Founded in 1976, SAS has established itself as a global leader in analytics, business intelligence, and data management. The vendor’s data integration and engineering offerings currently serve a diverse user base reflected in the survey’s deployment model results: 30% operate on premises using traditional SAS Data Integration and Data Management, 35% have adopted cloud-based deployments (SaaS, public cloud, or private cloud), and 35% run hybrid environments. This distribution reveals an active platform transition in progress. SAS Data Management represents a comprehensive suite that includes traditional on-premises components such as Data Integration Server and Studio. In contrast, SAS Data Engineering, as part of the cloud-native SAS Viya platform, represents the vendor’s strategic direction. Viya offers an open architecture supporting multiple programming languages including SAS, Python, R, and Lua, marking a significant functional and architectural evolution from the traditional platform. SAS’s guidance to customers reflects this transition strategy: maintain existing SAS 9 and Data Integration Studio installations while planning and executing a gradual migration of data integration workloads to SAS Data Engineering and SAS Studio Flows on Viya.
The survey population employs SAS Data Engineering across core use cases including data warehousing and business intelligence (65%), data integration (60%), and advanced analytics (60%). Notably, AI and machine learning adoption has grown from 17% in the 2024 survey to 25% in 2026, a shift attributable to Viya’s enhanced capabilities in this domain. Real-time analytics and streaming use cases have similarly expanded to 15%. The user base shows a median deployment of 50 users with a mean of 198, serving primarily mid-market organizations with 100 to 2,500 employees (55%) and large enterprises exceeding 2,500 employees (45%).
SAS Data Engineering achieved exceptional results in the Data Fabric Survey 26, ranking first in Business Value (7.6/10) and Technical Foundation (8.3/10) across all three peer groups: ETL Tools, Data Engineering Tools, and Data Engineering (Big Players). Within the Technical Foundation category of KPIs, the product captured first-place rankings across all sub-categories, including Platform Reliability (8.5/10), Connectivity (8.5/10), Scalability (8.8/10), and Data Security & Privacy (8.6/10). Ease of Use is also highly rated with a score of 7.9/10, representing a notable differentiator among data engineering solutions from large vendors. Additional strong performance areas include Product Satisfaction (8.5/10), Project Success (8.2/10), and User Support (7.9/10). However, SAS achieved mid-tier rankings for Price to Value (7.0/10) and Time to Market (7.0/10), while Product Enhancements received lower ratings (6.6/10), likely reflecting the maintenance mode status of traditional SAS Data Integration and Data Management components.
Customers cite functional capabilities (60%) and scalability (60%) as primary reasons for selecting SAS Data Engineering, both significantly above the survey average. Reliability (45%), pre-existing vendor relationships (40%), and product roadmap confidence (35%) also score well above average, reflecting both the enduring trust in the traditional SAS 9 platform and growing confidence in Viya’s maturity. An interesting dynamic emerges around platform integration: while customers clearly value SAS’s strong intra-platform integration capabilities – evidenced by the first-place Technical Foundation ranking – concerns about fit into existing technology landscapes (25% versus 44% average) and ecosystem flexibility suggest the proprietary architecture creates external integration challenges.
The most frequently reported problems center on pricing and flexibility. Issues with pricing models and increasing software costs (28% versus 19% average), difficulty in customization and insufficient flexibility (22% versus 8% average), and license model inflexibility (17% versus 7% average) are all cited by an above-average proportion of SAS customers. These concerns align with the lower ratings for price/performance ratio as a buying reason (20% versus 37% average). On a positive note, only 6% of respondents find the tool too difficult for business users, well below the 19% average, reinforcing the platform’s accessibility strength. Additionally, 33% report no significant problems, which is above the 26% average.
SAS demonstrates exceptional technical foundation and business value while navigating a platform transition that presents both opportunities and challenges. The vendor’s strength in business user accessibility and proven reliability is offset by persistent pricing and flexibility concerns.
