Find and compare the best Artificial Intelligence software for Amazon Kinesis in 2025
Sort:
Use the comparison tool below to compare the top Artificial Intelligence software for Amazon Kinesis on the market. You can filter results by user reviews, pricing, features, platform, region, support options, integrations, and more.
Need help deciding?
Talk to one of our software experts for free. They will help you select the best software for your business.
-
1
Edge Delta
Edge Delta
$0.20 per GBEdge Delta is a new way to do observability. We are the only provider that processes your data as it's created and gives DevOps, platform engineers and SRE teams the freedom to route it anywhere. As a result, customers can make observability costs predictable, surface the most useful insights, and shape your data however they need. Our primary differentiator is our distributed architecture. We are the only observability provider that pushes data processing upstream to the infrastructure level, enabling users to process their logs and metrics as soon as they’re created at the source. Data processing includes: * Shaping, enriching, and filtering data * Creating log analytics * Distilling metrics libraries into the most useful data * Detecting anomalies and triggering alerts We combine our distributed approach with a column-oriented backend to help users store and analyze massive data volumes without impacting performance or cost. By using Edge Delta, customers can reduce observability costs without sacrificing visibility. Additionally, they can surface insights and trigger alerts before data leaves their environment. -
2
5X
5X
$350 per month5X is a data platform that offers everything you need to centralize your data, clean it, model it, and analyze it. 5X is designed to simplify data management. It offers seamless integration with more than 500 data sources. This ensures uninterrupted data movement between all your systems using pre-built connectors and custom connectors. The platform includes ingestion, warehousing and modeling, orchestration and business intelligence. All of this is presented in a simple-to-use interface. 5X supports a variety of data movements including SaaS applications, databases, ERPs and files. Data is transferred automatically and securely to data lakes and warehouses. 5X's enterprise-grade security encrypts the data at its source, identifying personally identifiable data and encrypting it at a column-level. The platform is designed for a 30% reduction in total cost of ownership compared to building a platform yourself. It also enhances productivity by providing a single interface for building end-to-end pipelines. -
3
Privacera
Privacera
Multi-cloud data security with a single pane of glass Industry's first SaaS access governance solution. Cloud is fragmented and data is scattered across different systems. Sensitive data is difficult to access and control due to limited visibility. Complex data onboarding hinders data scientist productivity. Data governance across services can be manual and fragmented. It can be time-consuming to securely move data to the cloud. Maximize visibility and assess the risk of sensitive data distributed across multiple cloud service providers. One system that enables you to manage multiple cloud services' data policies in a single place. Support RTBF, GDPR and other compliance requests across multiple cloud service providers. Securely move data to the cloud and enable Apache Ranger compliance policies. It is easier and quicker to transform sensitive data across multiple cloud databases and analytical platforms using one integrated system. -
4
Secuvy AI
Secuvy
Secuvy, a next-generation cloud platform, automates data security, privacy compliance, and governance via AI-driven workflows. Unstructured data is treated with the best data intelligence. Secuvy, a next-generation cloud platform that automates data security, privacy compliance, and governance via AI-driven workflows is called Secuvy. Unstructured data is treated with the best data intelligence. Automated data discovery, customizable subjects access requests, user validations and data maps & workflows to comply with privacy regulations such as the ccpa or gdpr. Data intelligence is used to locate sensitive and private information in multiple data stores, both in motion and at rest. Our mission is to assist organizations in protecting their brand, automating processes, and improving customer trust in a world that is rapidly changing. We want to reduce human effort, costs and errors in handling sensitive data. -
5
StreamFlux
Fractal
Data is essential when it comes to constructing, streamlining and growing your company. Unfortunately, it can be difficult to get the most out of data. Many organizations face incompatibilities, slow results, poor access to data and spiraling costs. Leaders who can transform raw data into real results are the ones who will succeed in today's competitive landscape. This is possible by empowering everyone in your company to be able analyze, build, and collaborate on machine learning and AI solutions. Streamflux is a one stop shop for all your data analytics and AI needs. Our self-service platform gives you the freedom to create end-to-end data solutions. It uses models to answer complex questions, and evaluates user behavior. You can transform raw data into real business impact in days instead of months, whether you are generating recommendations or predicting customer turnover and future revenue. -
6
Amazon SageMaker Feature Store can be used to store, share and manage features for machine-learning (ML) models. Features are inputs to machine learning models that are used for training and inference. In an example, features might include song ratings, listening time, and listener demographics. Multiple teams may use the same features repeatedly, so it is important to ensure that the feature quality is high-quality. It can be difficult to keep the feature stores synchronized when features are used to train models offline in batches. SageMaker Feature Store is a secure and unified place for feature use throughout the ML lifecycle. To encourage feature reuse across ML applications, you can store, share, and manage ML-model features for training and inference. Any data source, streaming or batch, can be used to import features, such as application logs and service logs, clickstreams and sensors, etc.
-
7
Ikigai
Ikigai
Simulations based on historical data can be used to improve models and update them incrementally. Data governance, access control, and versioning allow for easy collaboration. Ikigai has a wide range of integrations that make it easy to integrate with tools already in your workflow. Ikigai has 200+ connectors that allow you to connect to almost any data source. Want to push your ML to a dashboard or website? Integrate directly using Ikigai’s web integrations. Triggers can be used to run data synchronizations, and retrieve updates every time you run an automation flow. You can integrate Ikigai seamlessly by using your own APIs or creating APIs for your data stack. -
8
Validio
Validio
Get a clear view of your data assets: popularity, usage, and schema coverage. Get important insights into your data assets, such as popularity and utilization. Find and filter data based on tags and descriptions in metadata. Get valuable insights about your data assets, such as popularity, usage, quality, and schema cover. Drive data governance and ownership throughout your organization. Stream-lake-warehouse lineage to facilitate data ownership and collaboration. Lineage maps are automatically generated at the field level to help understand the entire data ecosystem. Anomaly detection is based on your data and seasonality patterns. It uses automatic backfilling from historical data. Machine learning thresholds are trained for each data segment and not just metadata. -
9
Shaped
Shaped
The fastest way to relevant search and recommendations. Increase engagement, conversion and revenue using a configurable, real-time system. We help your users find the content or products that are most relevant for them by surfacing those products. We do this while taking into consideration your business objectives in order to ensure that all sides of your marketplace or platform are being optimized fairly. Shaped is an automated, real-time recommendation system that consists of four stages. It contains all the data, machine-learning, and infrastructure required to understand and serve your discovery needs at scale. Connect and deploy quickly with direct integration into your existing data sources. Ingest and rerank in real-time based on behavioral signals. Optimize LLMs and neural rankings models to achieve the best performance. Build and experiment with retrieval and ranking components for any use cases.
- Previous
- You're on page 1
- Next
