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Alternatives to Consider
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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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TRACTIANTractian serves as the Industrial Copilot focused on enhancing maintenance and reliability by integrating both hardware and software to oversee asset performance, streamline industrial operations, and execute predictive maintenance approaches. The platform, powered by AI, enables companies to avert unexpected equipment failures and improve production efficiency. Headquartered in Atlanta, GA, Tractian also has a global footprint with branches in Mexico City and Sao Paulo, thereby expanding its reach. For more information, you can visit their website at tractian.com, where additional resources and details about their offerings are available.
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StarTreeStarTree Cloud functions as a fully-managed platform for real-time analytics, optimized for online analytical processing (OLAP) with exceptional speed and scalability tailored for user-facing applications. Leveraging the capabilities of Apache Pinot, it offers enterprise-level reliability along with advanced features such as tiered storage, scalable upserts, and a variety of additional indexes and connectors. The platform seamlessly integrates with transactional databases and event streaming technologies, enabling the ingestion of millions of events per second while indexing them for rapid query performance. Available on popular public clouds or for private SaaS deployment, StarTree Cloud caters to diverse organizational needs. Included within StarTree Cloud is the StarTree Data Manager, which facilitates the ingestion of data from both real-time sources—such as Amazon Kinesis, Apache Kafka, Apache Pulsar, or Redpanda—and batch data sources like Snowflake, Delta Lake, Google BigQuery, or object storage solutions like Amazon S3, Apache Flink, Apache Hadoop, and Apache Spark. Moreover, the system is enhanced by StarTree ThirdEye, an anomaly detection feature that monitors vital business metrics, sends alerts, and supports real-time root-cause analysis, ensuring that organizations can respond swiftly to any emerging issues. This comprehensive suite of tools not only streamlines data management but also empowers organizations to maintain optimal performance and make informed decisions based on their analytics.
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Google Compute EngineGoogle's Compute Engine, which falls under the category of infrastructure as a service (IaaS), enables businesses to create and manage virtual machines in the cloud. This platform facilitates cloud transformation by offering computing infrastructure in both standard sizes and custom machine configurations. General-purpose machines, like the E2, N1, N2, and N2D, strike a balance between cost and performance, making them suitable for a variety of applications. For workloads that demand high processing power, compute-optimized machines (C2) deliver superior performance with advanced virtual CPUs. Memory-optimized systems (M2) are tailored for applications requiring extensive memory, making them perfect for in-memory database solutions. Additionally, accelerator-optimized machines (A2), which utilize A100 GPUs, cater to applications that have high computational demands. Users can integrate Compute Engine with other Google Cloud Services, including AI and machine learning or data analytics tools, to enhance their capabilities. To maintain sufficient application capacity during scaling, reservations are available, providing users with peace of mind. Furthermore, financial savings can be achieved through sustained-use discounts, and even greater savings can be realized with committed-use discounts, making it an attractive option for organizations looking to optimize their cloud spending. Overall, Compute Engine is designed not only to meet current needs but also to adapt and grow with future demands.
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Google Cloud PlatformGoogle Cloud serves as an online platform where users can develop anything from basic websites to intricate business applications, catering to organizations of all sizes. New users are welcomed with a generous offer of $300 in credits, enabling them to experiment, deploy, and manage their workloads effectively, while also gaining access to over 25 products at no cost. Leveraging Google's foundational data analytics and machine learning capabilities, this service is accessible to all types of enterprises and emphasizes security and comprehensive features. By harnessing big data, businesses can enhance their products and accelerate their decision-making processes. The platform supports a seamless transition from initial prototypes to fully operational products, even scaling to accommodate global demands without concerns about reliability, capacity, or performance issues. With virtual machines that boast a strong performance-to-cost ratio and a fully-managed application development environment, users can also take advantage of high-performance, scalable, and resilient storage and database solutions. Furthermore, Google's private fiber network provides cutting-edge software-defined networking options, along with fully managed data warehousing, data exploration tools, and support for Hadoop/Spark as well as messaging services, making it an all-encompassing solution for modern digital needs.
