# Best AWS Marketplace Software - Page 71

## How Many AWS Marketplace Software Products Does G2 Track?

**Total Products under this Category:** 2,544

### Category Stats (Jul 2026)

- **Average Rating:** 4.4/5 The average rating of products in this category, based on all submitted ratings
- **Top Trending Product:** Wordpress for Centos8 (+1.19%) - Among all products in this category, Wordpress for Centos8 recorded the largest rating increase compared to last month

_Last updated: July 26, 2026_

## How Does G2 Rank AWS Marketplace Software Products?

**Why You Can Trust G2's Software Rankings:**

- 30 Analysts and Data Experts
- 29,700+ Authentic Reviews
- 2,544+ Products
- Unbiased Rankings

G2's software rankings are built on verified user reviews, rigorous moderation, and a consistent research methodology maintained by a team of analysts and data experts. Each product is measured using the same transparent criteria, with no paid placement or vendor influence. While reviews reflect real user experiences, which can be subjective, they offer valuable insight into how software performs in the hands of professionals. Together, these inputs power the G2 Score, a standardized way to compare tools within every category.

**Sponsored**

### Fortinet Managed Rules for AWS WAF

Fortinet’s WAF rulesets are additional security signatures that can be used to enhance the protections included in the base AWS WAF product. They are updated on a regular basis to include the latest threat intelligence from the award-winning FortiGuard Labs. The Complete OWASP Top 10 Ruleset provides a comprehensive package for web application protection offered by Fortinet to help address the OWASP Top 10 web application threats. Includes protection for various Injection attacks such as SQL and command Injection , Cross Site Scripting, General and Known Exploits, Malicious Bots and Common Vulnerabilities and Exposures (CVE).

[Visit website](https://www.g2.com/external_clickthroughs/record?secure%5Bad_program%5D=ppc&secure%5Bad_slot%5D=category_product_list&secure%5Bcategory_id%5D=2598&secure%5Bchosen_at%5D=2026-07-30T00%3A17%3A55Z&secure%5Bdisplayable_resource_id%5D=2598&secure%5Bdisplayable_resource_type%5D=Category&secure%5Bmedium%5D=sponsored&secure%5Bplacement_reason%5D=page_category&secure%5Bplacement_resource_ids%5D%5B%5D=2598&secure%5Bprioritized%5D=false&secure%5Bproduct_id%5D=145276&secure%5Bresource_id%5D=2598&secure%5Bresource_type%5D=Category&secure%5Bsource_type%5D=category_page&secure%5Bsource_url%5D=https%3A%2F%2Fwww.g2.com%2Fcategories%2Faws-marketplace%3Fpage%3D71&secure%5Btoken%5D=b176b5faf143d27bdfa241e73e81c8595ebbfd2677672a2da417f89595becdb4&secure%5Burl%5D=https%3A%2F%2Fwaf-security.com%2F%3Futm_source%3Dg2%26utm_medium%3Dcpc%26utm_id%3Ddirect-publisher&secure%5Burl_type%5D=custom_url)

### [Deepgreen DB](https://www.g2.com/products/deepgreen-db/reviews)

Deepgreen DB is an advanced, massively parallel processing (MPP database designed to enhance data warehousing and analytics performance. Building upon the Greenplum database, Deepgreen DB offers significant optimizations, including up to 5x faster execution of TPC-H benchmarks compared to its predecessor. Its architecture supports seamless integration with various data sources and cloud storage solutions, facilitating efficient data management and analysis. Key Features and Functionality: - Enhanced Performance: Deepgreen DB delivers substantial speed improvements, enabling clusters to handle more extensive workloads without the need for costly expansions. - Broad Connectivity: The database effortlessly connects to cloud storage and diverse data sources such as HDFS, S3, Oracle, Geode, and Elasticsearch. This capability allows for dynamic querying of fresh data from external sources without prior loading. - Advanced Analytics Integration: Deepgreen DB's tight integration with TensorFlow facilitates high-bandwidth machine learning training and enables in-database inference using SQL. - True Sampling Support: The database includes built-in support for true sampling with SQL, allowing users to sample data by a specific number of rows or by percentage, enhancing analytical flexibility. - Compatibility and Ease of Transition: Deepgreen DB is 100% binary compatible with Greenplum, making the transition process straightforward: 1. Stop Greenplum 2. Swap binaries 3. Start Deepgreen Primary Value and User Solutions: Deepgreen DB addresses the critical need for high-performance, scalable, and flexible data warehousing solutions. By offering significant speed enhancements and seamless integration with various data sources, it empowers organizations to manage and analyze large datasets more efficiently. The compatibility with Greenplum ensures a smooth transition, minimizing downtime and leveraging existing infrastructure investments. Additionally, the integration with machine learning frameworks like TensorFlow positions Deepgreen DB as a comprehensive platform for advanced analytics, enabling users to derive deeper insights and drive data-driven decision-making.

