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RaimaDBRaimaDB is an embedded time series database designed specifically for Edge and IoT devices, capable of operating entirely in-memory. This powerful and lightweight relational database management system (RDBMS) is not only secure but has also been validated by over 20,000 developers globally, with deployments exceeding 25 million instances. It excels in high-performance environments and is tailored for critical applications across various sectors, particularly in edge computing and IoT. Its efficient architecture makes it particularly suitable for systems with limited resources, offering both in-memory and persistent storage capabilities. RaimaDB supports versatile data modeling, accommodating traditional relational approaches alongside direct relationships via network model sets. The database guarantees data integrity with ACID-compliant transactions and employs a variety of advanced indexing techniques, including B+Tree, Hash Table, R-Tree, and AVL-Tree, to enhance data accessibility and reliability. Furthermore, it is designed to handle real-time processing demands, featuring multi-version concurrency control (MVCC) and snapshot isolation, which collectively position it as a dependable choice for applications where both speed and stability are essential. This combination of features makes RaimaDB an invaluable asset for developers looking to optimize performance in their applications.
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What is SAS Health?
Elevate your digital transformation efforts while unlocking critical insights from your data with tailored health analytic solutions. With its user-friendly drag-and-drop interface, the SAS Health Cohort Builder empowers users to create and query cohorts based on temporal connections without requiring any coding experience. This intuitive tool facilitates the exploration of cohort characteristics and the effects of various inclusion or exclusion criteria on patient populations, aiding in the evaluation of study feasibility. Users can conveniently save cohort definitions for future applications, adjust them as necessary, and utilize them across various real-world data sources for comparative studies, ultimately saving both time and resources in the research process. Moreover, findings can be validated and further examined through in-memory processing and visualization capabilities within SAS or via other platforms like R, Python, as well as a range of third-party visualization tools. Conversely, SAS Health: Episode Builder grants you the flexibility to view and adjust episode definitions directly, putting you in control of the entire process. With SAS’s comprehensive documentation outlining the logic behind generating episodes of care, you can have confidence in the transparency and auditability of the underlying business rules, enhancing the integrity of your health data analytics. This blend of features not only streamlines the analytic process but also significantly positions SAS as a premier solution in the field of health analytics, making it an invaluable asset for healthcare professionals.
What is PicnicHealth?
PicnicHealth acts as a vital link connecting patients to researchers by delivering targeted and thorough real-world data. By collaborating with patients who voluntarily provide their medical histories for research, we can cultivate a rich understanding of patient health that includes insights from all healthcare providers rather than being confined to a single location or specialist. Our network of established patient communities, along with effective recruitment strategies through various direct-to-patient avenues, facilitates the easy assembly of the appropriate patient cohort. Patients can swiftly register and consent in just ten minutes, enabling them to access their medical records. If you have patients participating in ongoing registries or clinical trials, consider recommending PicnicHealth for a more efficient setup process. Our research platform is crafted to deliver customized real-world data at the individual patient level, allowing researchers to specify exactly which data elements, including doctors’ notes and narrative text, should be extracted from medical records. This innovative, patient-centric methodology not only amplifies the quality of the data collected but also motivates patients to engage actively in the research journey. By fostering this empowerment among patients, we aim to cultivate a more profound understanding of health outcomes, ultimately elevating the quality and relevance of research conducted in the field. Furthermore, this collaboration has the potential to inspire a greater sense of ownership among patients regarding their health information, leading to more robust participation in future studies.
Integrations Supported
Python
API Availability
Has API
API Availability
Has API
Pricing Information
Pricing not provided.
Free Trial Offered?
Free Version
Pricing Information
Pricing not provided.
Free Trial Offered?
Free Version
Supported Platforms
SaaS
Android
iPhone
iPad
Windows
Mac
On-Prem
Chromebook
Linux
Supported Platforms
SaaS
Android
iPhone
iPad
Windows
Mac
On-Prem
Chromebook
Linux
Customer Service / Support
Standard Support
24 Hour Support
Web-Based Support
Customer Service / Support
Standard Support
24 Hour Support
Web-Based Support
Training Options
Documentation Hub
Webinars
Online Training
On-Site Training
Training Options
Documentation Hub
Webinars
Online Training
On-Site Training
Company Facts
Organization Name
SAS
Company Location
United States
Company Website
www.sas.com/en_us/software/health.html
Company Facts
Organization Name
PicnicHealth
Date Founded
2014
Company Location
United States
Company Website
picnichealth.com/research-platform
Categories and Features
Categories and Features
Clinical Trial Management
21 CFR Part 11 Compliance
Document Management
Electronic Data Capture
Enrollment Management
HIPAA Compliant
Monitoring
Patient Database
Recruiting Management
Scheduling
Study Planning