Sold by: RRecktek
Deployed on AWS
AWS Free Tier
Version 5.0.1. Optimized parallel R 4.6.1 and Python analysis, 4,952 packages, with provenance-tracked memory
5
Overview
Current version: 5.0.1 (released 2026-08-30)
A complete, optimized data analysis environment in R and Python with a provenance-tracked analytical memory. Everything is built from source, tuned, and verified on a running instance.
What is installed
- R 4.6.1 built from source against OpenBLAS 0.3.29 with runtime CPU dispatch
- 4,952 R packages — 2,043 Bioconductor, 2,878 CRAN, including the full genomics stack
- Open MPI 4.1.6 with Rmpi, pbdMPI, doMPI, snow, foreach, doParallel, future and BiocParallel
- RStudio Server 2026.08.1
- Shiny Server 1.5.23
- Python 3.12.3 with numpy, scipy, pandas, scikit-learn and statsmodels, bridged to R through reticulate
- PostgreSQL 17 with pgvector, carrying pmem and HIVEMIND
- JDK 21 headless, for rJava and Java-backed packages
- Ubuntu 24.04 LTS
Performance
Measured on a running m5.2xlarge: 4.68x speedup across 8 cores, and 184 GFLOPS on a 2000x2000 matrix multiply through threaded OpenBLAS.
Graphics
cairo, PNG, JPEG, TIFF and Tcl/Tk are compiled in and work with no display attached, so plots and image output succeed on a headless server.
Provenance-tracked memory
Record a result with its lineage, supersede a conclusion without destroying what it replaced, and retrieve by meaning. Backed by the bundled PostgreSQL with pgvector.
Security
Runs entirely offline. All services bind to localhost and are reached over SSH with your own key. No credential ships in the image — the API token and RStudio password are generated per instance at first boot.
Highlights
- R 4.6.1 built from source against OpenBLAS 0.3.29 with runtime CPU dispatch. 4,952 packages: 2,043 Bioconductor and 2,878 CRAN, plus RStudio Server, Shiny Server and Python 3.12 bridged to R through reticulate.
- Open MPI 4.1.6 with Rmpi, pbdMPI, doMPI, snow, foreach, doParallel, future and BiocParallel. Measured on a running instance: 4.68x speedup across 8 cores, 184 GFLOPS on threaded OpenBLAS.
- Provenance-tracked analytical memory on bundled PostgreSQL 17 with pgvector: record a result with its lineage, supersede a conclusion without destroying what it replaced, and retrieve by meaning. Offline; no credential ships in the image. For a comprehensive feature exploration: www.predictiveanalyticsframework.com
Details
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Delivery method
Delivery option
64-bit (x86) Amazon Machine Image (AMI)
Latest version
Operating system
Ubuntu 24.04
Deployed on AWS
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Features and programs
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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.
Additional AWS infrastructure costs may apply. Use the AWS Pricing Calculator to estimate your infrastructure costs.
If you are an AWS Free Tier customer with a free plan, you are eligible to subscribe to this offer. You can use free credits to cover the cost of eligible AWS infrastructure. See AWS Free Tier for more details. If you created an AWS account before July 15th, 2025, and qualify for the Legacy AWS Free Tier, Amazon EC2 charges for Micro instances are free for up to 750 hours per month. See Legacy AWS Free Tier for more details.
Dimension | Description | Cost/hour |
|---|---|---|
m5.2xlarge Recommended | m5.2xlarge instance hour | $2.00 |
t2.micro | - | $1.00 |
c3.2xlarge | - | $2.00 |
c3.4xlarge | - | $2.00 |
c3.8xlarge | - | $2.00 |
c3.large | - | $2.00 |
c3.xlarge | - | $2.00 |
c4.2xlarge | - | $2.00 |
c4.4xlarge | - | $2.00 |
c4.8xlarge | - | $2.00 |
Dimensions summary
You pay by the hour based on the EC2 instance type you run. Pricing is usage-based, so charges accrue only while an instance is running. The dimensions map to AWS instance families: compute-optimized (c3, c4, c5), memory-optimized (r3, r5), storage-optimized (d2, i2, hs1, hi1), general-purpose (m3, m4, m5, t2, t3), GPU (g2, cg1), and specialized cluster types (cc1, cc2, cr1). Larger sizes within each family carry higher hourly rates. Choose the instance type that fits your workload; heavy linear algebra work benefits from larger compute or memory instances.
Top-of-mind questions for buyers
Each unit is one instance-hour of the EC2 instance type you launch. For example, running an m5.xlarge for one hour equals one m5.xlarge instance hour. You pay separately for each instance you run, and charges accrue for every hour that instance stays active.
Software charges meter running time only. A fully stopped instance stops accruing the hourly software fee. Stopped instances may still incur underlying AWS storage costs for attached volumes, but those are separate from this product's per-hour software rate.
