Apache Spark Analytics with JupyterLab and Spark Connect by Code Creator
BerriAI · Software Development
Certification per AWS Marketplace.
Evidence tier Source Confirmed · 4 captures on record
What the publisher says
As described on AWS Marketplace.
This is a repackaged open source software product wherein additional charges are applied for the deployment of the application and AMI support and compliance. Apache Spark Analytics Workbench with JupyterLab and Spark Connect is a preconfigured analytics environment built for teams and developers who want a faster path to working with Apache Spark on AWS. It provides a browser based JupyterLab workspace, Apache Spark master and worker services, Spark Connect for modern client server workflows, and a Spark History Server for reviewing completed jobs. The product is designed for simple launch and access by public IP address so customers can begin working without requiring a domain name.
This AMI is built on Ubuntu and is designed to reduce setup time for data engineering, notebook based experimentation, distributed job execution, ETL development, analytics learning, and Spark testing. Internal Spark interfaces are kept private for safer operation while the main user experience is delivered through JupyterLab. The environment is configured to auto start on boot and includes first boot guidance to help users quickly retrieve login details and begin using the platform.
Show the rest of the publisher’s description (1 more line)
Apache Spark Analytics Workbench with JupyterLab and Spark Connect is well suited for developers, analysts, data engineers, students, and organizations that want a practical Spark workspace on AWS without building the full environment by hand.
Highlights
Highlighted by the publisher on AWS Marketplace.
Ready to use Spark analytics workspace Launch Apache Spark with JupyterLab and Spark Connect on Ubuntu 24.04 and start working from your browser using the instance public IP address with no domain name required.
Faster setup for data and notebook workflows Run distributed Spark jobs, explore data in Jupyter notebooks, and test analytics workloads without spending time building and wiring the environment by hand.
Built for practical AWS use Includes auto start on boot, first boot access guidance, private internal Spark services for safer operation, and a cleaner user friendly experience for developers analysts and data teams
Agent build and provenance
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The layer-by-layer build, the evidence behind each claim, the risk basis and the cross-marketplace links are open to any account. Some rows are disclosed, some the source leaves Unknown; a free account shows you which.
Compliance
- FedRAMPConfirmedNot listed90%, registry-checkedNo FedRAMP Marketplace entry matched this vendor's domain, checked 2026-08-27registry recordas observed 2026-08-27
Confirmed means matched to a public authoritative registry. Claimed means the vendor or its listing states it, not yet cross-checked. A framework not shown was not found in any source we hold, which is not evidence against it. Not listed means a scoped registry check found no match for this vendor's domain: a No is a scoped registry check, not a compliance judgment. Confidence bands: 95% domain-verified, 90% registry-checked, 80% self-attested, 70% weak signal. Self-attested items marked “vendor's site” are gathered from the vendor's own website and are not verified by us.
Vendor
External enrichment · as of 2026-08-13
Plans and pricing as listed
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Refund terms
As stated by the publisher on AWS Marketplace.
No contracts. We do not currently support refunds, but you can cancel at any time.
Sources
Publisher resources
2 linksLinked repositories
Unknown means this listing does not publish a repository. It is not a statement that the code is closed, and a linked repository is not a claim that the publisher wrote it: the registry computes that relationship privately and does not publish it.
Evidence risk is the share of the build you cannot see before you deploy, not a security rating. Sign in to see the layer-by-layer basis for this band.