# Best Data Fabric Software - Page 3 *By [Shalaka Joshi](https://research.g2.com/insights/author/shalaka-joshi)* Data fabric software is a unified data platform that enables organizations to integrate their data and data management processes. Adopting a data fabric allows for the creation of complete views of their data, helping power existing processes and applications and enabling the rapid development of new use cases. A data fabric is not just a single solution but an entire data ecosystem that connects disparate data sources and infrastructure types across locations (on-premises, in the cloud, or hybrid environments), enabling analysis without onerous data integration requirements. The software offers benefits such as the ability to explore and extract value from any form of data regardless of location by connecting stores of structured and unstructured data. It provides centralized access via a single, unified view of an organization's data that inherits access and governance restrictions. Companies use data fabric software to gain greater visibility into often highly complex and heterogeneous data landscapes. Data fabric software offers deeper insights and control over their data irrespective of where it sits, enabling better business decisions and strategies. Helping businesses become data-driven is key to the emergence of data fabric software and it can be adopted by any industry vertical. Fraud detection and security management, sales and marketing management, and governance and compliance management are some of the major use cases driving the growth of data fabric. To qualify for inclusion in the Data Fabric category, a product must: - Perform data management processes on a single unified platform - Pull and connect or collaborate on data from disparate sources across locations - Manage data across all environments (multi-cloud and on-premises) - Allow single, seamless access and control to data across sources and types - Provide analytics tools and connectivity to other analytical solutions - Offer metadata functionality with data currency and data lineage capabilities ## Category Overview **Total Products under this Category:** 76 ## Trust & Credibility Stats **Why You Can Trust G2's Software Rankings:** - 30 Analysts and Data Experts - 1,700+ Authentic Reviews - 76+ 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. ## Best Data Fabric Software At A Glance - **Leader:** [ServiceNow Workflow Data Fabric](https://www.g2.com/products/servicenow-workflow-data-fabric/reviews) - **Highest Performer:** [Incorta](https://www.g2.com/products/incorta/reviews) - **Easiest to Use:** [TimeXtender](https://www.g2.com/products/timextender/reviews) - **Top Trending:** [Astro by Astronomer](https://www.g2.com/products/astro-by-astronomer/reviews) - **Best Free Software:** [TimeXtender](https://www.g2.com/products/timextender/reviews) --- **Sponsored** ### Strategy Mosaic Strategy Mosaic, from Strategy (formerly MicroStrategy), is an enterprise-grade universal semantic layer solution designed to enhance the capabilities of AI and Business Intelligence (BI) within organizations. It addresses critical challenges such as data fragmentation and inconsistent metrics, which lead to untrusted AI answers, compliance risks, and runaway cloud costs. The universal semantic layer that Mosaic provides serves as a centralized repository for business definitions, hierarchies, and security rules, ensuring that all users access consistent metrics and KPIs regardless of the tools they employ. This single source of truth is actively monitored by our integrated Sentinel layer, which moves you from reactive audits to proactive, real-time governance. Sentinel provides immediate intelligence on potential data breaches, compliance risks, and cost-saving opportunities, helping you optimize cloud spend and prevent violations before they happen. Additionally, Mosaic empowers organizations to build an auditable foundation for AI. By providing a layer of rich business context and consistent, human-readable definitions, Mosaic gives AI models the deep understanding required to provide more accurate and verifiable answers. This accelerates time to insight, allows you to end vendor lock-in, and dramatically reduces the total cost of ownership (TCO) by eliminating costly data rework and optimizing data management processes. In summary, Strategy Mosaic stands out by addressing the fundamental issues of data fragmentation and governance. Its robust connectivity, centralized semantic layer, and focus on delivering trusted data make it an invaluable tool for organizations aiming to enhance their analytics capabilities and leverage AI effectively. [Visit company website](https://www.g2.com/external_clickthroughs/record?secure%5Bad_program%5D=paid_promo&secure%5Bad_slot%5D=category_product_list&secure%5Bcategory_id%5D=2394&secure%5Bmedium%5D=sponsored&secure%5Bprioritized%5D=false&secure%5Bproduct_id%5D=1559674&secure%5Bresource_id%5D=2394&secure%5Bresource_type%5D=Category&secure%5Bsource_type%5D=category_page&secure%5Bsource_url%5D=https%3A%2F%2Fwww.g2.com%2Fcategories%2Fdata-fabric%3Fpage%3D3&secure%5Btoken%5D=27f71e1e82c2e9f033d0cd480e03df30c1b0768528307c1a73d73aee708666a2&secure%5Burl%5D=https%3A%2F%2Fwww.strategysoftware.com%2Fstrategymosaic&secure%5Burl_type%5D=paid_promos) --- ## Top-Rated Products (Ranked by G2 Score) ### 1. [Talon FAST™](https://www.g2.com/products/talon-fast/reviews) Talon FAST™ software allows you to leverage the power of the cloud and simplify local branch office IT while cutting your IT and egress costs. Through local file caching you can store active data locally, eliminating the need for extensive on-premise storage systems. **Average Rating:** 4.5/5.0 **Total Reviews:** 1 **User Satisfaction Scores:** - **Governance:** 10.0/10 (Category avg: 8.9/10) - **Data Integration:** 10.0/10 (Category avg: 8.8/10) - **Ease of Use:** 10.0/10 (Category avg: 8.7/10) - **Data Protection:** 10.0/10 (Category avg: 8.9/10) **Seller Details:** - **Seller:** [Talon.One](https://www.g2.com/sellers/talon-one) - **Year Founded:** 2015 - **HQ Location:** Berlin, Germany - **Twitter:** @talonone (287 Twitter followers) - **LinkedIn® Page:** https://www.linkedin.com/company/talon.one/ (300 employees on LinkedIn®) **Reviewer Demographics:** - **Company Size:** 100% Mid-Market ### 2. [Bright Machine Data Hub](https://www.g2.com/products/bright-machine-data-hub/reviews) Bright Machines' Data Hub is a comprehensive software solution designed to enhance manufacturing operations by integrating advanced data analytics and visualization tools. It enables manufacturers to monitor, analyze, and optimize their production processes in real-time, leading to improved efficiency, quality, and equipment uptime. **Seller Details:** - **Seller:** [Bright Machines](https://www.g2.com/sellers/bright-machines) - **Year Founded:** 2018 - **HQ Location:** San Francisco, California, United States - **LinkedIn® Page:** https://www.linkedin.com/company/bright-machines/ (259 employees on LinkedIn®) ### 3. [CData Software](https://www.g2.com/products/cdata-software/reviews) CData Software offers a comprehensive suite of enterprise data connectivity solutions designed to address modern data challenges, including seamless access, replication, and movement of data across cloud and on-premises environments. Their products enable organizations to connect, integrate, and manage data from over 300 sources, facilitating real-time insights and efficient data operations. **Seller Details:** - **Seller:** [CData](https://www.g2.com/sellers/cdata-475d387c-e40d-42b5-b8dc-5c9b20b287d2) - **HQ Location:** Chapel Hill, NC - **Twitter:** @Arcesb (3 Twitter followers) - **LinkedIn® Page:** https://www.linkedin.com/company/No-Linkedin-Presence-Added-Intentionally-By-DataOps (1 employees on LinkedIn®) ### 4. [Collibra](https://www.g2.com/products/collibra/reviews) Try Collibra for free @ Collibra.com/tour Collibra is for organizations with complex data challenges, hybrid data ecosystems—and big ambitions for data and AI. We help organizations who are trying to accelerate data and AI use cases while ensuring compliance, but are struggling with fragmented governance and visibility across the whole hybrid data ecosystem. Collibra unifies governance for data and AI across every system, data source and user—to create safe autonomy and a foundation for scaling AI and data use cases. With Collibra, you can accelerate all your data and AI use cases, safely and with well–understood data. That’s Data Confidence. **Average Rating:** 4.2/5.0 **Total Reviews:** 99 **User Satisfaction Scores:** - **Ease of Use:** 8.0/10 (Category avg: 8.7/10) **Seller Details:** - **Seller:** [Collibra](https://www.g2.com/sellers/collibra) - **Company Website:** https://www.collibra.com - **Year Founded:** 2008 - **HQ Location:** New York, New York - **Twitter:** @collibra (5,735 Twitter followers) - **LinkedIn® Page:** https://www.linkedin.com/company/288365/ (1,082 employees on LinkedIn®) **Reviewer Demographics:** - **Top Industries:** Financial Services, Banking - **Company Size:** 72% Enterprise, 19% Mid-Market #### Pros & Cons **Pros:** - Features (14 reviews) - Ease of Use (13 reviews) - Data Management (12 reviews) - Data Governance (9 reviews) - Integrations (9 reviews) **Cons:** - Limited Functionality (8 reviews) - Complexity Issues (7 reviews) - Complexity (6 reviews) - Improvement Needed (6 reviews) - Complex Setup (5 reviews) ### 5. [Consulting](https://www.g2.com/products/indicium-tecnologia-de-dados-limitada-consulting/reviews) Indicium's Data Strategy Consultancy offers comprehensive services designed to transform businesses into data-driven organizations. By deeply understanding each client's unique data needs and challenges, Indicium crafts tailored strategies that enhance decision-making and operational efficiency. **Seller Details:** - **Seller:** [Indicium Tecnologia de Dados Limitada](https://www.g2.com/sellers/indicium-tecnologia-de-dados-limitada) - **Year Founded:** 2017 - **HQ Location:** Florianópolis, Santa Catarina - **LinkedIn® Page:** https://www.linkedin.com/company/indiciumtech (229 employees on LinkedIn®) ### 6. [Dataisland](https://www.g2.com/products/dataisland/reviews) Data Island is a technology solutions provider dedicated to assisting businesses in optimizing their technology investments through a comprehensive suite of services. These services encompass project management, data privacy, IT audits, IT strategy development, business continuity planning, IT recruitment, and background checks. By offering tailored solutions, Data Island enables organizations to navigate the complexities of the technological landscape effectively, ensuring their operations are secure, compliant, and aligned with business objectives. **Seller Details:** - **Seller:** [Dataisland](https://www.g2.com/sellers/dataisland) - **Year Founded:** 2023 - **HQ Location:** London, GB - **LinkedIn® Page:** https://www.linkedin.com/company/neural-innovations-ltd/ (11 employees on LinkedIn®) ### 7. [Data Lineage](https://www.g2.com/products/data-lineage/reviews) Relyance AI's Data Lineage solution offers comprehensive, real-time visibility into data flows across an organization's entire ecosystem, including applications, third-party vendors, microservices, and internal systems. By leveraging advanced machine learning and natural language processing, it automates data discovery and classification, ensuring accurate and up-to-date data inventories without manual intervention. This approach enables organizations to maintain transparency, align operational practices with contractual and regulatory obligations, and proactively address potential