HPE Ezmeral Data Fabric vs. MongoDB Atlas Comparison


HPE Ezmeral Data Fabric Hewlett Packard Enterprise	MongoDB Atlas MongoDB	+	+
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The platform includes capabilities such as zero-copy data access, unified semantics, centralized compliance, natural language search, data marketplaces, and optimized query performance. 387 Ratings Visit Website Teradata VantageCloud Teradata VantageCloud: The complete cloud analytics and data platform for AI. Teradata VantageCloud is an enterprise-grade, cloud-native data and analytics platform that unifies data management, advanced analytics, and AI/ML capabilities in a single environment. Designed for scalability and flexibility, VantageCloud supports multi-cloud and hybrid deployments, enabling organizations to manage structured and semi-structured data across AWS, Azure, Google Cloud, and on-premises systems. It offers full ANSI SQL support, integrates with open-source tools like Python and R, and provides built-in governance for secure, trusted AI. VantageCloud empowers users to run complex queries, build data pipelines, and operationalize machine learning models—all while maintaining interoperability with modern data ecosystems. 1,121 Ratings Visit Website Google Cloud Platform Google Cloud is a cloud-based service that allows you to create anything from simple websites to complex applications for businesses of all sizes. New customers get $300 in free credits to run, test, and deploy workloads. All customers can use 25+ products for free, up to monthly usage limits. Use Google's core infrastructure, data analytics & machine learning. Secure and fully featured for all enterprises. Tap into big data to find answers faster and build better products. Grow from prototype to production to planet-scale, without having to think about capacity, reliability or performance. From virtual machines with proven price/performance advantages to a fully managed app development platform. Scalable, resilient, high performance object storage and databases for your applications. State-of-the-art software-defined networking products on Google’s private fiber network. Fully managed data warehousing, batch and stream processing, data exploration, Hadoop/Spark, and messaging. 61,049 Ratings Visit Website DataBuck DataBuck is an AI-powered data validation platform that automates risk detection across dynamic, high-volume, and evolving data environments. DataBuck empowers your teams to: ✅ Enhance trust in analytics and reports, ensuring they are built on accurate and reliable data. ✅ Reduce maintenance costs by minimizing manual intervention. ✅ Scale operations 10x faster compared to traditional tools, enabling seamless adaptability in ever-changing data ecosystems. By proactively addressing system risks and improving data accuracy, DataBuck ensures your decision-making is driven by dependable insights. Proudly recognized in Gartner’s 2024 Market Guide for #DataObservability, DataBuck goes beyond traditional observability practices with its AI/ML innovations to deliver autonomous Data Trustability—empowering you to lead with confidence in today’s data-driven world. 6 Ratings Visit Website Google Cloud BigQuery 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. Gemini in BigQuery offers AI-driven tools for assistance and collaboration, such as code suggestions, visual data preparation, and smart recommendations designed to boost efficiency and reduce costs. BigQuery delivers an integrated platform featuring SQL, a notebook, and a natural language-based canvas interface, catering to data professionals with varying coding expertise. This unified workspace streamlines the entire analytics process. 2,027 Ratings Visit Website SCIKIQ SCIKIQ is an AI-native Data & Intelligence Platform designed to help enterprises make their data trusted, governed, connected, and ready for AI in weeks rather than years. Recognized by Forrester, NASSCOM League of 10, YourStory Tech30, Inc42, and DataIQ, SCIKIQ supports enterprises across the USA, India, UK, and UAE. SCIKIQ brings together Data Integration, Data Quality, Data Governance, Metadata Management, Data Lineage, Semantic Intelligence, Knowledge Graphs, Conversational Analytics, Generative AI, Data Products, and AI Agents within one unified platform. Unlike traditional data platforms that often require extensive replatforming or migration, SCIKIQ works with an enterprise’s existing technology ecosystem. Organizations can connect SAP, Salesforce, Oracle, Snowflake, Databricks, AWS, Azure, GCP, data lakes, data warehouses, and enterprise applications through 200+ pre-built connectors, without rip-and-replace. Contextual Intelligence at the Core SCIKIQ goes beyond connecting data by helping AI understand the business context behind it. Its semantic intelligence layer brings together business terminology, KPI definitions, metadata, lineage, ownership, business rules, ontologies, and relationships to create a trusted context layer for enterprise analytics and AI. Business users can ask questions in natural language, investigate KPIs, identify root causes, and generate insights without writing SQL. Data teams gain enterprise-grade capabilities for data integration, quality, governance, lineage, metadata, and control. AI teams gain trusted, contextual enterprise data for building Generative AI applications, copilots, and intelligent AI agents. Why Enterprises Choose SCIKIQ AI-ready in 3–6 weeks \| 200+ connectors \| 99.9% availability \| No-code \| Multi-cloud \| No vendor lock-in \| No replatforming SCIKIQ has production deployments across industries including manufacturing, retail, aviation, logistics, BFSI, healthcare, and other data-intensive enterprises. 