Matillion and StreamSets are competitive players in the data integration and analytics platform category. While both products offer robust capabilities, Matillion holds an edge with its extensive AWS integration and user-friendly interface, especially for users already within the AWS ecosystem.
Features: Matillion offers comprehensive integration with AWS services, a drag-and-drop GUI for building data pipelines, and seamless connections with platforms like Redshift. StreamSets provides ease of configuration alongside a broad range of connectors. It features robust data manipulation, including Change Data Capture and data drift resilience, catering well to both batch and streaming data needs.
Room for Improvement: StreamSets struggles with integration issues on non-Java platforms and memory leak problems, alongside a complex logging system that can complicate the introduction for new users. Matillion could improve with more frequent API updates, better integration with other data ecosystems, and enhanced real-time data capture, plus improved handling of multiple environments.
Ease of Deployment and Customer Service: Both Matillion and StreamSets are designed for public cloud deployment, with StreamSets offering additional flexibility through hybrid cloud support. While Matillion users often rely on self-learning and documentation, StreamSets is noted for responsive customer service, even if some users mention prolonged waits during critical times. Matillion's deployment is straightforward via AWS Marketplace, though it involves higher costs.
Pricing and ROI: Matillion utilizes a pay-as-you-use model based on hours, making it efficient for variable workloads but possibly expensive for some. StreamSets provides an open-source version as a cost-effective choice, though its commercial support can be costly for small businesses. Matillion's AWS integration simplifies cost management, whereas StreamSets is appreciated for reducing time and resource investments, leading to significant ROI.
Consequently, we adjusted our processes to use Matillion Data Productivity Cloud only for extraction and ingestion, while Snowflake handled all transformations and jobs.
They communicate effectively and respond quickly to all inquiries.
IBM technical support sometimes transfers tickets between different teams due to shift changes, which can be frustrating.
The autoscale process works well, allowing the system to start another node automatically if the first machine reaches 80% capacity.
Connections to BigQuery for extracting information are complex.
It would be beneficial if StreamSets addressed any potential memory leak issues to prevent unnecessary upgrades.
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.
Matillion Data Productivity Cloud is effective for ingest functions, particularly when moving information to Snowflake and performing many transformations.
It allows a hybrid installation approach, rather than being completely cloud-based or on-premises.
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.
StreamSets is a data integration platform that enables organizations to efficiently move and process data across various systems. It offers a user-friendly interface for designing, deploying, and managing data pipelines, allowing users to easily connect to various data sources and destinations. StreamSets also provides real-time monitoring and alerting capabilities, ensuring that data is flowing smoothly and any issues are quickly addressed.
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