

Qlik Replicate and SAS Data Management compete in the data integration and management category. Qlik Replicate seems to have an upper hand due to its strong real-time data integration and Change Data Capture capabilities.
Features: Qlik Replicate focuses on real-time data integration, Change Data Capture, and extensive connector support. It offers ELT capabilities for a streamlined data process. SAS Data Management emphasizes robust data integration with powerful data sorting, categorizing, summarizing features and comprehensive data management and analysis capabilities.
Room for Improvement: Qlik Replicate users wish for better user-friendliness, error reporting, support responsiveness, more transparent licensing, and enhanced API integration. SAS Data Management could benefit from simplified connectivity, improved stability, better documentation, and a less complex installation and management process.
Ease of Deployment and Customer Service: Qlik Replicate offers flexible deployment options including public cloud, hybrid, and on-premises. However, its customer service experiences inconsistency with support delays and a focus on licensing issues. SAS Data Management is primarily on-premises and has unclear support processes, though it provides excellent assistance for specific issues.
Pricing and ROI: Qlik Replicate is considered costly, suitable for large enterprises but potentially expensive for smaller businesses. It offers significant ROI by lowering database usage and storage costs for real-time data operations. SAS Data Management is also expensive with less flexible pricing but delivers a comprehensive suite of tools that can provide valuable analytics and data management, supporting business insights and operational efficiencies.
I conducted a cost comparison with the AWS service provider, and this option is much cheaper than the Kinesis service offered by AWS.
Customers have seen ROI with Qlik Replicate because they get their data for analysis faster, enabling quicker decision-making compared to traditional data sourcing methods.
Even priority tickets, which should be resolved in minutes, can take days.
Support response times could be improved as there are sometimes delays in receiving replies to support cases.
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.
The system could be scaled to include more sources and functions.
It is a core-based licensing, which, especially in the banking industry, results in the system capacity being utilized up to a maximum of 60%.
Qlik Replicate could be improved in the next release by incorporating more monitoring options to monitor the logs.
There is significant room for improvement, especially with regard to using a hybrid approach that involves both CAS and persistent storage.
For Qlik Replicate, the setup cost includes the requirement of a server, which represents the hardware cost that must be covered.
Licensing is calculated based on the machine's total capacity rather than actual usage.
From my experience, SAS Data Management is an expensive tool.
The most valuable feature of Qlik Replicate is their change data capture feature.
Data retrieved from the system can be pushed to multiple places, supporting various divisions such as marketing, loans, and others.
SAS Data Management stands out because of its data standardization, transformation, and verification capabilities.
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.
| Product | Mindshare (%) |
|---|---|
| Qlik Replicate | 1.4% |
| SAS Data Management | 1.3% |
| Other | 97.3% |
| Company Size | Count |
|---|---|
| Small Business | 9 |
| Large Enterprise | 11 |
| Company Size | Count |
|---|---|
| Small Business | 7 |
| Midsize Enterprise | 1 |
| Large Enterprise | 8 |
Qlik Replicate offers log-based change data capture, supporting real-time data updates without affecting source databases. It manages schema changes automatically and ensures seamless data distribution. The platform is user-friendly, enables late-stage transformation, and supports incremental replication and real-time analytics.
Qlik Replicate is known for efficiently capturing data changes with minimal impact on source databases. Its log-based change data capture capabilities ensure quick propagation of updates in real-time while automatically handling schema changes, facilitating ease in data management. The system's seamless integration across endpoints and a user-friendly interface make it an invaluable tool for incremental replication and real-time analytics. Despite some challenges like UI freezing, complex licensing, and error handling, it is instrumental in enhancing business growth and operational efficiency. Users continuously seek improvements in error insights, data compression, and expanded API integration to better serve diverse data sources and platforms.
What are the key features of Qlik Replicate?Qlik Replicate is used across industries such as energy, banking, and semiconductors to modernize analytics environments and streamline data flows. It excels in data migration from systems like SAP HANA and Oracle to environments like AWS, significantly reducing downtime and boosting analytics capabilities. Organizations report advantages such as enhanced data accessibility and automated data modeling, which facilitates efficient change data capture and operational effectiveness.
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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