14 Ratings Visit Website TIMi The most efficient, sovereign & unified "on-premise" data platform available today. Think about the Azure data platform, but on steroids and 100% Sovereign. TIMi is an ethical solution: Zero Lock-In: We gain your trust through exceptional performance and service, not artificial vendor lock-in Fair price & No hidden fees & No price hikes TIMi is a leader in these fields: Data Preparation/ETL/BPA/BPM/ESB - automate the most complex tasks without code - Connect to everything: Sharepoint, SAP, Salesforce, Facebook, GAds, etc. BigData - 1 TIMi-server is faster than 267 Spark-servers - Process any volumetry at negligible infrastructure cost. Process billions of rows in a matter of seconds on a standard 2K€ server. - manage peta-byte Data Lakes AI/ML: We invented the 1st Auto-ML tool in 2007 TIMi is a horizontal solution used in any industry: Manufacturing, Telecoms, Banks, Supermarket chains, Defense, Gov. Also available in EU-hosted sovereign cloud. 68 Ratings Visit Website Stonebranch Universal Automation Center (UAC) is a real-time IT automation platform designed to centrally manage and orchestrate tasks and processes across hybrid IT environments - from on-prem to the cloud. Universal Automation Center (UAC) is a software platform designed to automate and orchestrate your IT and business processes, securely manage file transfers, and centralize the management of disparate IT job scheduling and workload automation solutions. With our event-driven automation technology, it is now possible to achieve real-time automation across your entire hybrid IT environment. Real-time hybrid IT automation and managed file transfers (MFT) for any type of cloud, mainframe, distributed or hybrid environment. Start automating, managing and orchestrating file transfers from mainframe or disparate systems to the AWS or Azure cloud and vice versa with no ramp-up time or cost-intensive hardware investments. 183 Ratings Visit Website AnalyticsCreator AnalyticsCreator is a metadata-driven design application for data warehouse automation and data product engineering across the Microsoft data stack. At its core is the AnalyticsCreator Governed Control Model, which keeps business meaning, data structures, transformation rules, dependencies and technical implementation connected in one controlled project model. Data teams design the required architecture in AnalyticsCreator, then generate native Microsoft assets from that design. Generated assets can include SQL Server objects, SSIS packages, Azure Data Factory pipelines, Microsoft Fabric components, deployment artefacts and Power BI semantic models. 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Typical use cases include enterprise data warehouse development, Microsoft Fabric adoption, SQL Server and SSIS modernisation, governed Power BI delivery, SAP-to-Microsoft analytics architectures and repeatable data product engineering. 46 Ratings Visit Website RaimaDB 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. 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About Access HPE Ezmeral Data Fabric Software as a fully managed service. Register now for a 300GB instance to try out the latest features and capabilities. Increasingly enterprise data is being distributed across a growing number of locations while at the same time, the demand for insights continues to grow as users expect richer, high-quality data insights. Hybrid cloud solutions offer the best outcomes in terms of cost, data placement, workload control, and user experience. The upside of hybrid is the ability to better match applications with the appropriate services across the application lifecycle. The downside of hybrid is that it adds a new dimension of complexity such as limited data visibility, the need to use multiple analytic formats, and the potential for organizational risk and increased costs.	About The most innovative cloud database service on the market, with unmatched data distribution and mobility across AWS, Azure, and Google Cloud, built-in automation for resource and workload optimization, and so much more. MongoDB Atlas is the global cloud database service for modern applications. Deploy fully managed MongoDB across AWS, Google Cloud, and Azure with best-in-class automation and proven practices that guarantee availability, scalability, and compliance with the most demanding data security and privacy standards. The best way to deploy, run, and scale MongoDB in the cloud. MongoDB Atlas offers built-in security controls for all your data. Enable enterprise-grade features to integrate with your existing security protocols and compliance standards. With MongoDB Atlas, your data is protected with preconfigured security features for authentication, authorization, encryption, and more.