#### Who Is the Company Behind Deepgreen DB?

- **Seller:** [Vitesse Data](https://www.g2.com/sellers/vitesse-data)
- **Year Founded:** 2014
- **HQ Location:** N/A
- **LinkedIn® Page:** [www.linkedin.com](https://www.g2.com/external_clickthroughs/record?secure%5Bsource_type%5D=product_profile&secure%5Btoken%5D=99455c66c69ef7aa328157a8ac22dcf83beb2f082d819b7606828b7c068718d5&secure%5Burl%5D=http%3A%2F%2Fwww.linkedin.com%2Fcompany%2Fvitesse-data&secure%5Burl_type%5D=linkedin_company_website)  
4 employees on LinkedIn®

### [DeepInsights Named Entity Recognizer](https://www.g2.com/products/deepinsights-named-entity-recognizer/reviews)

DeepInsights Named Entity Recognizer is an advanced tool designed to extract and classify named entities from unstructured text, enabling businesses to transform raw data into actionable insights. By identifying specific entities such as names, organizations, locations, dates, and more, it enhances data analysis and decision-making processes. Key Features and Functionality: - Entity Extraction: Accurately identifies and categorizes entities like people, organizations, locations, dates, and custom-defined entities within text. - Custom Entity Recognition: Allows users to define and train models for recognizing domain-specific entities unique to their business needs. - Scalability: Capable of processing large volumes of text data efficiently, making it suitable for enterprises of various sizes. - Integration: Seamlessly integrates with existing workflows and applications, facilitating easy deployment and use. Primary Value and Problem Solved: DeepInsights Named Entity Recognizer addresses the challenge of extracting meaningful information from vast amounts of unstructured text data. By automating the identification and classification of entities, it reduces manual effort, minimizes errors, and accelerates data processing. This leads to improved data-driven decision-making, enhanced customer insights, and more efficient business operations.

#### Who Is the Company Behind DeepInsights Named Entity Recognizer?

- **Seller:** [Mphasis](https://www.g2.com/sellers/mphasis-5a2b4772-cd1c-4cbd-bf88-54fc79a85d25)
- **Year Founded:** 2007
- **HQ Location:** Reston, VA
- **Twitter:** @Stelligent  
1,106 Twitter followers
- **LinkedIn® Page:** [www.linkedin.com](https://www.g2.com/external_clickthroughs/record?secure%5Bsource_type%5D=product_profile&secure%5Btoken%5D=ace0aa7310e9fd4ef0facca25c9ef8b08d319acab135d8d95d5c03e74d84f199&secure%5Burl%5D=https%3A%2F%2Fwww.linkedin.com%2Fcompany%2F220927&secure%5Burl_type%5D=linkedin_company_website)  
14 employees on LinkedIn®

### [Deep Learning AMI Amazon Linux 2 with Support by Supported Images](https://www.g2.com/products/deep-learning-ami-amazon-linux-2-with-support-by-supported-images/reviews)

