customer service is praised for expertise but criticized for delays, with ratings ranging from 6 to 10 out of 10.
They communicate effectively and respond quickly to all inquiries.
The technical support from Teradata is quite advanced.
Customer support is very good, rated eight out of ten under our essential agreement.
 

Scalability Issues

Sentiment score
7.6
Matillion Data Productivity Cloud is highly scalable, leveraging cloud environments for efficient processing with recent improvements enhancing flexibility and compatibility.
Sentiment score
7.4
Teradata is praised for its scalability, speed, and flexibility, despite some complexity and cost challenges in cloud environments.
The autoscale process works well, allowing the system to start another node automatically if the first machine reaches 80% capacity.
This expansion can occur without incurring downtime or taking systems offline.
Scalability is complex as you need to purchase a license and coordinate with Teradata for additional disk space and CPU.
 

Stability Issues

Sentiment score
7.8
Matillion Data Productivity Cloud is stable and reliable, rated highly by users, with responsive support and minor issues resolved.
Sentiment score
8.4
Teradata excels in stability with minimal downtime, robust architecture, 99.9% uptime, and reliable performance, despite minor large dataset issues.
I find the stability to be almost a ten out of ten.
The workload management and software maturity provide a reliable system.
 

Room For Improvement

Matillion Data Productivity Cloud requires enhanced API updates, integration, customization, real-time capture, user documentation, UI management, and processing efficiency.
Teradata users seek better transaction processing, enhanced scalability, modern interface, cloud focus, advanced analytics, and improved support and documentation.
Connections to BigQuery for extracting information are complex.
Unlike SQL and Oracle, which have in-built replication capabilities, we don't have similar functionality with Teradata.
 

Setup Cost

Matillion Data Productivity Cloud offers flexible pricing on AWS, with competitive rates and potential savings through strategic management and discounts.
Teradata's high cost is justified by its superior performance, competitive total ownership costs, and flexible pricing models.
Matillion Data Productivity Cloud offers discounts and special deals, especially when dealing with high-volume clients or fewer existing clients in specific regions, like Spain.
Initially, it may seem expensive compared to similar cloud databases, however, it offers significant value in performance, stability, and overall output once in use.
Teradata is much more expensive than SQL, which is well-performed and cheaper.
 

Valuable Features

Matillion Data Productivity Cloud enhances ETL efficiency with seamless AWS integration, user-friendly UI, and automatic scalability for comprehensive data management.
Teradata offers efficient, scalable data management with fast query performance, robust security, automation, and cloud flexibility for businesses.
Matillion Data Productivity Cloud is effective for ingest functions, particularly when moving information to Snowflake and performing many transformations.
The data mover is valuable over the last two years as it allows us to achieve data replication to our disaster recovery systems.
 

Categories and Ranking

Matillion Data Productivity...
Average Rating
8.4
Reviews Sentiment
7.4
Number of Reviews
27
Ranking in other categories
Cloud Data Integration (6th)
Teradata
Average Rating
8.2
Reviews Sentiment
7.0
Number of Reviews
76
Ranking in other categories
Customer Experience Management (6th), Backup and Recovery (20th), Data Integration (17th), Relational Databases Tools (7th), Data Warehouse (3rd), BI (Business Intelligence) Tools (10th), Marketing Management (6th), Cloud Data Warehouse (6th)
 

Mindshare comparison

While both are Data Integration and Access solutions, they serve different purposes. Matillion Data Productivity Cloud is designed for Cloud Data Integration and holds a mindshare of 3.4%, down 4.7% compared to last year.
Teradata, on the other hand, focuses on Data Warehouse, holds 16.3% mindshare, up 15.2% since last year.
Cloud Data Integration
Data Warehouse
 

