Sold by: Tom Sawyer Software
Deployed on AWS
Deploy your Tom Sawyer Perspectives graph and data visualization and analysis applications on Amazon Web Services (AWS). Tom Sawyer Perspectives integrates enterprise data sources with powerful graph visualization, layout, and analysis technology to solve big data problems.
Overview
Tom Sawyer Perspectives is a data-driven platform for building graph and data visualization and analysis applications. Global clients use Tom Sawyer Perspectives to design aircraft and automobiles, manage networks, detect fraud, and more. They are able to federate and integrate across a wide variety of enterprise data sources and rapidly build advanced visualization and analysis applications.
Tom Sawyer Perspectives Deployment Container empowers clients to deploy Tom Sawyer Perspectives applications on AWS and auto-scale the deployment on demand.
Tom Sawyer Software is the leading provider of software and services that enable organizations to build highly scalable and flexible graph and data visualization and analysis applications. These applications are used to discover hidden patterns, complex relationships, and key trends in large and diverse datasets. Tom Sawyer Software serves clients with needs in link analysis; network topology; architectures and models; schematics and maps; and dependencies, flows, and processes. We help clients federate and integrate their data from multiple sources and build the graph and data visualization applications that are critical to analyzing and gaining insight into their data.
Start your evaluation of Tom Sawyer Perspectives [https://www.tomsawyer.com/evaluation ] to build your graph and data visualization and analysis application and then deploy to AWS with the Tom Sawyer Perspectives Deployment Container.
Highlights
- Tom Sawyer Perspectives Deployment Container facilitates fast and easy deployment of your Tom Sawyer Perspectives graph and data visualization applications. The container auto-scales up and down based on the usage of your application.
- Powerful bundle, circular, hierarchical, orthogonal, and symmetric layout styles enable dynamic exploration of data relationships. Drawings, maps, charts, timelines, tables, trees, and inspectors facilitate visual analysis.
- Federate data from multiple data sources into a single data model. Address analytic problems with clustering and partitioning; dependency, impact, and root-cause analysis; path finding; traversals; network flow; and social network analysis.
Details
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Delivery method
Supported services
Delivery option
Scalable Application Deployment Container
Latest version
Operating system
Linux
Deployed on AWS
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Pricing
Pricing is based on actual usage, with charges varying according to how much you consume. Subscriptions have no end date and may be canceled any time. Alternatively, you can pay upfront for a contract, which typically covers your anticipated usage for the contract duration. Any usage beyond contract will incur additional usage-based costs.
Additional AWS infrastructure costs may apply. Use the AWS Pricing Calculator to estimate your infrastructure costs.
Dimension | Cost/host/hour |
|---|---|
vCPU | $0.30 |
Memory in GB | $0.60 |
Dimensions summary
You pay for this deployment container based on the compute resources it consumes, not a flat fee. Two usage dimensions bill separately: vCPU and Memory in GB, both measured per host hour (HostHrs). Your cost scales with how much processing power and memory your hosted graph visualization application uses over time. As you run larger or busier workloads, both dimensions add up independently. This usage-based model lets you match spending to actual deployment size rather than committing to a fixed amount upfront.
Top-of-mind questions for buyers
Both dimensions meter per host hour (HostHrs). One vCPU unit is one virtual processor core running for one hour on the container host. Memory bills per gigabyte allocated per hour. The system counts the resources your hosted graph visualization application consumes as it runs.
Charges accrue per host hour while the container runs and uses vCPU and memory. When the container is fully stopped, software metering stops for both dimensions. Underlying AWS infrastructure fees, such as storage, may still apply separately from these usage charges.
Both dimensions bill independently and appear on the same invoice. Compute-heavy graph analysis, like running layout or shortest-path algorithms, raises vCPU hours. Loading large in-memory graph models raises memory hours. Your workload type decides which dimension dominates; both scale with running time.
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Delivery details
Scalable Application Deployment Container
Supported services: Learn more
- Amazon ECS
- Amazon EKS
Container image
Containers are lightweight, portable execution environments that wrap server application software in a filesystem that includes everything it needs to run. Container applications run on supported container runtimes and orchestration services, such as Amazon Elastic Container Service (Amazon ECS) or Amazon Elastic Kubernetes Service (Amazon EKS). Both eliminate the need for you to install and operate your own container orchestration software by managing and scheduling containers on a scalable cluster of virtual machines.
Version release notes
Tom Sawyer Perspectives 13.6.0 introduces the annotations graph commenting system that allows users to capture and organize context directly within their graphs, improving clarity and supporting more effective visualization and understanding. Also, support has been added for QLever databases, Amazon Neptune Analytics graph engines, and for Java date and time APIs.
The new layout on interactive diagramming option preserves orthogonality of edges on drop actions in order to to provide cleaner handling of dynamic interactions and more stable and visually consistent diagrams. Hierarchical layout with polyline edge routing with a medium layout quality setting is now up to 10% faster.
Perspectives has been upgraded to Spring Framework 6.2.17, and Spring Boot 3.5.13. Also, many third-party libraries have been updated to eliminate potential vulnerabilities.
Additional details
Usage instructions
To create your Tom Sawyer Perspectives Deployment container: - Use the Docker image provided to build your custom deployment application. - Set your Tom Sawyer Perspectives deployment libraries as provided by the container image and load them from the container directory /TomSawyer/lib.
You can review: - An example of a Tom Sawyer Perspectives deployment in the container directory /TomSawyer/network-editor. The application visualizes equipment connections in a network. - Our AWS CloudFormation templates. The templates show how to start this demonstration as an autoscalable service in an AWS Fargate cluster."
Resources
Vendor resources
Support
Vendor support
Support is included with Tom Sawyer Perspectives. Visit our support page to sign up for support or submit a support request. We also offer a full range of professional services to build custom graph and data visualization applications. This includes end-user training and assistance in designing, building and deploying enterprise applications built with Tom Sawyer Perspectives. Visit <www.tomsawyer.com/sales > to learn more. Sign up for support at <www.tomsawyer.com/aws-marketplace-support >. If you have any questions or comments about Tom Sawyer Perspectives Deployment Container, contact us at aws.marketplace@tomsawyer.com .
AWS infrastructure support
AWS Support is a one-on-one, fast-response support channel that is staffed 24x7x365 with experienced and technical support engineers. The service helps customers of all sizes and technical abilities to successfully utilize the products and features provided by Amazon Web Services.
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