

SAS Data Management and Fivetran provide distinct data solutions competing in data integration and management. Fivetran seems to have the upper hand for ease of use and scalability, while SAS Data Management stands out for its robust data handling features.
Features: SAS Data Management offers a comprehensive suite for data quality and integration, flexibility for analytics, and effective data-cleaning functions suitable for both cloud and big data environments. Fivetran excels in data replication, managed pipelines, and easy integration with other tools like DBT, offering simple and quick data pipeline setup and scalable data movements.
Room for Improvement: SAS Data Management faces challenges with expensive licensing, inflexible models, and requires enhanced database connectivity and a more intuitive setup. Fivetran could improve by addressing costly data syncing for high-volume data, offering more connectors, and enhancing customization options.
Ease of Deployment and Customer Service: SAS Data Management primarily uses an on-premises model with robust but potentially complex technical support needing consulting for intricate issues. Fivetran provides efficient customer service with ample room for technical support enhancement, offering wide cloud deployment capabilities.
Pricing and ROI: SAS Data Management is expensive but yields significant ROI through data reliability and reduced duplication, appealing in regulated sectors for compliance benefits. Fivetran's pricing is viewed as high; however, it offers scalability that can decrease costs per data unit with larger implementations.
Fivetran provides time savings, cost reductions, and improvements in data quality.
It saves us the effort of having one to two data engineers managing the tasks that Fivetran handles.
If they could provide support more quickly, that would be great.
The technical support provided by Fivetran has generally been good, with a response time and competence that I would rate as good.
Customer support from Fivetran is quite good; it's really nice and responsive.
The support for SAS in Brazil is not the best one, but the support in Sweden is really good, as they visit the company and work to solve the issues.
Fivetran's scalability has been tested effectively, and it has been working well for our organization's growing data needs.
They have 99.9% accuracy on the data load and they maintain transparency.
In my experience, Fivetran is stable with very few instances of downtime or reliability issues.
During the duration of the time that we used Fivetran, it was highly stable.
From a cost perspective, if the number of connectors is lesser, then Fivetran is not the most cost-efficient option.
When we tried to use a built-in Oracle connector, it didn't allow for the tweaks we needed, which led us to the SDK connector route and caused delays in development.
Fivetran could improve by adapting more for technical users and by providing more options for such users.
There is significant room for improvement, especially with regard to using a hybrid approach that involves both CAS and persistent storage.
Our current yearly contract for Fivetran is approximately $70,000.
From my experience, SAS Data Management is an expensive tool.
The most valuable feature of Fivetran is its built-in connectors for a wide range of data sources.
The real-time data replication is what I see best in the market where it reduces the overhead of customers needing to maintain the pipeline.
Fivetran not only has built-in connectors but also provides SDK connectors, allowing us to develop our own connectors in an easy manner.
The best features I appreciate about SAS Data Management tool are that it's easy to create the flows and schedule data, and the tables are not too big, making it easy to control the ETL process, including user access which is also easy to manage in SAS.
SAS Data Management stands out because of its data standardization, transformation, and verification capabilities.
| Product | Mindshare (%) |
|---|---|
| Fivetran | 1.8% |
| SAS Data Management | 1.3% |
| Other | 96.9% |

| Company Size | Count |
|---|---|
| Small Business | 10 |
| Midsize Enterprise | 7 |
| Large Enterprise | 16 |
| Company Size | Count |
|---|---|
| Small Business | 7 |
| Midsize Enterprise | 1 |
| Large Enterprise | 8 |
Fivetran offers a seamless, scalable data integration platform with strong connectors and real-time synchronization. Tailored for managing ETL workflows and integrating with DBT, it appeals to organizations seeking efficient data management.
Fivetran distinguishes itself through its intuitive interface and extensive scalability, allowing businesses to manage entire ETL workflows seamlessly. Its robust connectors ensure smooth integration with multiple data sources, while transparent logging and minimal coding requirements enhance accessibility. With real-time data synchronization, organizations benefit from up-to-date insights for analytics and engineering purposes. While some users point out areas for improvement like better documentation and expanded integration options, Fivetran remains a cherished tool for centralizing data in data warehouses such as supporting change data capture, migrations, and synchronizations from systems like Salesforce, NetSuite, and Google Analytics. Operating within an ELT framework, it empowers businesses to streamline data processes without complex extraction logic.
What are the key features of Fivetran?In industry-specific implementation, Fivetran is integral for businesses requiring robust data integration to power analytics. Retailers utilize it to consolidate e-commerce data for sales insights, while finance firms rely on its capabilities to merge financial data for reporting. In the tech sector, it supports engineering teams by providing a reliable data pipeline that fuels app development and performance monitoring.
SAS Data Management provides data integration, governance, and robust reporting tools. It connects to diverse data sources, ensuring quality management and enabling data analysis for technical and non-technical users.
SAS Data Management features flexible data flow creation, scheduling, and ETL control. It enhances data integration and metadata management with tools that support data standardization. Users benefit from its importing and exporting capabilities, connecting to multiple sources. It facilitates improved data quality management and offers a flexible language for diverse needs. Data visualization capabilities further support decision-making across industries, automating reports and data warehouses.
What are the key features of SAS Data Management?SAS Data Management helps industries like finance integrate diverse data sources for analytics and reporting. It is used for tasks such as financial reporting, credit risk analysis, and data cleansing. Through user-driven automation, it aids in aligning data warehouses and generating insightful visual outputs, making it ideal for analyzing structured data from sources like Excel and CSV files.
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