Talend Data Management Platform and Matillion Data Productivity Cloud compete in the ETL and data integration category. Matillion seems to have the upper hand given its ease of use and seamless AWS integration.
Features: Talend includes comprehensive ETL tools with robust metadata sharing and cloud integration. It is noted for its pushdown capabilities, SVN integration, and diverse connectors. Matillion is recognized for easy setup with Redshift, extensive AWS service integration, and a graphical interface simplifying ETL processes for non-technical users.
Room for Improvement: Talend users report installation errors, system stability issues, and a need for better documentation and SAP connections. Matillion needs more frequent updates, enhanced backend integration, and improved real-time data capture and GCP connectivity.
Ease of Deployment and Customer Service: Talend offers varied deployment options across on-premises and clouds but faces mixed customer service reviews. Matillion, deployed mainly on public clouds, is praised for its simple AWS Marketplace setup yet seeks better support query handling.
Pricing and ROI: Talend's developer-user licensed model has high initial costs but offers flexible scaling options. Matillion uses a pay-as-you-go pricing model through AWS Marketplace, providing cost efficiency by strategically managing EC2 instances, though pricing depends on usage.
Consequently, we adjusted our processes to use Matillion Data Productivity Cloud only for extraction and ingestion, while Snowflake handled all transformations and jobs.
We actually achieved the first 18 months worth of work in the first six months.
They communicate effectively and respond quickly to all inquiries.
Depending on the nature of data sets, volume, and mixture of different data, the scalability could be improved as manual code writing is still required.
The autoscale process works well, allowing the system to start another node automatically if the first machine reaches 80% capacity.
We have not encountered many issues with remote engines, and the interfaces are properly developed.
The main areas for improvement are AI features and scalability.
Connections to BigQuery for extracting information are complex.
On the flip side, that is one of its amazing strengths, as you are not locked into a very rigid way of doing something.
Data management could also encompass APIs and real-time streaming data integration.
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.
The pricing is moderate, neither expensive nor cheap.
The predefined connectors eliminate the need to write code for connectivity.
Matillion Data Productivity Cloud is effective for ingest functions, particularly when moving information to Snowflake and performing many transformations.
Having access to Talend support directly from TNC proved quite beneficial.
Matillion Data Productivity Cloud features an intuitive graphical interface, seamless AWS integration, and efficient data management. Its tools streamline complex tasks for SFDC, RDS, Marketo, Facebook, and Google AdWords.
Matillion Data Productivity Cloud provides fast transformations with built-in verification, easy scheduling, and sampling. With automatic scalability and diverse data source support, it simplifies complex data tasks. Users benefit from cloud data warehousing and integrating data into Snowflake while appreciating its ease of use by non-technical teams. Enhancements can focus on frequent API adjustments, improved documentation, faster performance with less latency, and better error handling.
What are the key features of Matillion Data Productivity Cloud?
What benefits and ROI should users seek in reviews?
In industries such as technology, finance, and healthcare, Matillion Data Productivity Cloud is implemented to streamline ETL processes, optimize data pipeline construction, and enhance data migration efforts. It supports efficient data loading and integration between cloud and on-premises databases, aiding industries in managing data-driven projects.
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