Platforms Supported Windows Not Supported Mac Not Supported Linux Not Supported Cloud Supported On-Premises Not Supported iPhone Not Supported iPad Not Supported Android Not Supported Chromebook Not Supported	Platforms Supported Windows Not Supported Mac Not Supported Linux Not Supported Cloud Supported On-Premises Not Supported iPhone Not Supported iPad Not Supported Android Not Supported Chromebook Not Supported
Audience Companies in need of a fully managed service to achieve data visibility, availability, and federation in a hybrid, multi-cloud world	Audience Developers, data engineers, and organizations looking for a fully managed, cloud-based database solution to build scalable, secure, and high-performance applications
Support Phone Support Supported 24/7 Live Support Not Supported Online Supported	Support Phone Support Supported 24/7 Live Support Supported Online Supported
API Offers API Not Supported	API Offers API Supported
Screenshots and Videos View more images or videos	Screenshots and Videos View more images or videos
Pricing No information available. Free Version Not Supported Free Trial Not Supported	Pricing $0.08/hour Free Version Supported Free Trial Not Supported
Reviews/Ratings Overall 0.0 / 5 ease 0.0 / 5 features 0.0 / 5 design 0.0 / 5 support 0.0 / 5 This software hasn't been reviewed yet. Be the first to provide a review: Review this Software	Reviews/Ratings Overall 5.0 / 5 ease 5.0 / 5 features 5.0 / 5 design 5.0 / 5 support 5.0 / 5 Read all reviews
	Pros & Cons from Real Users Pros MongoDB Atlas significantly reduces operational overhead by handling provisioning, scaling, backups, and maintenance automatically. From a DevOps standpoint, this means less time managing infrastructure and more time focusing on reliability, pipelines, and delivery. The ability to deploy clusters in minutes across AWS, Azure, or GCP makes it highly flexible for multi cloud strategies and rapid environment setup Cons Despite being managed, it is not fully hands off. Production setups still require careful configuration of cluster sizing, networking, and security policies, especially for high traffic workloads. Misconfiguration can still lead to performance or cost issues
Training Documentation Supported Webinars Supported Live Online Not Supported In Person Not Supported	Training Documentation Supported Webinars Supported Live Online Not Supported In Person Not Supported
Company Information Hewlett Packard Enterprise Founded: 2009 United States www.mapr.com	Company Information MongoDB Founded: 2007 United States www.mongodb.com/atlas
Alternatives Talend Data Fabric Qlik	Alternatives Couchbase
Paxata	RaimaDB Raima
Ataccama ONE Ataccama	ScaleGrid
EC2 Spot Amazon	MongoDB
Vertica Rocket Software View All	Azure Cosmos DB Microsoft View All
Categories Big Data Supported	Categories AI Memory Layers Supported Big Data Supported Data Intelligence Supported Data Management Supported Database Supported Database as a Service (DBaaS) Supported Database Backup Supported Database Performance Tuning Supported Distributed Databases Supported Document Databases Supported Event Stream Processing Supported NoSQL Database Supported Unstructured Data Analysis Supported Vector Databases Supported

Integrations IRI Voracity Supported AWS CloudFormation Not Supported Ant Media Server Not Supported Apono Not Supported ClicData Not Supported CloudAvocado Not Supported Collate Not Supported Data V Not Supported DocumentDB for VS Code Not Supported GlobalSUITE Not Supported Hevo Not Supported HiveMQ Not Supported LLMWare.ai Not Supported Mimasa AI Not Supported Procyon Not Supported QuerySurge Not Supported Refold Not Supported Resmo Not Supported Secuvy AI Not Supported Stacksync Not Supported Show More Integrations View All 15 Integrations	Integrations IRI Voracity Supported AWS CloudFormation Supported Ant Media Server Supported Apono Supported ClicData Supported CloudAvocado Supported Collate Supported Data V Supported DocumentDB for VS Code Supported GlobalSUITE Supported Hevo Supported HiveMQ Supported LLMWare.ai Supported Mimasa AI Supported Procyon Supported QuerySurge Supported Refold Supported Resmo Supported Secuvy AI Supported Stacksync Supported Show More Integrations View All 69 Integrations
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