risks. **Seller Details:** - **Seller:** [Relyance AI](https://www.g2.com/sellers/relyance-ai) - **Year Founded:** 2020 - **HQ Location:** San Francisco, US - **LinkedIn® Page:** https://www.linkedin.com/company/relyanceai/ (149 employees on LinkedIn®) ### 8. [Data Products](https://www.g2.com/products/data-products/reviews) Indicium's Data Products are custom-designed solutions that transform raw data into actionable insights, driving business growth and innovation. Tailored to meet the unique needs of each organization, these products enhance decision-making processes, optimize operations, and provide a competitive edge in the market. **Seller Details:** - **Seller:** [Indicium Tecnologia de Dados Limitada](https://www.g2.com/sellers/indicium-tecnologia-de-dados-limitada) - **Year Founded:** 2017 - **HQ Location:** Florianópolis, Santa Catarina - **LinkedIn® Page:** https://www.linkedin.com/company/indiciumtech (229 employees on LinkedIn®) ### 9. [Datavolo](https://www.g2.com/products/datavolo/reviews) Datavolo is a comprehensive data engineering platform designed to streamline the creation, management, and observability of multimodal data pipelines for AI systems. Leveraging the robust capabilities of Apache NiFi, Datavolo offers a visual, low-code interface that enables rapid development of secure, scalable, and adaptable data workflows. With over 300 pre-built connectors and processors, along with support for custom Python and Java extensions, Datavolo empowers data engineers to efficiently handle diverse data types, including audio, video, images, and complex hierarchical structures. **Seller Details:** - **Seller:** [Datavolo](https://www.g2.com/sellers/datavolo) - **Year Founded:** 2023 - **HQ Location:** Phoenix, US - **LinkedIn® Page:** https://www.linkedin.com/company/datavolo (2 employees on LinkedIn®) ### 10. [EDIX Architecture](https://www.g2.com/products/edix-architecture/reviews) EDIX Architecture is a comprehensive framework designed to transform enterprises into cognitive organizations by integrating advanced AI and decision intelligence capabilities. It enables businesses to create a live digital twin of their operations, enhancing planning and decision-making through enriched data and actionable insights. **Seller Details:** - **Seller:** [Intelmatix](https://www.g2.com/sellers/intelmatix) - **Year Founded:** 2021 - **HQ Location:** N/A - **LinkedIn® Page:** https://www.linkedin.com/company/intelmatix (58 employees on LinkedIn®) ### 11. [Enfabrica](https://www.g2.com/products/enfabrica/reviews) Enfabrica is a technology company specializing in developing advanced hardware and software solutions to address the performance and scalability demands of artificial intelligence (AI) and high-performance computing (HPC) workloads. Their flagship product, the Accelerated Compute Fabric SuperNIC (ACF-S), is a 3.2 Tbps multi-GPU SuperNIC chip designed to enhance data movement efficiency and reduce congestion in AI clusters. **Seller Details:** - **Seller:** [Enfabrica](https://www.g2.com/sellers/enfabrica) - **Year Founded:** 2019 - **HQ Location:** Mountain View, US - **LinkedIn® Page:** https://www.linkedin.com/company/acebinfra1 (126 employees on LinkedIn®) ### 12. [eQube®-DaaS Platform](https://www.g2.com/products/eqube-daas-platform/reviews) eQube®-DaaS is a Low/No-Code Data Integration & Analytics Platform that establishes a Data Fabric connecting various sources in an organization. It enhances visibility and enables insights through two suites: Integration and Analytics. Users can handle diverse data types, formats, speeds, systems, application or device without requiring coding, ensuring secure collaboration across networks. Deployable on-premises, in multi-cloud, or hybrid setups, eQube®-DaaS consists of six components: eQube®-MI (Migration & Integration), eQube®-TM (Transformation Modeler), eQube®-AG (API Gateway), eQube®-BI (Business Intelligence), eQube®-ADA (Augmented Data Analytics), and eQube®-DP (Data Profiler), for versatile data management solutions. These components can be used individually or in combination to create a comprehensive data management solution. **Average Rating:** 5.0/5.0 **Total Reviews:** 1 **User Satisfaction Scores:** - **Ease of Use:** 10.0/10 (Category avg: 8.7/10) **Seller Details:** - **Seller:** [eQ Technologic](https://www.g2.com/sellers/eq-technologic) - **Year Founded:** 2000 - **HQ Location:** Costa Mesa, US - **Twitter:** @1eQTechnologic (57 Twitter followers) - **LinkedIn® Page:** https://www.linkedin.com/company/eq-technologic (916 employees on LinkedIn®) **Reviewer Demographics:** - **Company Size:** 100% Small-Business #### Pros & Cons **Pros:** - Automation (1 reviews) - Ease of Use (1 reviews) - Easy Integrations (1 reviews) - Easy Setup (1 reviews) - Functionality (1 reviews) **Cons:** - Expensive (1 reviews) ### 13. [Foundational](https://www.g2.com/products/foundational/reviews) Foundational is a data governance platform that analyzes source code, pipelines, configurations, and BI metadata to provide end to end visibility, preventative controls, and real time understanding of how data flows across an enterprise environment. The platform is designed for data engineering teams, analytics engineers, data platform teams, and data governance leaders who work across complex, multi technology ecosystems that include both SQL and non SQL systems. The platform introduces an approach to governance that operates at the level of code rather than relying on manual processes or downstream detection. By parsing source code and metadata across warehouses, orchestration tools, transformation frameworks, and BI systems, Foundational produces complete lineage, build time impact analysis, and automated data contracts that help teams understand dependencies, assess change risk, and maintain a consistent standard for quality and