The Deep Learning AMI (Amazon Linux 2 with Support by Supported Images) is a pre-configured Amazon Machine Image designed to streamline the development and deployment of deep learning applications on Amazon EC2 instances. This AMI comes equipped with essential deep learning frameworks, libraries, and tools, enabling researchers and developers to efficiently build, train, and deploy machine learning models without the need for extensive setup. Key Features and Functionality: - Pre-installed Deep Learning Frameworks: Includes popular frameworks such as TensorFlow and PyTorch, facilitating immediate development and training of models. - Optimized for Amazon EC2: Tailored to leverage the computational power of EC2 instances, ensuring high performance and scalability for deep learning tasks. - Comprehensive Toolset: Comes with NVIDIA CUDA drivers, cuDNN, and other essential libraries, providing a robust environment for GPU-accelerated computations. - Regular Updates and Support: Maintained with the latest updates and security patches, offering a reliable and secure platform for machine learning projects. Primary Value and Problem Solved: This AMI addresses the challenge of setting up a deep learning environment by offering a ready-to-use, optimized platform. It eliminates the complexities associated with installing and configuring deep learning frameworks and dependencies, allowing users to focus on developing and deploying their models. By providing a stable and scalable environment, it accelerates the machine learning development lifecycle, making it an invaluable resource for both beginners and experienced practitioners in the field.

#### Who Is the Company Behind Deep Learning AMI Amazon Linux 2 with Support by Supported Images?

- **Seller:** [Supported Images](https://www.g2.com/sellers/supported-images-2a9b5d8f-6313-4986-91c0-39b460e3cf43)
- **HQ Location:** N/A
- **LinkedIn® Page:** [www.linkedin.com](https://www.g2.com/external_clickthroughs/record?secure%5Bsource_type%5D=product_profile&secure%5Btoken%5D=0aeb553e94129f3e841bdb0afd606170d988c14ba43eb7ac4a34c82590c6a97a&secure%5Burl%5D=https%3A%2F%2Fwww.linkedin.com%2Fcompany%2Fsupported-images%2F&secure%5Burl_type%5D=linkedin_company_website)  
1 employees on LinkedIn®

### [Deep Learning AMI Amazon Linux with Support by Supported Images](https://www.g2.com/products/deep-learning-ami-amazon-linux-with-support-by-supported-images/reviews)

The Deep Learning AMI Amazon Linux with Support by Supported Images is a pre-configured Amazon Machine Image designed to streamline the development and deployment of deep learning applications on AWS. This AMI comes equipped with essential deep learning frameworks, including TensorFlow, PyTorch, Apache MXNet, Chainer, and Keras, all optimized for GPU acceleration. It supports a wide range of EC2 instance types, such as P2, P3, G2, G3, G4dn, and Inf1, enabling users to select the appropriate hardware for their computational needs. Additionally, the AMI includes model debugging and hosting tools like Apache MXNet Model Server, TensorFlow Serving, and TensorBoard, facilitating efficient model development and deployment. By providing a ready-to-use environment with comprehensive support, this AMI allows developers and data scientists to focus on building and training deep learning models without the overhead of manual setup and configuration. Key Features and Functionality: - Pre-installed Deep Learning Frameworks: Includes TensorFlow, PyTorch, Apache MXNet, Chainer, and Keras, all configured for GPU acceleration. - Broad Instance Compatibility: Supports various EC2 instance types, including P2, P3, G2, G3, G4dn, and Inf1, offering flexibility in hardware selection. - Model Development Tools: Comes with Apache MXNet Model Server, TensorFlow Serving, and TensorBoard for efficient model debugging and hosting. - Optimized Performance: Configured with CUDA and cuDNN to leverage GPU capabilities for accelerated deep learning computations. - Comprehensive Support: Offers support services to assist with setup, configuration, and troubleshooting, ensuring a smooth user experience. Primary Value and Problem Solved: The Deep Learning AMI Amazon Linux with Support by Supported Images addresses the challenges of setting up and configuring deep learning environments by providing a ready-to-use, optimized platform. This allows developers and data scientists to focus on model development and training, reducing the time and effort required for environment setup. The inclusion of comprehensive support ensures that users have assistance readily available, enhancing productivity and minimizing potential roadblocks in the deep learning workflow.

