FPT Cloud vs. Oracle Cloud Infrastructure Compute Comparison Chart

Compute Engine is Google's infrastructure as a service (IaaS) platform for organizations to create and run cloud-based virtual machines. Computing infrastructure in predefined or custom machine sizes to accelerate your cloud transformation. General purpose (E2, N1, N2, N2D) machines provide a good balance of price and performance. Compute optimized (C2) machines offer high-end vCPU performance for compute-intensive workloads. Memory optimized (M2) machines offer the highest memory and are great for in-memory databases. Accelerator optimized (A2) machines are based on the A100 GPU, for very demanding applications. Integrate Compute with other Google Cloud services such as AI/ML and data analytics. Make reservations to help ensure your applications have the capacity they need as they scale. Save money just for running Compute with sustained-use discounts, and achieve greater savings when you use committed-use discounts.

RunPod offers a cloud-based platform designed for running AI workloads, focusing on providing scalable, on-demand GPU resources to accelerate machine learning (ML) model training and inference. With its diverse selection of powerful GPUs like the NVIDIA A100, RTX 3090, and H100, RunPod supports a wide range of AI applications, from deep learning to data processing. The platform is designed to minimize startup time, providing near-instant access to GPU pods, and ensures scalability with autoscaling capabilities for real-time AI model deployment. RunPod also offers serverless functionality, job queuing, and real-time analytics, making it an ideal solution for businesses needing flexible, cost-effective GPU resources without the hassle of managing infrastructure.

With our comprehensive suite of scalable cloud services, you can build your cloud server, your way. Kamatera’s infrastructure specializes in VPS hosting, with a choice of 24 data centers worldwide, including 8 data centers across the US as well as locations in Europe, Asia, and the Middle East. Our enterprise-grade cloud servers can meet your needs at every stage. We use cutting-edge hardware, such as Ice Lake Processors and NVMe SSD, to deliver consistent speed and 99.95% uptime. With a robust service like ours, you can expect plenty of great features, such as fantastic hardware, flexible and scalable cloud setup, fully managed hosting, windows server hosting, data security and safety, consultation, server migration, and disaster recovery. Our technical staff is always on duty, with 24/7 live support to assist you across all time zones. And our flexible, predictable pricing plans means you’ll only pay for what you use with our hourly or monthly billing options.

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. Vertex AI Agent Builder enables developers to create and deploy enterprise-grade generative AI applications. It offers both no-code and code-first approaches, allowing users to build AI agents using natural language instructions or by leveraging frameworks like LangChain and LlamaIndex.

Dataiku is an enterprise AI platform designed to help organizations move from fragmented AI efforts to fully scalable and governed AI success. It brings together people, data, and technology into a single system that enables collaboration between domain experts and technical teams. The platform allows users to build, deploy, and manage AI models, analytics workflows, and AI agents with greater efficiency. Dataiku emphasizes orchestration by connecting data sources, applications, and machine learning processes into unified pipelines. It also provides strong governance capabilities, helping organizations monitor performance, control costs, and reduce risks across AI initiatives. Businesses across industries use Dataiku to modernize analytics, automate workflows, and scale machine learning across teams. With proven results from global enterprises, the platform supports faster innovation and measurable ROI through AI-driven solutions.

QuantaStor is a unified Software-Defined Storage platform designed to scale up and out to make storage management easy while reducing overall enterprise storage costs. With support for all major file, block, and object protocols including iSCSI/FC, NFS/SMB, and S3, QuantaStor storage grids may be configured to address the needs of complex workflows which span sites and datacenters. QuantaStor’s storage grid technology is a built-in federated management system which enables QuantaStor servers to be combined together to simplify management and automation via CLI and REST APIs. The layered architecture of QuantaStor provides solution engineers with unprecedented flexibility and application design options that maximizes workload performance and fault-tolerance for a wide range of storage workloads. QuantaStor includes end-to-end security coverage enabling multi-layer data protection “on the wire” and “at rest” for enterprise and cloud storage deployments.

Ango Hub is a quality-focused, enterprise-ready data annotation platform for AI teams, available on cloud and on-premise. It supports computer vision, medical imaging, NLP, audio, video, and 3D point cloud annotation, powering use cases from autonomous driving and robotics to healthcare AI. Built for AI fine-tuning, RLHF, LLM evaluation, and human-in-the-loop workflows, Ango Hub boosts throughput with automation, model-assisted pre-labeling, and customizable QA while maintaining accuracy. Features include centralized instructions, review pipelines, issue tracking, and consensus across up to 30 annotators. With nearly twenty labeling tools—such as rotated bounding boxes, label relations, nested conditional questions, and table-based labeling—it supports both simple and complex projects. It also enables annotation pipelines for chain-of-thought reasoning and next-gen LLM training and enterprise-grade security with HIPAA compliance, SOC 2 certification, and role-based access controls.

A sample tracking, test result capture, and inventory management cloud LIMS for life science research, biotech/NGS, and industrial QC labs. Includes regulatory support for CLIA, HIPAA, Part 11, and ISO 17025. Nothing is more critical to a lab’s success than the quality, security, and traceability of samples. The Lockbox LIMS system provides robust sample management functionality to laboratory professionals, giving them full visibility on every aspect of a sample’s journey, from accessioning to long-term storage. LIMS analysis is about more than just tracking results- Lockbox’s multi-layered sample storage and location management functionality allows you to define your lab’s storage framework using a variety of location options: rooms, storage units, shelves, racks, boxes, and positions.

RaimaDB is an embedded time series database for IoT and Edge devices that can run in-memory. It is an extremely powerful, lightweight and secure RDBMS. Field tested by over 20 000 developers worldwide and has more than 25 000 000 deployments. RaimaDB is a high-performance, cross-platform embedded database designed for mission-critical applications, particularly in the Internet of Things (IoT) and edge computing markets. It offers a small footprint, making it suitable for resource-constrained environments, and supports both in-memory and persistent storage configurations. RaimaDB provides developers with multiple data modeling options, including traditional relational models and direct relationships through network model sets. It ensures data integrity with ACID-compliant transactions and supports various indexing methods such as B+Tree, Hash Table, R-Tree, and AVL-Tree.

DbVisualizer is a universal database client for developers, DBAs, analysts, and data engineers working with relational and NoSQL databases. It provides a graphical interface for database development, SQL querying, data exploration, and database admin. The tool includes a powerful SQL editor with intelligent autocomplete, visual query builders, variables, and query execution tools. Customize window layouts, key bindings, and UI themes, mark scripts or database objects as favorites, and configure security settings to meet organizational requirements. Ask questions, explain errors, and analyze code with the built-in AI Assistant. Use the built-in Git integration to manage your SQL scripts and collaboration. DbVisualizer connects to many popular databases through JDBC drivers, including MySQL, PostgreSQL, SQL Server, Oracle, Snowflake, SQLite, Cassandra, and BigQuery. It runs on Windows, macOS, and Linux. Nearly 7 million downloads and Pro users in 150 countries.