The product's performance depends on the math library doing matrix work inside the BLAS. Workloads dominated by linear algebra, such as genomics or large regressions, benefit from compute-optimized or memory-optimized types. Workloads dominated by loops and string handling gain far less, so match the type to your pipeline mix.
www.predictiveanalyticsframework.com
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Vendor refund policy
We do not currently support refunds under any circumstances, but you can cancel at any time.
Legal
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Content disclaimer
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Delivery details
64-bit (x86) Amazon Machine Image (AMI)
Amazon Machine Image (AMI)
An AMI is a virtual image that provides the information required to launch an instance. Amazon EC2 (Elastic Compute Cloud) instances are virtual servers on which you can run your applications and workloads, offering varying combinations of CPU, memory, storage, and networking resources. You can launch as many instances from as many different AMIs as you need.
Version release notes
Additional details
Usage instructions
Connect over SSH with the key pair you selected at launch: ssh -i /path/my-key-pair.pem ubuntu@<public-dns> The SSH username is "ubuntu".
Every service binds to localhost and none is exposed to the network. Reach them over an SSH tunnel. RStudio Server: ssh -i /path/my-key-pair.pem -L 8787:127.0.0.1:8787 ubuntu@<public-dns> then open http://localhost:8787 . Shiny Server is on 3838 and the pmem API on 8130; tunnel them the same way.
The RStudio password is generated uniquely on this instance at first boot and is readable only by root on the instance. Retrieve it with: sudo cat /var/lib/paf/rstudio-credentials
PAF with hivemind runs a provenance-tracked analytical memory (pmem) on a bundled PostgreSQL. Documentation is on the instance under /opt/paf/docs.
Support
Vendor support
Email rreck@rrecktek.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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AI generated from product descriptions
R and Python Integration
R 4.6.1 built from source against OpenBLAS 0.3.29 with runtime CPU dispatch, 4,952 packages (2,043 Bioconductor, 2,878 CRAN), Python 3.12.3 with numpy, scipy, pandas, scikit-learn and statsmodels bridged to R through reticulate
Parallel Computing Framework
Open MPI 4.1.6 with Rmpi, pbdMPI, doMPI, snow, foreach, doParallel, future and BiocParallel, delivering 4.68x speedup across 8 cores and 184 GFLOPS on threaded OpenBLAS matrix operations
Provenance-Tracked Memory System
PostgreSQL 17 with pgvector backend enabling lineage tracking of analytical results, result superseding without data destruction, and semantic retrieval capabilities
Web-Based Development Interfaces
RStudio Server 2026.08.1 and Shiny Server 1.5.23 for interactive analysis and application development
Offline Security Architecture
Entirely offline operation with all services bound to localhost, SSH key-based access, and per-instance generated credentials at first boot with no embedded credentials in the image
Integrated Development Environment
RStudio Server provides an integrated development environment for R programming language with support for statistical computing, data analysis, and graphical visualization.
Pre-installed R Packages
Includes thousands of pre-installed R packages spanning multiple domains including data science, machine learning, econometrics, Bayesian statistics, natural language processing, genomics, and optimization.
Secure Communication Protocol
HTTPS encryption enabled for all data transmission between client browser and server, with automatic HTTP to HTTPS redirection and self-signed certificate support.
Web-based Access
RStudio Server accessible via web browser using public IP address with default authentication credentials.
Current R Version
Up-to-date R programming language version included with the environment.
N-Dimensional Array Processing
Provides comprehensive mathematical functions and linear algebra routines for handling n-dimensional arrays
Data Analysis and Manipulation
Open-source data analysis and manipulation tool built on Python programming language
Machine Learning Capabilities
Supports supervised and unsupervised learning with tools for model fitting, data preprocessing, model selection, and model evaluation
Web Interface for Model Demonstration
Enables creation and sharing of machine learning model demonstrations through a web interface using Python
Standard contract
No
Customer reviews
Omer
Excellent service
Reviewed on Apr 08, 2020
Review from a verified AWS customer
This allowed me to immediately get a dashboard up without having to build out the environment
or be lost in the details. It also had the latest versions of things which was a great plus
Martins
Great Support
Reviewed on Jan 24, 2017
Review from a verified AWS customer
RRecktek is providing great and very responsive support. We solved all technical problems over chat. At the end I got the Predictive Analytics Framework running.
OneConnxt
Delivers perfectly
Reviewed on Jan 23, 2017
Review from a verified AWS customer
This allows us to provide a consistent environment for
out-sourced developers. We are happy with the value it
provides as it saves us both time and money. We will
continue to use it.
H. Roland
When on one else could deliiver
Reviewed on Jan 28, 2015
Review from a verified AWS customer
We approached rrecktek with a proprietary use case, that we could not find anyone else, who even understood what we were trying to acheive. Not only did rrecktek understand, through the use of their software solutions, our use case is delivering to our projections. And, the visualization support is fantastic. Now, we are getting a lot of WOWs. rrecktek is now our "goto" company for our predictive needs.
Anil Dwivedi
value based solutions
Reviewed on Jan 27, 2015
Review from a verified AWS customer
i have been using components of this rrecktek software solution for more than 2.5 years for my business and am happy with the value it provides. I will continue to use it.