#### Who Is the Company Behind Deep Learning AMI Amazon Linux with Support by Supported Images?

- **Seller:** [Supported Images](https://www.g2.com/sellers/supported-images-2a9b5d8f-6313-4986-91c0-39b460e3cf43)
- **HQ Location:** N/A
- **LinkedIn® Page:** [www.linkedin.com](https://www.g2.com/external_clickthroughs/record?secure%5Bsource_type%5D=product_profile&secure%5Btoken%5D=0aeb553e94129f3e841bdb0afd606170d988c14ba43eb7ac4a34c82590c6a97a&secure%5Burl%5D=https%3A%2F%2Fwww.linkedin.com%2Fcompany%2Fsupported-images%2F&secure%5Burl_type%5D=linkedin_company_website)  
1 employees on LinkedIn®

### [Deep Learning AMI DLAMI Ubuntu 16 with Support by Supported Images](https://www.g2.com/products/deep-learning-ami-dlami-ubuntu-16-with-support-by-supported-images/reviews)

The Deep Learning AMI (DLAMI Ubuntu 16 with Support by Supported Images is a pre-configured Amazon Machine Image designed to facilitate the development and deployment of deep learning applications on Amazon EC2 instances. This AMI comes with Ubuntu 16.04 LTS and includes a comprehensive suite of deep learning frameworks, tools, and libraries, enabling researchers and developers to efficiently build, train, and deploy sophisticated AI models in the cloud. Key Features and Functionality: - Pre-installed Deep Learning Frameworks: The AMI includes popular frameworks such as TensorFlow, PyTorch, Apache MXNet, Theano, Caffe, Caffe2, Keras, CNTK, and Torch, providing flexibility to work with various tools. - Optimized for NVIDIA GPUs: Equipped with NVIDIA CUDA drivers and libraries, the AMI is optimized for GPU acceleration, enhancing the performance of deep learning workloads. - Comprehensive Development Environment: The AMI offers a ready-to-use environment with essential tools and dependencies, reducing setup time and allowing users to focus on model development. - Support for Multiple Instance Types: Compatible with various EC2 instance types, including those with NVIDIA GPUs, the AMI allows users to select the appropriate resources based on their computational needs. Primary Value and Problem Solved: The Deep Learning AMI Ubuntu 16 with Support by Supported Images addresses the challenges associated with setting up and configuring deep learning environments. By providing a pre-configured and optimized platform, it eliminates the complexities of manual installation and compatibility issues, enabling users to quickly start developing and deploying deep learning models. This streamlined approach accelerates the development process, allowing researchers and developers to focus on innovation and experimentation without the overhead of environment setup.

#### Who Is the Company Behind Deep Learning AMI DLAMI Ubuntu 16 with Support by Supported Images?

- **Seller:** [Supported Images](https://www.g2.com/sellers/supported-images-2a9b5d8f-6313-4986-91c0-39b460e3cf43)
- **HQ Location:** N/A
- **LinkedIn® Page:** [www.linkedin.com](https://www.g2.com/external_clickthroughs/record?secure%5Bsource_type%5D=product_profile&secure%5Btoken%5D=0aeb553e94129f3e841bdb0afd606170d988c14ba43eb7ac4a34c82590c6a97a&secure%5Burl%5D=https%3A%2F%2Fwww.linkedin.com%2Fcompany%2Fsupported-images%2F&secure%5Burl_type%5D=linkedin_company_website)  
1 employees on LinkedIn®

### [Deep Learning AMI DLAMI Ubuntu 18 with Support by Supported Images](https://www.g2.com/products/deep-learning-ami-dlami-ubuntu-18-with-support-by-supported-images/reviews)

Deep Learning AMI (DLAMI) Ubuntu 18 is perfect for creating your deep learning models and then changing to the inf1 instance types such as inf1.24xlarge,inf1.2xlarge,inf1.6xlarge,inf1.xlarge providing up t0 40% lower cost per inference.

#### Who Is the Company Behind Deep Learning AMI DLAMI Ubuntu 18 with Support by Supported Images?

- **Seller:** [Supported Images](https://www.g2.com/sellers/supported-images-2a9b5d8f-6313-4986-91c0-39b460e3cf43)
- **HQ Location:** N/A
- **LinkedIn® Page:** [www.linkedin.com](https://www.g2.com/external_clickthroughs/record?secure%5Bsource_type%5D=product_profile&secure%5Btoken%5D=0aeb553e94129f3e841bdb0afd606170d988c14ba43eb7ac4a34c82590c6a97a&secure%5Burl%5D=https%3A%2F%2Fwww.linkedin.com%2Fcompany%2Fsupported-images%2F&secure%5Burl_type%5D=linkedin_company_website)  
1 employees on LinkedIn®

