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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.
I received great support in migrating data to Snowflake, with quick responses and innovative solutions.
The technical support from Snowflake is very good, nice, and efficient.
The autoscale process works well, allowing the system to start another node automatically if the first machine reaches 80% capacity.
Snowflake is very scalable and has a dedicated team constantly improving the product.
The billing doubles with size increase, but processing does not necessarily speed up accordingly.
Snowflake is very stable, especially when used with AWS.
Snowflake as a SaaS offering means that maintenance isn't an issue for me.
Connections to BigQuery for extracting information are complex.
Enhancements in user experience for data observability and quality checks would be beneficial, as these tasks currently require SQL coding, which might be challenging for some users.
Cost reduction is one area I would like Snowflake to improve.
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.
Snowflake's pricing is on the higher side.
Snowflake lacks transparency in estimating resource usage.
Matillion Data Productivity Cloud is effective for ingest functions, particularly when moving information to Snowflake and performing many transformations.
The independence of the compute and storage within Snowflake is key.
Snowflake is a data lake on the cloud where all processing happens in memory, resulting in very fast query responses.
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.
Snowflake provides a modern data warehousing solution with features designed for seamless integration, scalability, and consumption-based pricing. It handles large datasets efficiently, making it a market leader for businesses migrating to the cloud.
Snowflake offers a flexible architecture that separates storage and compute resources, supporting efficient ETL jobs. Known for scalability and ease of use, it features built-in time zone conversion and robust data sharing capabilities. Its enhanced security, performance, and ability to handle semi-structured data are notable. Users suggest improvements in UI, pricing, on-premises integration, and data science functions, while calling for better transaction performance and machine learning capabilities. Users benefit from effective SQL querying, real-time analytics, and sharing options, supporting comprehensive data analysis with tools like Tableau and Power BI.
What are Snowflake's Key Features?In industries like finance, healthcare, and retail, Snowflake's flexible data warehousing and analytics capabilities facilitate cloud migration, streamline data storage, and allow organizations to consolidate data from multiple sources for advanced insights and AI-driven strategies. Its integration with analytics tools supports comprehensive data analysis and reporting tasks.
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