reliability. This foundation supports AI governance by providing visibility into the inputs that feed machine learning features, models, and AI products so that teams can evaluate data quality, lineage, and policy adherence before training or deployment. Foundational helps users support several core data governance and data quality use cases. These include identifying the upstream source of a metric, predicting the effect of a schema or pipeline update, enforcing rules for critical datasets, and understanding how changes in one part of the stack may affect downstream analytics, feature pipelines, or AI systems. The platform supports organizations that need reliable data for reporting and machine learning, as well as teams that want to minimize data incidents and improve development speed across the data lifecycle. Key product capabilities include: • Automated end to end lineage across SQL and non SQL systems that updates when code changes • Build time impact analysis that evaluates downstream effects before code is merged • Automated data contracts that define and enforce expectations for structure, freshness, and behavior • Governance automation that centralizes change tracking, policy checks, and review workflows • Quality monitoring that prioritizes issues based on business impact by using lineage context • AI governance support that traces model inputs back to source systems, evaluates data quality for training data, and maintains visibility into the dependencies that influence AI output reliability Organizations adopt Foundational to replace manual tracing, fragmented governance tools, and reactive quality checks with a single system that provides comprehensive visibility and proactive controls. The result is a consistent understanding of how data is created, transformed, and consumed, supporting more reliable analytics, faster engineering work, and stronger readiness for AI initiatives. **Seller Details:** - **Seller:** [Foundational](https://www.g2.com/sellers/foundational) - **HQ Location:** San Francisco, US - **LinkedIn® Page:** https://www.linkedin.com/company/foundational-data (23 employees on LinkedIn®) ### 14. [General Dynamics Mediaware](https://www.g2.com/products/general-dynamics-mediaware/reviews) We develop mission critical products and solutions for the Australian Defence Force. **Average Rating:** 4.5/5.0 **Total Reviews:** 1 **User Satisfaction Scores:** - **Ease of Use:** 8.3/10 (Category avg: 8.7/10) **Seller Details:** - **Seller:** [Mediaware International](https://www.g2.com/sellers/mediaware-international) - **Year Founded:** 1952 - **HQ Location:** Chantilly, US - **LinkedIn® Page:** https://www.linkedin.com/company/gdms (9,119 employees on LinkedIn®) **Reviewer Demographics:** - **Company Size:** 100% Small-Business ### 15. [Global IDs Data Governance Platform](https://www.g2.com/products/global-ids-data-governance-platform/reviews) Global IDs is an innovative software company delivering purpose-built solutions for data-centric organizations. Global IDs is committed to helping organizations of any size solve business problems with core metadata management techniques in an automated and scalable approach. Our integrated platform delivers key capabilities that enable transparency, trust and traceability of your data assets. A highly automated approach to implementing a Data Governance methodology that drives cost optimization and revenue growth by uncovering hidden insights and opportunities. **Average Rating:** 4.2/5.0 **Total Reviews:** 3 **User Satisfaction Scores:** - **Ease of Use:** 6.7/10 (Category avg: 8.7/10) **Seller Details:** - **Seller:** [Global IDs](https://www.g2.com/sellers/global-ids) - **Year Founded:** 2001 - **HQ Location:** Princeton, US - **Twitter:** @GlobalIDs (3,968 Twitter followers) - **LinkedIn® Page:** https://www.linkedin.com/company/global-ids (90 employees on LinkedIn®) **Reviewer Demographics:** - **Company Size:** 33% Enterprise, 33% Mid-Market ### 16. [Infinidat Elastic Data Fabric](https://www.g2.com/products/infinidat-elastic-data-fabric/reviews) Infinidat Elastic Data Fabric is our vision for the evolution of enterprise storage from traditional hardware appliances into elastic data center-scale pools of high-performance, highly reliable, low-cost digital storage with seamless data mobility within the data center and the public cloud. **Seller Details:** - **Seller:** [Infinidat](https://www.g2.com/sellers/infinidat) - **Year Founded:** 2011 - **HQ Location:** Waltham, US - **Twitter:** @INFINIDAT (2,302 Twitter followers) - **LinkedIn® Page:** https://www.linkedin.com/company/infinidat (512 employees on LinkedIn®) **Reviewer Demographics:** - **Company Size:** 100% Mid-Market ### 17. [NetApp AI Data Engine](https://www.g2.com/products/netapp-ai-data-engine/reviews) NetApp AI Data Engine (AIDE) is a storage-integrated AI data service that offers a secure, end-to-end solution for managing your NetApp data estate across the entire AI lifecycle - from preparing raw data to serving it to GenAI apps. It provides a global, structured view, automates data synchronization and change detection, and embeds governance and security throughout the AI lifecycle. By combining vectorization for GenAI with advanced compression and secure workflows, AIDE enhances data efficiency and clarity while reducing complexity and costs. AIDE is ideal for enterprises looking to streamline AI initiatives, reduce storage costs, improve AI data governance and security, and enhance the efficiency and reliability of AI-driven decisions. NetApp AIDE streamlines and secures AI initiatives by providing unified management, reducing tool complexity, and lowering costs with efficient data transformation using NVIDIA NIMs and NetApp compression. It offers a global structured view for rapid AI discovery and readiness, ensuring quick data access and real-time