Featured Reviews

Tomáš Hronek - PeerSpot reviewer
Used for wrangling or transforming data from sources like S3 and Databricks
I use Matillion ETL for wrangling or transforming data from sources like S3 and Databricks The most valuable feature of Matillion ETL is the UI experience in which you can drag and drop most of the transformation. Sometimes, we have issues with the solution's stability and need to restart it for…
SurjitChoudhury - PeerSpot reviewer
Offers seamless integration capabilities and performance optimization features, including extensive indexing and advanced tuning capabilities
We created and constructed the warehouse. We used multiple loading processes like MultiLoad, FastLoad, and Teradata Pump. But those are loading processes, and Teradata is a powerful tool because if we consider older technologies, its architecture with nodes, virtual processes, and nodes is a unique concept. Later, other technologies like Informatica also adopted the concept of nodes from Informatica PowerCenter version 7.x. Previously, it was a client-server architecture, but later, it changed to the nodes concept. Like, we can have the database available 24/7, 365 days. If one node fails, other nodes can take care of it. Informatica adopted all those concepts when it changed its architecture. Even Oracle databases have since adapted their architecture to them. However, this particular Teradata company initially started with its own different type of architecture, which major companies later adopted. It has grown now, but initially, whatever query we sent it would be mapped into a particular component. After that, it goes to the virtual processor and down to the disk, where the actual physical data is loaded. So, in between, there's a map, which acts like a data dictionary. It also holds information about each piece of data, where it's loaded, and on which particular virtual processor or node the data resides. Because Teradata comes with a four-node architecture, or however many nodes we choose, the cost is determined by that initially. So, what type of data does each and every node hold? It's a shared-no architecture. So, whatever task is given to a virtual processor it will be processed. If there's a failure, then it will be taken care of by another virtual processor. Moreover, this solution has impacted the query time and data performance. In Teradata, there's a lot of joining, partitioning, and indexing of records. There are primary and secondary indexes, hash indexing, and other indexing processes. To improve query performance, we first analyze the query and tune it. If a join needs a secondary index, which plays a major role in filtering records, we might reconstruct that particular table with the secondary index. This tuning involves partitioning and indexing. We use these tools and technologies to fine-tune performance. When it comes to integration, tools like Informatica seamlessly connect with Teradata. We ensure the Teradata database is configured correctly in Informatica, including the proper hostname and properties for the load process. We didn't find any major complexity or issues with integration. But, these technologies are quite old now. With newer big data technologies, we've worked with a four-layer architecture, pulling data from Hadoop Lake to Teradata. We configure Teradata with the appropriate hostname and credentials, and use BTEQ queries to load data. Previously, we converted the data warehouse to a CLD model as per Teradata's standardized procedures, moving from an ETL to an EMT process. This allowed us to perform gap analysis on missing entities based on the model and retrieve them from the source system again. We found Teradata integration straightforward and compatible with other tools.
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Comparison Review

it_user232068 - PeerSpot reviewer
Aug 5, 2015
Netezza vs. Teradata
Original published at https://www.linkedin.com/pulse/should-i-choose-net Two leading Massively Parallel Processing (MPP) architectures for Data Warehousing (DW) are IBM PureData System for Analytics (formerly Netezza) and Teradata. I thought talking about the similarities and differences…
 

Top Industries

By visitors reading reviews
Financial Services Firm
18%
Computer Software Company
16%
Manufacturing Company
9%
Healthcare Company
5%
Financial Services Firm
26%
Computer Software Company
10%
Healthcare Company
7%
Manufacturing Company
7%
 

Company Size

By reviewers
Large Enterprise
Midsize Enterprise
Small Business
 

Questions from the Community

What do you like most about Matillion ETL?
The new version with the Productivity Cloud is very simple. It's easy to use, navigate, and understand.
What is your experience regarding pricing and costs for Matillion ETL?
The solution's pricing is not based on the licensing cost but on the running hours when the Matillion instance is up and running. Its pricing model is different from the traditional pricing models ...
What needs improvement with Matillion ETL?
Depending on the use case, the solution's pricing could be improved. Matillion ETL should include more enhanced capabilities for extracting data from the SAP systems.
Comparing Teradata and Oracle Database, which product do you think is better and why?
I have spoken to my colleagues about this comparison and in our collective opinion, the reason why some people may declare Teradata better than Oracle is the pricing. Both solutions are quite simi...
Which companies use Teradata and who is it most suitable for?
Before my organization implemented this solution, we researched which big brands were using Teradata, so we knew if it would be compatible with our field. According to the product's site, the comp...
Is Teradata a difficult solution to work with?
Teradata is not a difficult product to work with, especially since they offer you technical support at all levels if you just ask. There are some features that may cause difficulties - for example,...
 

Also Known As

Matillion ETL for Redshift, Matillion ETL for Snowflake, Matillion ETL for BigQuery
IntelliFlex, Aster Data Map Reduce, , QueryGrid, Customer Interaction Manager, Digital Marketing Center, Data Mover, Data Stream Architecture
 

Overview

 

Sample Customers

Thrive Market, MarketBot, PWC, Axtria, Field Nation, GE, Superdry, Quantcast, Lightbox, EDF Energy, Finn Air, IPRO, Twist, Penn National Gaming Inc
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