### [Deep Learning Base AMI Ubuntu 16.04 Version 34.0 Support by Bansir](https://www.g2.com/products/deep-learning-base-ami-ubuntu-16-04-version-34-0-support-by-bansir/reviews)

This item is a repackaged open source software, additional charges apply for support by Bansir for Deep Learning Base AMI Ubuntu 16.04 Version 34.0 AWS Deep Learning Base AMI provides a foundational platform for deep learning on AWS EC2 with NVIDIA CUDA, cuDNN, NCCL, GPU Drivers, Intel MKL-DNN, Docker, NVIDIA-Docker, EFA, and AWS Neuron support. This AMI is suitable for deploying your own custom deep learning environment at scale. For example, for machine learning developers contributing to open source deep learning framework enhancements, the AWS Deep Learning Base AMI provides a foundation for installing your custom configurations and forked repositories to test out new framework features. You could also be a Machine Learning / AI startup with a highly specialized deep learning setup that needs a foundation to run on a cloud-scale infrastructure.

#### Who Is the Company Behind Deep Learning Base AMI Ubuntu 16.04 Version 34.0 Support by Bansir?

- **Seller:** [Bansir](https://www.g2.com/sellers/bansir)
- **HQ Location:** N/A
- **LinkedIn® Page:** [www.linkedin.com](https://www.g2.com/external_clickthroughs/record?secure%5Bsource_type%5D=product_profile&secure%5Btoken%5D=7886df2ed926834e5eb248c77dcfa8e5c815d3ab1f0fe3132ced0dba45868834&secure%5Burl%5D=https%3A%2F%2Fwww.linkedin.com%2Fcompany%2FNo-Linkedin-Presence-Added-Intentionally-By-DataOps&secure%5Burl_type%5D=linkedin_company_website)  
1 employees on LinkedIn®

### [Deep Learning Base AMI (Ubuntu 18.04) Version 34.0](https://www.g2.com/products/deep-learning-base-ami-ubuntu-18-04-version-34-0/reviews)

This item is a repackaged open source software, additional charges apply for support by Bansir for Deep Learning Base AMI on Ubuntu 18.04 Version 34.0. This AMI is suitable for deploying your own custom deep learning environment at scale. For example, for machine learning developers contributing to open source deep learning framework enhancements, the AWS Deep Learning Base AMI provides a foundation for installing your custom configurations and forked repositories to test out new framework features. You could also be a Machine Learning / AI startup with a highly specialized deep learning setup that needs a foundation to run on a cloud-scale infrastructure.

#### Who Is the Company Behind Deep Learning Base AMI (Ubuntu 18.04) Version 34.0?

- **Seller:** [Bansir](https://www.g2.com/sellers/bansir)
- **HQ Location:** N/A
- **LinkedIn® Page:** [www.linkedin.com](https://www.g2.com/external_clickthroughs/record?secure%5Bsource_type%5D=product_profile&secure%5Btoken%5D=7886df2ed926834e5eb248c77dcfa8e5c815d3ab1f0fe3132ced0dba45868834&secure%5Burl%5D=https%3A%2F%2Fwww.linkedin.com%2Fcompany%2FNo-Linkedin-Presence-Added-Intentionally-By-DataOps&secure%5Burl_type%5D=linkedin_company_website)  
1 employees on LinkedIn®

### [Deeplearning Implementation](https://www.g2.com/products/deeplearning-implementation/reviews)

Delivering capabilities of data science, deep learning expertise, IT operations experts and tools to develop, deploy, monitor and manage deep learning models in production on AWS. Easily develop and deploy machine learning projects written in modern languages and frameworks, on modern production infrastructures. Monitor ML-based applications for performance issues with ML-centric capabilities. Manage the dynamic nature of machine learning applications with the ability to frequently update models, including testing and validation of new models.