sync for accurate, timely AI-driven decisions. AIDE also embeds robust governance and security with policy-driven controls, automated classification, and NetApp snapshot technology, ensuring compliance, data protection, and responsible AI usage. **Seller Details:** - **Seller:** [NetApp](https://www.g2.com/sellers/netapp) - **Year Founded:** 1992 - **HQ Location:** Sunnyvale, California - **Twitter:** @NetApp (118,257 Twitter followers) - **LinkedIn® Page:** https://www.linkedin.com/company/2105/ (12,677 employees on LinkedIn®) - **Ownership:** NASDAQ ### 18. [Predactiv Data Platform](https://www.g2.com/products/predactiv-data-platform/reviews) Predactiv Data Platform is a product that is transforming how data can be leveraged, delivering actionable insights and scalable solutions that drive impact, optimize strategy, and fuel growth. **Seller Details:** - **Seller:** [Predactiv](https://www.g2.com/sellers/predactiv) - **Year Founded:** 2024 - **HQ Location:** Palo Alto, US - **LinkedIn® Page:** https://www.linkedin.com/company/predactiv/ (65 employees on LinkedIn®) ### 19. [SKAIDOCK - Space qualified Data processing Unit](https://www.g2.com/products/skaidock-space-qualified-data-processing-unit/reviews) SKAIDOCK is a space-qualified data processing unit designed as a carrier board for Xiphos Q8(S) modules, which are equipped with Xilinx Zynq UltraScale+ Multi-Processor System-on-Chip (MPSoC). It features a PC104 form factor, making it compatible with CubeSat systems, and offers configurable interfaces accessible through side connectors. The board is engineered to seamlessly integrate into satellite systems and is compatible with Simera Sense CubeSat imagers. **Seller Details:** - **Seller:** [Zaitra](https://www.g2.com/sellers/zaitra) - **Year Founded:** 2020 - **HQ Location:** Brno, CZ - **LinkedIn® Page:** https://www.linkedin.com/company/zaitra (21 employees on LinkedIn®) ### 20. [StirlingX](https://www.g2.com/products/stirlingx/reviews) StirlingX is a technology company that provides AI-driven data intelligence and autonomous drone solutions. **Seller Details:** - **Seller:** [StirlingX](https://www.g2.com/sellers/stirlingx) - **Year Founded:** 2024 - **HQ Location:** London, GB - **LinkedIn® Page:** https://www.linkedin.com/company/stirlingx/?originalSubdomain=uk (24 employees on LinkedIn®) ### 21. [Strategy Mosaic](https://www.g2.com/products/strategy-mosaic/reviews) Strategy Mosaic, from Strategy (formerly MicroStrategy), is an enterprise-grade universal semantic layer solution designed to enhance the capabilities of AI and Business Intelligence (BI) within organizations. It addresses critical challenges such as data fragmentation and inconsistent metrics, which lead to untrusted AI answers, compliance risks, and runaway cloud costs. The universal semantic layer that Mosaic provides serves as a centralized repository for business definitions, hierarchies, and security rules, ensuring that all users access consistent metrics and KPIs regardless of the tools they employ. This single source of truth is actively monitored by our integrated Sentinel layer, which moves you from reactive audits to proactive, real-time governance. Sentinel provides immediate intelligence on potential data breaches, compliance risks, and cost-saving opportunities, helping you optimize cloud spend and prevent violations before they happen. Additionally, Mosaic empowers organizations to build an auditable foundation for AI. By providing a layer of rich business context and consistent, human-readable definitions, Mosaic gives AI models the deep understanding required to provide more accurate and verifiable answers. This accelerates time to insight, allows you to end vendor lock-in, and dramatically reduces the total cost of ownership (TCO) by eliminating costly data rework and optimizing data management processes. In summary, Strategy Mosaic stands out by addressing the fundamental issues of data fragmentation and governance. Its robust connectivity, centralized semantic layer, and focus on delivering trusted data make it an invaluable tool for organizations aiming to enhance their analytics capabilities and leverage AI effectively. **Average Rating:** 4.5/5.0 **Total Reviews:** 15 **User Satisfaction Scores:** - **Ease of Use:** 8.6/10 (Category avg: 8.7/10) **Seller Details:** - **Seller:** [Strategy (formerly MicroStrategy)](https://www.g2.com/sellers/strategy-formerly-microstrategy) - **Company Website:** https://www.strategy.com/software - **Year Founded:** 1989 - **HQ Location:** Tysons Corner, VA - **Twitter:** @MicroStrategy (302,648 Twitter followers) - **LinkedIn® Page:** https://www.linkedin.com/company/strategy/ (3,404 employees on LinkedIn®) **Reviewer Demographics:** - **Company Size:** 53% Enterprise, 40% Mid-Market #### Pros & Cons **Pros:** - Ease of Use (2 reviews) - Features (2 reviews) - Reporting (2 reviews) - Data Analysis (1 reviews) - Data Modeling (1 reviews) **Cons:** - Bugs (2 reviews) - Bug Issues (1 reviews) - Debugging Issues (1 reviews) - Expensive (1 reviews) - Learning Curve (1 reviews) ### 22. [Syniti Knowledge Platform](https://www.g2.com/products/syniti-syniti-knowledge-platform/reviews) A comprehensive enterprise data management solution designed to handle various data initiatives, the Syniti Knowledge Platform (SKP) integrates capabilities for data migration, quality, governance, and master data management into one unified platform. SKP aims to deliver trustworthy, optimized, and actionable data across businesses, ensuring successful digital transformations with minimal disruption. Able to support the most complex migrations, such as transitioning to SAP S/4HANA, SKP’s unified data management capabilities drive better business outcomes. SKP is an essential tool for enterprises looking to manage their data effectively and leverage it for strategic advantage. Its