Pathway vs. WarpStream Comparison Chart

Cloud-based observability solution that helps businesses track and manage workload and performance on a unified dashboard. Monitor everything you run in your cloud without compromising on cost, granularity, or scale. groundcover is a full stack cloud-native APM platform designed to make observability effortless so that you can focus on building world-class products. By leveraging our proprietary sensor, groundcover unlocks unprecedented granularity on all your applications, eliminating the need for costly code changes and development cycles to ensure monitoring continuity. 100% visibility, all the time. Cover your entire Kubernetes stack instantly, with no code changes using the superpowers of eBPF instrumentation. Take control of your data, all in-cloud. groundcover’s unique inCloud architecture keeps your data private, secured and under your control without ever leaving your cloud premises.

The training data platform for AI teams. A machine learning model is only as good as its training data. Labelbox is an end-to-end platform to create and manage high-quality training data all in one place, while supporting your production pipeline with powerful APIs. Powerful image labeling tool for image classification, object detection and segmentation. When every pixel matters, you need accurate and intuitive image segmentation tools. Customize the tools to support your specific use case, including instances, custom attributes and much more. Performant video labeling editor for cutting-edge computer vision. Label directly on the video up to 30 FPS with frame level. Additionally, Labelbox provides per frame label feature analytics enabling you to create better models faster. Creating training data for natural language intelligence has never been easier. Label text strings, conversations, paragraphs, and documents with fast & customizable classification.

(Bank CFO) “I don’t have confidence and trust in our data. We keep discovering hidden risks”. Since 70% of data initiatives fail due to unreliable data (Gartner research), are you risking your reputation by trusting the accuracy of your data that you share with your business stakeholders and partners? Data Trust Scores must be measured in Data Lakes, warehouses, and throughout the pipeline, to ensure the data is trustworthy and fit for use. It typically takes 4-6 weeks of manual effort just to set a file or table for validation. Then, the rules have to be constantly updated as the data evolves. The only scalable option is to automate data validation rules discovery and rules maintenance. DataBuck is an autonomous, self-learning, Data Observability, Quality, Trustability and Data Matching tool. It reduces effort by 90% and errors by 70%. "What took my team of 10 Engineers 2 years to do, DataBuck could complete it in less than 8 hours." (VP, Enterprise Data Office, a US bank)

Derive insights from your images in the cloud or at the edge with AutoML Vision or use pre-trained Vision API models to detect emotion, understand text, and more. Google Cloud offers two computer vision products that use machine learning to help you understand your images with industry-leading prediction accuracy. Automate the training of your own custom machine learning models. Simply upload images and train custom image models with AutoML Vision’s easy-to-use graphical interface; optimize your models for accuracy, latency, and size; and export them to your application in the cloud, or to an array of devices at the edge. Google Cloud’s Vision API offers powerful pre-trained machine learning models through REST and RPC APIs. Assign labels to images and quickly classify them into millions of predefined categories. Detect objects and faces, read printed and handwritten text, and build valuable metadata into your image catalog.

The Industry Standard Universal Binary Repository Manager. Supports all major package types (over 27 and growing) such as Maven, npm, Python, NuGet, Gradle, Go, and Helm including Kubernetes and Docker as well as integration with leading CI servers and DevOps tools that you already use. Additional functionalities include: - High Availability that scales to infinity with active/active clustering of your DevOps environment and scales as business grows - On-Prem, Cloud, Hybrid, or Multi-Cloud Solution - De Facto Kubernetes Registry managing application packages, operating system’s component dependencies, open source libraries, Docker containers, and Helm charts with full visibility of all dependencies. Compatible with a growing list of Kubernetes cluster providers.

Qloo is the “Cultural AI”, decoding and predicting consumer taste across the globe. A privacy-first API that predicts global consumer preferences and catalogs hundreds of millions of cultural entities. Through our API, we provide contextualized personalization and insights based on a deep understanding of consumer behavior and more than 575 million people, places, and things. Our technology empowers you to look beyond trends and uncover the connections behind people’s tastes in the world around them. Look up entities in our vast library spanning categories like brands, music, film, fashion, travel destinations, and notable people. Results are delivered within milliseconds and can be weighted by factors such as regionalization and real-time popularity. Used by companies who want to incorporate best-in-class data in their consumer experiences. Our flagship recommendation API delivers results based on demographics, preferences, cultural entities, metadata, and geolocational factors.

Dialogflow from Google Cloud is a natural language understanding platform that makes it easy to design and integrate a conversational user interface into your mobile app, web application, device, bot, interactive voice response system, and so on. Using Dialogflow, you can provide new and engaging ways for users to interact with your product. Dialogflow can analyze multiple types of input from your customers, including text or audio inputs (like from a phone or voice recording). It can also respond to your customers in a couple of ways, either through text or with synthetic speech. Dialogflow CX and ES provide virtual agent services for chatbots and contact centers. If you have a contact center that employs human agents, you can use Agent Assist to help your human agents. Agent Assist provides real-time suggestions for human agents while they are in conversations with end-user customers.

Build, deploy, and scale machine learning (ML) models faster, with fully managed ML tools for any use case. Through Vertex AI Workbench, Vertex AI is natively integrated with BigQuery, Dataproc, and Spark. You can use BigQuery ML to create and execute machine learning models in BigQuery using standard SQL queries on existing business intelligence tools and spreadsheets, or you can export datasets from BigQuery directly into Vertex AI Workbench and run your models from there. Use Vertex Data Labeling to generate highly accurate labels for your data collection.

Google Cloud’s Speech API processes more than 1 billion voice minutes per month with close to human levels of understanding for many commonly spoken languages. Powered by the best of Google's AI research and technology, Google Cloud's Speech-to-Text API helps you accurately transcribe speech into text in 73 languages and 137 different local variants. Leverage Google’s most advanced deep learning neural network algorithms for automatic speech recognition (ASR) and deploy ASR wherever you need it, whether in the cloud with the API, on-premises with Speech-to-Text On-Prem, or locally on any device with Speech On-Device.

BigQuery is a serverless, multicloud data warehouse that simplifies the process of working with all types of data so you can focus on getting valuable business insights quickly. At the core of Google’s data cloud, BigQuery allows you to simplify data integration, cost effectively and securely scale analytics, share rich data experiences with built-in business intelligence, and train and deploy ML models with a simple SQL interface, helping to make your organization’s operations more data-driven.