#### Who Is the Company Behind Deeplearning Implementation?

- **Seller:** [Axstrm](https://www.g2.com/sellers/axstrm-42d05f1d-b1ff-4e14-b754-62b4e3a36f6e)
- **HQ Location:** San Ramon, US
- **Twitter:** @axstrm  
5 Twitter followers
- **LinkedIn® Page:** [www.linkedin.com](https://www.g2.com/external_clickthroughs/record?secure%5Bsource_type%5D=product_profile&secure%5Btoken%5D=19f49f5d5e73ab8231ba467c8939b3836e61711f15fcc7f2fcfdcd98e613f5b6&secure%5Burl%5D=https%3A%2F%2Fwww.linkedin.com%2Fcompany%2Faxstrm&secure%5Burl_type%5D=linkedin_company_website)  
1 employees on LinkedIn®

### [Deep Learning Reference Stack](https://www.g2.com/products/deep-learning-reference-stack/reviews)

The Deep Learning Reference Stack with Tensorflow is an integrated, highly-performant open source stack optimized for Intel Xeon Scalable and Client platforms. This release is part of an effort to ensure AI developers have easy access to all features and functionality of Intel platforms.

**Average Rating:** 2.5/5.0

**Total Reviews:** 2

#### How Do G2 Users Rate Deep Learning Reference Stack?

- **Has the product been a good partner in doing business?:** 5.0/10 (Category avg: 8.7/10)
- **Quality of Support:** 5.8/10 (Category avg: 8.5/10)
- **Ease of Admin:** 5.0/10 (Category avg: 8.6/10)
- **Ease of Use:** 5.0/10 (Category avg: 8.7/10)

#### Who Is the Company Behind Deep Learning Reference Stack?

- **Seller:** [Intel Corporation](https://www.g2.com/sellers/intel-corporation)
- **Year Founded:** 1968
- **HQ Location:** Santa Clara, CA
- **Twitter:** @intel  
4,467,591 Twitter followers
- **LinkedIn® Page:** [www.linkedin.com](https://www.g2.com/external_clickthroughs/record?secure%5Bsource_type%5D=product_profile&secure%5Btoken%5D=ffa114db2dc7a0181ce6c8d6339b78011d53549a79f5a963a5be775c2cfb5de7&secure%5Burl%5D=https%3A%2F%2Fwww.linkedin.com%2Fcompany%2F1053%2F&secure%5Burl_type%5D=linkedin_company_website)  
106,198 employees on LinkedIn®
- **Ownership:** NASDAQ:INTC

#### Who Uses This Product?

- **Company Size:** 100% Small

#### What Do G2 Reviewers Say About Deep Learning Reference Stack?

_AI-generated summary from verified user reviews_

##### Pros

- Users find the **ease of use** of Deep Learning Reference Stack beneficial for discovering content and software effectively.

##### Cons

- Users find the **slow performance** of Deep Learning Reference Stack frustrating, hindering their progress and understanding.
- Users find the **slow speed** of the Deep Learning Reference Stack frustrating, hindering their understanding and usage of features.

### [Deeploy Core](https://www.g2.com/products/deeploy-core/reviews)

Collabspace ARCHIVE is a data protection application that enables cross-system content access, auditing, recovery, and search. Content connectors automatically stream and index your files into a data lake in real-time to achieve comprehensive visibility, multi-level permissioned access and effective collaboration.

#### Who Is the Company Behind Deeploy Core?

- **Seller:** [Deeploy](https://www.g2.com/sellers/deeploy)
- **Year Founded:** 2020
- **HQ Location:** Utrecht, NL
- **Twitter:** @DeeployML  
15 Twitter followers
- **LinkedIn® Page:** [www.linkedin.com](https://www.g2.com/external_clickthroughs/record?secure%5Bsource_type%5D=product_profile&secure%5Btoken%5D=141193923c4e0fa4976628491549766f75569951033d2f618ba8587ddc71cd07&secure%5Burl%5D=https%3A%2F%2Fwww.linkedin.com%2Fcompany%2Fdeeploy-ml%2F&secure%5Burl_type%5D=linkedin_company_website)  
19 employees on LinkedIn®

### [DeepStream](https://www.g2.com/products/deepstream/reviews)

DeepStream SDK delivers a complete streaming analytics toolkit for AI based video and image understanding and multi-sensor processing. DeepStream SDK features hardware-accelerated building blocks, called plugins that bring deep neural networks and other complex processing tasks into a stream processing pipeline.