comprehensive features and benefits make it a valuable asset for any business aiming to improve data quality, governance, and overall management. SKP helps businesses achieve successful digital transformations with minimal disruption. **Average Rating:** 4.2/5.0 **Total Reviews:** 14 **User Satisfaction Scores:** - **Ease of Use:** 8.3/10 (Category avg: 8.7/10) **Seller Details:** - **Seller:** [Syniti](https://www.g2.com/sellers/syniti) - **Year Founded:** 1996 - **HQ Location:** Needham, MA - **LinkedIn® Page:** https://www.linkedin.com/company/backoffice-associates (370 employees on LinkedIn®) **Reviewer Demographics:** - **Company Size:** 71% Enterprise, 43% Mid-Market ### 23. [The Cognite AI & Data Platform](https://www.g2.com/products/the-cognite-ai-data-platform/reviews) The Cognite AI and Data Platform™ is a sophisticated Industrial DataOps solution specifically designed for asset-intensive industries seeking to harness the power of their operational and engineering data. Founded in 2016 and based in Tempe, Arizona, Cognite aims to facilitate the transformation of complex data environments into actionable insights that drive efficiency and innovation across various sectors. This cloud-native platform excels in ingesting and contextualizing data from a multitude of sources, including Information Technology (IT), Operational Technology (OT), and engineering systems. By creating a unified industrial knowledge graph, the Cognite AI and Data Platform integrates data from historians, Enterprise Resource Planning (ERP) systems, Computerized Maintenance Management Systems (CMMS), and even 3D models. This comprehensive approach allows organizations to standardize their data models and utilize robust APIs, enabling secure workspaces that support advanced analytics, interactive dashboards, and AI-driven applications. Targeted primarily at industries that rely heavily on operational data, such as manufacturing, energy, and utilities, the Cognite AI and Data Platform addresses specific use cases that enhance productivity and operational efficiency. For instance, organizations can leverage the platform for production optimization, where real-time data insights lead to improved throughput and reduced operational bottlenecks. Additionally, the platform supports predictive maintenance initiatives, allowing companies to anticipate equipment failures before they occur, thereby minimizing downtime and associated costs. Key features of the Cognite AI and Data Platform include its ability to transform fragmented data into a trusted and contextual foundation, which is crucial for making informed decisions. By providing a centralized repository of data, users gain full ownership and control over their information, facilitating compliance and security. Moreover, the platform’s scalability enables organizations to implement AI initiatives that can evolve with their operational needs, ensuring that they remain competitive in a rapidly changing industrial landscape. Overall, the Cognite AI and Data Platform stands out in the DataOps category by offering a comprehensive solution that not only integrates disparate data sources but also empowers organizations to unlock the full potential of their industrial data. Through its focus on contextualization and user-friendly interfaces, it provides significant value to companies looking to enhance their operational capabilities and drive long-term growth. **Seller Details:** - **Seller:** [Cognite](https://www.g2.com/sellers/cognite) - **Company Website:** https://www.cognite.com/en/ - **Year Founded:** 2016 - **HQ Location:** Tempe, Arizona, United States - **LinkedIn® Page:** https://www.linkedin.com/company/cognitedata (760 employees on LinkedIn®) ### 24. [WEKA](https://www.g2.com/products/wekaio-weka/reviews) We help enterprises, neoclouds, and exascale AI innovators accelerate real-world performance, deploy anywhere without compromise, and grow stronger with scale. NeuralMesh™ by WEKA® is the world’s only storage system purpose-built for AI—built on a high-performance, containerized microservices architecture that eliminates bottlenecks, maximizes infrastructure efficiency, and enables teams to build boldly into the future. **Average Rating:** 4.5/5.0 **Total Reviews:** 2 **User Satisfaction Scores:** - **Ease of Use:** 10.0/10 (Category avg: 8.7/10) **Seller Details:** - **Seller:** [WekaIO](https://www.g2.com/sellers/wekaio) - **Year Founded:** 2013 - **HQ Location:** Campbell, California, United States - **LinkedIn® Page:** https://www.linkedin.com/company/weka-io (499 employees on LinkedIn®) **Reviewer Demographics:** - **Company Size:** 100% Small-Business #### Pros & Cons **Pros:** - AI Integration (1 reviews) - Performance (1 reviews) - Workflow Efficiency (1 reviews) ### 25. [XponentL Data](https://www.g2.com/products/xponentl-data/reviews) XponentL Data specializes in transforming complex data environments into strategic assets, delivering market-leading solutions designed to maximize return on investment. By bridging the gap between data producers and consumers, XponentL enables organizations to reduce the time from question to answer, fostering a network of data products that fuel insights and artificial intelligence, thereby capturing significant value. **Seller Details:** - **Seller:** [XponentL Data](https://www.g2.com/sellers/xponentl-data) - **Year Founded:** 2023 - **HQ Location:** Philadelphia, US - **LinkedIn® Page:** https://www.linkedin.com/company/xponentl (232 employees on LinkedIn®) ## Parent Category [IT Infrastructure Software](https://www.g2.com/categories/it-infrastructure) ## Related Categories - [Big Data Integration Platforms](https://www.g2.com/categories/big-data-integration-platforms) - [Machine Learning Data Catalog Software](https://www.g2.com/categories/machine-learning-data-catalog) - [Data Governance