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RunMyJobs by RedwoodRunMyJobs by Redwood stands out as the leading SAP-certified SaaS workload automation platform, enabling organizations to seamlessly automate their entire IT processes and integrate complex workflows across any application, system, or environment without restrictions while ensuring high availability as they grow. Recognized as the top choice for SAP customers, it offers effortless integration with S/4HANA, BTP, RISE, ECC, and additional platforms, all while preserving a clean core architecture. Teams are empowered through a user-friendly low-code editor and an extensive library of templates, facilitating smooth integration with both current and emerging technology stacks. Users can monitor their processes in real-time, benefiting from predictive SLA management and receiving timely notifications via email or SMS regarding any performance issues or delays that may arise. The Redwood team is committed to providing round-the-clock global support with industry-leading SLAs and rapid response times of just 15 minutes, alongside a well-established migration strategy that guarantees uninterrupted operations, including team training and on-demand learning resources to ensure success. Furthermore, Redwood's dedication to customer satisfaction ensures that businesses can focus on innovation while relying on robust support and automation solutions.
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Kasm WorkspacesKasm Workspaces enables you to access your work environment seamlessly through your web browser, regardless of the device or location you are in. This innovative platform is transforming the delivery of digital workspaces for organizations by utilizing open-source, web-native container streaming technology, which allows for a contemporary approach to Desktop as a Service, application streaming, and secure browser isolation. Beyond just a service, Kasm functions as a versatile platform equipped with a powerful API that can be tailored to suit your specific requirements, accommodating any scale of operation. Workspaces can be implemented wherever necessary, whether on-premise—including in Air-Gapped Networks—within cloud environments (both public and private), or through a hybrid approach that combines elements of both. Additionally, Kasm's flexibility ensures that it can adapt to the evolving needs of modern businesses.
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DataBuckEnsuring the integrity of Big Data Quality is crucial for maintaining data that is secure, precise, and comprehensive. As data transitions across various IT infrastructures or is housed within Data Lakes, it faces significant challenges in reliability. The primary Big Data issues include: (i) Unidentified inaccuracies in the incoming data, (ii) the desynchronization of multiple data sources over time, (iii) unanticipated structural changes to data in downstream operations, and (iv) the complications arising from diverse IT platforms like Hadoop, Data Warehouses, and Cloud systems. When data shifts between these systems, such as moving from a Data Warehouse to a Hadoop ecosystem, NoSQL database, or Cloud services, it can encounter unforeseen problems. Additionally, data may fluctuate unexpectedly due to ineffective processes, haphazard data governance, poor storage solutions, and a lack of oversight regarding certain data sources, particularly those from external vendors. To address these challenges, DataBuck serves as an autonomous, self-learning validation and data matching tool specifically designed for Big Data Quality. By utilizing advanced algorithms, DataBuck enhances the verification process, ensuring a higher level of data trustworthiness and reliability throughout its lifecycle.
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HighchartsHighcharts is a JavaScript charting library that simplifies the integration of interactive charts and graphs into web or mobile applications, regardless of their scale. This library is favored by over 80% of the top 100 global companies and is widely utilized by numerous developers across diverse sectors such as finance, publishing, app development, and data analytics. Since its inception in 2009, Highcharts has been continuously developed and improved, earning a loyal following among developers thanks to its extensive features, user-friendly documentation, accessibility options, and active community support. Its ongoing updates and enhancements ensure that it remains at the forefront of data visualization tools, meeting the evolving needs of modern developers.
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Adaptive Compliance Engine (ACE)The Adaptive Compliance Engine® (ACE®) is a versatile, workflow-driven eQMS/eDMS solution that can seamlessly adjust to various business processes, providing real-time oversight, management, and reporting for compliance, quality, and operational tasks. By utilizing ACE®, organizations can alleviate administrative burdens and enhance ROI through immediate productivity improvements, while maintaining adherence to 21 CFR Part 11 regulations. Our comprehensive software suite features: -Office 365 Integration -Inspection Management -Document Management -Risk Management -Product Lifecycle Management -Learning Management -Audit Management -Quality Events -Paperless Validation -Electronic Signatures (21 CFR Part 11 Compliant) -Endless Workflow Configurations -And numerous additional capabilities! Enable every tier of your organization with user-friendly interfaces, effortlessly locate all documents and records, and convert your data into insightful intelligence through advanced analytics, all within one unified platform. Every essential application is bundled together at a single price with ACE, eliminating the need for separate purchases. Enjoy the convenience of one software solution with countless functionalities, making it a truly invaluable asset for your business.