#### Who Is the Company Behind DeepStream?

- **Seller:** [NVIDIA](https://www.g2.com/sellers/nvidia)
- **Year Founded:** 1993
- **HQ Location:** Santa Clara, CA
- **Twitter:** @nvidia  
2,582,827 Twitter followers
- **LinkedIn® Page:** [www.linkedin.com](https://www.g2.com/external_clickthroughs/record?secure%5Bsource_type%5D=product_profile&secure%5Btoken%5D=78ee5403fa8a1bf981ce9ddbc58839ffedf0b07ab7bb703e5734e5f87464a603&secure%5Burl%5D=https%3A%2F%2Fwww.linkedin.com%2Fcompany%2F3608%2F&secure%5Burl_type%5D=linkedin_company_website)  
48,229 employees on LinkedIn®
- **Ownership:** NVDA

### [DeepStream IVA Deployment Demo](https://www.g2.com/products/deepstream-iva-deployment-demo/reviews)

This container provides a demonstration of how to deploy pre-trained models from NGC into an intelligent video analytics (IVA) pipeline in DeepStream. These models can be fine-tuned on additional data using Transfer Learning Toolkit.

#### Who Is the Company Behind DeepStream IVA Deployment Demo?

- **Seller:** [NVIDIA](https://www.g2.com/sellers/nvidia)
- **Year Founded:** 1993
- **HQ Location:** Santa Clara, CA
- **Twitter:** @nvidia  
2,582,827 Twitter followers
- **LinkedIn® Page:** [www.linkedin.com](https://www.g2.com/external_clickthroughs/record?secure%5Bsource_type%5D=product_profile&secure%5Btoken%5D=78ee5403fa8a1bf981ce9ddbc58839ffedf0b07ab7bb703e5734e5f87464a603&secure%5Burl%5D=https%3A%2F%2Fwww.linkedin.com%2Fcompany%2F3608%2F&secure%5Burl_type%5D=linkedin_company_website)  
48,229 employees on LinkedIn®
- **Ownership:** NVDA

### [Defense in Depth Server](https://www.g2.com/products/defense-in-depth-server/reviews)

The Defense in Depth Server is a comprehensive security solution designed to safeguard your IT infrastructure by implementing multiple layers of defense mechanisms. This approach ensures that if one security control fails, others remain in place to protect your systems from external and internal threats. By integrating various security measures, the Defense in Depth Server provides a robust and resilient defense strategy for your organization's critical assets. Key Features and Functionality: - Multi-Layered Security Controls: Employs a combination of physical, technical, and administrative controls to create a comprehensive security posture. - Vulnerability Management: Regularly scans and patches systems to identify and remediate vulnerabilities, reducing the risk of exploitation. - Access Control: Implements strict identity and access management policies, ensuring that only authorized personnel have access to sensitive resources. - Network Protection: Utilizes firewalls, intrusion detection and prevention systems, and network segmentation to monitor and control traffic flow, preventing unauthorized access. - Data Encryption: Ensures data is encrypted both at rest and in transit, protecting it from unauthorized access and breaches. - Automated Security Practices: Leverages automation to enforce security policies, monitor systems, and respond to incidents promptly, reducing human error and improving response times. Primary Value and Problem Solved: The Defense in Depth Server addresses the critical need for a robust and resilient security framework in today's complex threat landscape. By implementing multiple layers of defense, it mitigates the risk of security breaches, data loss, and unauthorized access. This comprehensive approach not only protects your organization's sensitive information but also ensures compliance with regulatory requirements and industry best practices. Ultimately, the Defense in Depth Server provides peace of mind, knowing that your IT infrastructure is well-protected against a wide range of potential threats.