Tools](https://www.g2.com/categories/data-governance-tools) --- ## Buyer Guide ### What You Should Know About Data Fabric Software ### What is Data Fabric Software? Data fabric software is an architecture that connects sources, types, and the location of data and provides end-to-end data integration. It is a unified environment for data services and technologies, helping with data management. Using this platform, organizations can collect enterprise data from disparate sources and provide it to various teams within the company without external help. The data is pulled by APIs from data warehouses, data lakes, databases, and apps. Data fabric software can be enhanced by incorporating artificial intelligence (AI) or machine learning (ML). AI-powered versions of these tools provide personalized recommendations to select datasets which can boost the speed of data science projects.  Data assets are usually generated in silos, while data preparation cycles in the data pipeline are long and take up a lot of time, affecting an organization’s data optimization. Data fabric systems help standardize data management practices across cloud, on-premises, and edge services. These tools usually include various data management technologies like [data catalog](https://www.g2.com/categories/machine-learning-data-catalog), [governance](https://www.g2.com/categories/data-governance), virtualization, integration, pipeline, and orchestration. Data fabric software helps users access data using unique workflows while also democratizing data, allowing data citizens to access information across the organization. Using this tool gives companies a holistic view of the business process. ### What are the Common Features of Data Fabric Software? The following are some core features of data fabric software that can help users in various ways: **Unified data environment:** Data fabric software creates an architecture that integrates various data management processes like data collaboration, data discovery, data analytics, data visualization, data access, and data control on a single platform. This eliminates the need for multiple data integration products. **Data collaboration and sharing:** Data fabric software allows data connectivity into a single unified view, helping data to be accessed by or shared with internal and external applications. **Governance and compliance:** Data owners remain in full control of who can visit, edit, download, or query their datasets. Data fabric software enables compliance, preserves integrity, and controls access. These tools also incorporate data quality in each step of data management. **Environment agnostic:** Data fabric software allows data management across multiple environments such as on-premises, in the cloud, hybrid, and multi cloud. **Metadata management:** Data fabric has data lineage capabilities and currency of data, which means it contains data migration and transformation history. The currency of data defines the state of the data—active or archived. **Data analytics and visualization:** These tools use continuous analytics over the existing metadata assets for better business insights. ### What are the Benefits of Data Fabric Software? While there are many data management technologies like master data management, data hubs, and data lakes, data fabric differs from them in various ways.  **Enhanced data management:** Data fabric software helps retrieve, validate, and enrich data automatically. It helps in enterprise data integration and management. It also helps to provide a single unified view of the data, which allows end users to identify and track data easily and use it efficiently. Automation and integration help in dynamic data orchestration across a distributed ecosystem. **Easy to use:** Technical and non-technical users can use data fabric platforms. The architecture makes it possible to create various user interfaces. Business users can create sleek dashboards and use it for various other functions, while data scientists can also use it for deep data exploration. **Compatible with hybrid hosting environments:** Data fabrics are environment agnostic. It can help in bi-directional integration with almost all the components to create a fabric-like structure and eliminate the need for coding. Data fabric software supports on-premises, hybrid cloud, and multi-cloud environments. **High scalability:** Data fabric systems can manage data at an enterprise scale. It helps to ingest data automatically, which would typically remain unutilized. They are scalable with minimum interference and no investment requirement into expensive hardware or trained staff. The data architecture helps reduce big data complexity and ultimately drives strategic business outcomes. **Fast insights:** Automation of data engineering tasks and integration augmentation helps deliver real-time insights faster. Also, continuous data analytics used by data fabric also helps provide value through rapid access. Data fabric software combines data warehouses and data lakes and integrated data from multiple apps, providing services that help organizations monitor and control their data. **Seamless integration:** Data fabric software solves the common challenge of big data in organizations. This tool removes data silos through a holistic approach and helps in the seamless integration of data across various functions. Many workloads are moving to the cloud, and it requires data. Data fabric software streamlines this movement from the cloud to the data center or between hybrid clouds.  ### Who Uses Data Fabric Software? Data fabric platforms have various stakeholders within an organization.  **Data scientists:** Data scientists use data fabric software to explore deep and hidden enterprise data to share with other departments for actionable insights. **Business users:** The organization's business users, like marketers, can use these tools to make critical business decisions. Smart data fabric solutions are the emerging data architecture helping organizations fast-track their enterprise data initiatives.  #### Software Related to Data Fabric Software Following are some tools that can be used with data fabric software: [Machine learning data catalog software](https://www.g2.com/categories/machine-learning-data-catalog) **:** Machine learning data catalogs allow organizations to categorize, access, interpret, and collaborate data across multiple data sources and maintain a high level of governance and access management. Data fabric helps identify, collect, and analyze data sources and metadata.  [Data quality software](https://www.g2.com/categories/data-quality) **:** Data quality software uses a set of technologies to identify, understand, prevent, and correct issues with the data used for decision making. Data quality tools carry out critical functions like data profiling, parsing, standardization, cleansing, built-in workflow, and knowledge bases.  [Data governance software](https://www.g2.com/categories/data-governance) **:** Data governance software is used to enforce data-related policies. These products help establish guidelines, processes, and accountability measures to ensure data quality standards are met. Data governance tools enable organizations to develop a framework to know what data they own and how to use it optimally.  [Data preparation software](https://www.g2.com/categories/data-preparation) **:** Data preparation and delivery are important steps in data transformation and integration during the data pipeline lifecycle. Data preparation begins with loading data into a data platform from a data lake. Then data processing begins using extract, transform, load or extract, load, transform (ETL or ELT) tools. The result is prepared data. ### Challenges with Data Fabric Software Although data fabric systems aim at data management, there are some challenges when implementing its services. Below are a few challenges faced by organizations commonly: **Deployment and configuration of services:** Services may have to be deployed on multiple servers to optimize performance. This may require configuring services in specific ways for them to work together.  **Creating a data model and managing data:** A data model determines how data will be structured and organized. Thus it becomes necessary to build a data model that fulfills the organization's needs and can be managed easily. Data fabric unifies data across various data types and points using a semantic knowledge graph. One of the challenges is managing and saving data. Data is available in different formats; hence, the software must be able to handle and manage all kinds of data. Building an architecture that supports different environments is a challenge. **Integration with external systems:** Data fabric makes it possible to integrate with multiple systems. For integration with external systems, middleware software is usually created to mediate between these external systems and data fabric tools, managing their communication. The challenge here is that two communicating systems may have different architectures; thus, it is challenging to produce a single middleware. **Data security:** Data protection is paramount to any organization. One of the challenges, when data is being transferred from one point to another using data fabric tools, is that the data is vulnerable to attacks. However, this can be avoided by introducing firewalls to ensure safety. It is also essential to go beyond data masking and encryption to ensure total data protection. ### How to Buy Data Fabric Software? #### Requirements Gathering (RFI/RFP) for Data Fabric Software Data fabric software solves several data management concerns or challenges in an organization. Before purchasing data fabric software, it is important to understand the existing requirements of the organization. If an organization needs only deduplication and data validation, a data quality tool may help. Many organizations also choose data processing solutions such as ETL tools to process and integrate their data. Depending on where in the organization there is a need for data management, data fabric solutions can be chosen. #### Compare Data Fabric Software Products **Create a long list** A list of data fabric software vendors can help understand their offerings. The team in the organization can then evaluate the vendors that would fulfill the organization’s needs.  **Create a short list** After evaluating various data fabric solutions, the organization's decision makers can shortlist a few depending on which vendors fit the bill. **Conduct demos** After shortlisting vendors, companies should look for a demo. The demo gives a better understanding of the technical functionality of the software. Nowadays, data fabric tools come with artificial intelligence features. AI-based recommendations help faster data recovery. These could be some important features that the teams need to know. IT professionals, data scientists, as well as data management and business teams can attend the demo to evaluate the product from various perspectives.  #### Selection of Data Fabric Software **Choose a selection team** A selection team is a mix of technical users and business users like data scientists, data management teams, and marketing teams. Along with that, the team should have a key decision maker. **Negotiation** Once a vendor is selected for their software, it is advisable to understand their pricing and negotiate if necessary. The negotiation part entirely depends on the organization’s budget and the difference between the product pricing and the budget.  **Final decision** After both parties arrive at a mutually agreeable term, it is time to decide whether to buy the software.