What is SAS Analytics for IoT?
Leverage an all-encompassing, AI-driven approach to effectively access, organize, select, and transform data derived from the Internet of Things. SAS Analytics for IoT encompasses the full analytics life cycle linked to IoT, featuring a seamless and flexible ETL process, a data model prioritizing sensor data, and a sophisticated analytics framework enhanced by an elite streaming execution engine that enables intricate multi-phase analytics. Built on SAS® Viya®, this solution functions adeptly within a rapid, in-memory distributed environment. Learn how to develop SAS Event Stream Processing applications that can manage high-volume and high-velocity data streams, providing instantaneous responses while retaining only crucial data elements. This course covers the fundamental concepts of event stream processing, explaining the various component objects that can be employed to create efficient event stream processing applications. Our dedication to curiosity fuels innovation, as SAS analytics solutions transform raw data into actionable insights, empowering clients worldwide to embark on ambitious new projects that promote growth. By embracing the future of data analytics with SAS, organizations can unlock a realm of endless possibilities and drive transformative change. Through this journey, businesses will not only enhance their operations but also gain a competitive edge in their respective industries.
What is Pratexo?
Pratexo dramatically accelerates the processes of developing, assessing, and deploying the distributed systems that are crucial for sophisticated applications in fields such as artificial intelligence, the Internet of Things, and Industry 4.0. By leveraging well-established and open technologies, Pratexo provides a secure and resilient platform that is customized to meet the specific needs of your application. For these transformative applications to operate effectively, they must have the capability to detect, analyze, and respond to enormous volumes of data in real-time. This requirement leads to the necessity for a distributed cloud infrastructure that offers vital cloud services across multiple locations, particularly nearer to the edge. The task of designing and implementing such architectures and applications is not only complex but also introduces various challenges. Applications that initially demonstrate strong performance may encounter difficulties in sustaining efficiency when scaled and can struggle in real-world settings. Many proof-of-concept projects aimed at 'digital transformation' tend to either fail or take significantly longer to be market-ready than originally expected, highlighting the intricacies involved in this journey. Therefore, it becomes clear that a thoughtful and strategic approach is crucial to overcoming these obstacles and achieving successful outcomes in deployment. Additionally, addressing these challenges with innovative solutions can pave the way for more efficient and effective operational models in the future.
Integrations Supported
Capgemini Intelligent Automation Platform
DataTerrain
HPE Consumption Analytics
NVMesh
Omnio
Phonexia Voice Inspector
SAS Data Loader for Hadoop
SAS MDM
SAS Visual Statistics
SAS Viya
Integrations Supported
Capgemini Intelligent Automation Platform
DataTerrain
HPE Consumption Analytics
NVMesh
Omnio
Phonexia Voice Inspector
SAS Data Loader for Hadoop
SAS MDM
SAS Visual Statistics
SAS Viya
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 Institute
Company Location
United States
Company Website
support.sas.com/en/software/analytics-for-iot-support.html
Company Facts
Organization Name
Pratexo
Date Founded
2019
Company Location
United States
Company Website
pratexo.com
Categories and Features
IoT
Application Development
Big Data Analytics
Configuration Management
Connectivity Management
Data Collection
Data Management
Device Management
Performance Management
Prototyping
Visualization
IoT Analytics
Activity Dashboard
Activity Tracking
Analytics
Asset Tracking
Data Collection
Data Synchronization
Data Visualization
ETL
Multiple Data Sources
Performance Analysis
Real-Time Analytics
Real-Time Data
Real-Time Monitoring
Status Tracking
Categories and Features
Artificial Intelligence
Chatbot
For Healthcare
For Sales
For eCommerce
Image Recognition
Machine Learning
Multi-Language
Natural Language Processing
Predictive Analytics
Process/Workflow Automation
Rules-Based Automation
Virtual Personal Assistant (VPA)
IoT
Application Development
Big Data Analytics
Configuration Management
Connectivity Management
Data Collection
Data Management
Device Management
Performance Management
Prototyping
Visualization