#### Who Is the Company Behind Defense in Depth Server?

- **Seller:** [Hardened Setup](https://www.g2.com/sellers/hardened-setup)
- **HQ Location:** N/A
- **LinkedIn® Page:** [www.linkedin.com](https://www.g2.com/external_clickthroughs/record?secure%5Bsource_type%5D=product_profile&secure%5Btoken%5D=7886df2ed926834e5eb248c77dcfa8e5c815d3ab1f0fe3132ced0dba45868834&secure%5Burl%5D=https%3A%2F%2Fwww.linkedin.com%2Fcompany%2FNo-Linkedin-Presence-Added-Intentionally-By-DataOps&secure%5Burl_type%5D=linkedin_company_website)  
1 employees on LinkedIn®

### [Definiseec SSPROTECT](https://www.g2.com/products/definiseec-ssprotect/reviews)

Definiseec SSPROTECT is a comprehensive network security solution designed to safeguard organizations against a wide array of cyber threats. By leveraging advanced machine learning algorithms, it offers real-time monitoring and threat detection, ensuring the integrity and reliability of your network infrastructure. SSPROTECT's robust firewall and intrusion detection systems provide a formidable defense against unauthorized access, while its vulnerability assessment tools proactively identify and mitigate potential security risks. Detailed reporting and analytics empower organizations to analyze security incidents, recognize patterns, and strengthen their defenses effectively. Ideal for businesses of all sizes, SSPROTECT enhances network security, reduces the risks associated with cyber threats, and supports compliance with industry regulations, ultimately contributing to an organization's overall resilience. Key Features and Functionality: - Advanced Threat Detection: Utilizes machine learning algorithms to identify potential vulnerabilities and malicious activities. - Real-Time Monitoring: Provides continuous surveillance of network activities to detect anomalies promptly. - Firewall Protection: Implements robust firewall systems to prevent unauthorized access to sensitive data. - Intrusion Detection System : Monitors network traffic for suspicious behavior and responds to potential threats. - Vulnerability Assessments: Conducts regular evaluations to identify and address security weaknesses. - Detailed Reporting and Analytics: Offers comprehensive insights into security incidents to inform strategic decisions. Primary Value and Problem Solved: SSPROTECT addresses the escalating complexity and frequency of cyberattacks by providing a multifaceted security solution that ensures data integrity and network reliability. By integrating advanced threat detection, real-time monitoring, and proactive vulnerability assessments, it empowers organizations to stay ahead of potential threats. This comprehensive approach not only enhances network security but also reduces the risks associated with cyber threats and supports compliance with industry regulations, thereby bolstering an organization's overall resilience.

#### Who Is the Company Behind Definiseec SSPROTECT?

- **Seller:** [Definitive Data Security](https://www.g2.com/sellers/definitive-data-security-0fa78857-df4b-4d8e-bf65-661e79276c9d)
- **Year Founded:** 2014
- **HQ Location:** El Cerrito, US
- **LinkedIn® Page:** [www.linkedin.com](https://www.g2.com/external_clickthroughs/record?secure%5Bsource_type%5D=product_profile&secure%5Btoken%5D=4b71d630e12bf1b1317c1093a9f8ac9dade81011844ebd26e8c1749145afe413&secure%5Burl%5D=https%3A%2F%2Fwww.linkedin.com%2Fcompany%2Fdefinisec&secure%5Burl_type%5D=linkedin_company_website)  
1 employees on LinkedIn®

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[Browse AWS Marketplace Themes](/categories/aws-marketplace/themes)

 ![Neeraja Prakash](/assets/transparent-ad5be28fbcd25b7b08d2cebe1d957125437fb5407d75ee717965ad22c8808791.gif "Neeraja Prakash")
NP

Researched and written by [Neeraja Prakash](https://research.g2.com/insights/author/neeraja-prakash)

Updated June 16, 2025

The AWS Marketplace category includes a diverse range of software solutions designed to enhance and optimize operations within the Amazon Web Services (AWS) ecosystem. These products offer pre-configured Amazon Machine Images (AMIs), container solutions, and specialized services that cater to various business needs, from secure web hosting and data labeling to machine learning model deployment and transportation cost prediction. By leveraging AWS infrastructure, these solutions provide scalability, security, and seamless integration with existing AWS services, enabling businesses to efficiently deploy, manage, and scale their applications and services in the cloud.

To qualify for inclusion in the AWS Marketplace category, a product must:

- Have features and use cases that do not fit into existing marketplace apps categories
- Be designed to integrate with or enhance the functionality of AWS services, providing value through pre-configured environments, specialized tools, or managed services

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