# Best Data Management Software *By [Shalaka Joshi](https://research.g2.com/insights/author/shalaka-joshi)* Data management software moves, manages, and provides access to data across diverse public clouds and on-premises and hybrid environments. Data management as a practice involves using multiple data tools that provide an efficient way to manage an organization’s data. Typically, companies use this software to connect, access, and transform data and applications across various sources within an organization while maintaining the quality and security of the data. Businesses also leverage additional tools like data cataloging and master data management (MDM), enabling them to categorize, classify, and centralize their master data. IT administrators, development, and data teams mainly use data management software. Organizations typically use this software to integrate, access, and modify data and applications from a range of internal sources, while ensuring data quality and security. Companies may also employ supplementary tools such as data cataloging and master data management (MDM) to categorize, classify, and consolidate their master data. To qualify for inclusion in the Data Management category, a product must: - Provide a 360° view of data about key business entities, like customer, supplier, partner, etc., from multiple internal and external data source systems - Support cloud API and application integration - Provide pre-built connectors supporting any data type or pattern - Allow users to streamline, govern, and manage integrations through a dashboard - Provide wizards for data replication and data synchronization - Discover data quality issues and ensure quality and governance by profiling, cleansing, and monitoring the datasets - Support de-duplication using rules to eliminate incorrect data from entering the system - Automate and accelerate integration and data management with artificial intelligence (AI) and machine learning (ML) recommendations - Identify sensitive data quickly and protect it to comply with regulations and data security policies - Offer collaboration features around data sets, including categorizing, commenting, and sharing - Give intelligent recommendations based on ML for quicker access to relevant data ## How Many Data Management Software Products Does G2 Track? **Total Products under this Category:** 29 ### Category Stats (May 2026) - **Average Rating**: 4.64/5 (↓0.01 vs Apr 2026) - **New Reviews This Quarter**: 35 - **Buyer Segments**: Small-Business 39% │ Enterprise 33% │ Mid-Market 28% - **Top Trending Product**: Rayven (+0.039) *Last updated: May 18, 2026* ## How Does G2 Rank Data Management Software Products? **Why You Can Trust G2's Software Rankings:** - 30 Analysts and Data Experts - 300+ Authentic Reviews - 29+ 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. ## Which Data Management Software Is Best for Your Use Case? - **Easiest to Use:** [Salesforce Data 360 (formerly Data Cloud)](https://www.g2.com/products/salesforce-data-360-formerly-data-cloud/reviews) - **Best Free Software:** [Syncari](https://www.g2.com/products/syncari/reviews) ## What Are the Top-Rated Data Management Software Products in 2026? ### 1. [Salesforce Data 360 (formerly Data Cloud)](https://www.g2.com/products/salesforce-data-360-formerly-data-cloud/reviews) Salesforce Data Cloud unlocks the full value of your enterprise data by powering Customer 360 apps, Agentforce, and enhancing your existing data lake and warehouse investments with real-time insights and intelligent action. Natively built on the Salesforce Platform, Data Cloud is designed to complement—not replace—your current systems. It acts as a smart data bridge, unifying structured and unstructured data from lakes, warehouses, and business applications using low-code tools. With Zero Copy architecture and deep partnerships with Amazon, Snowflake, Databricks, and Google, you can maximize existing data investments and activate data seamlessly across the Salesforce ecosystem. **Average Rating:** 4.3/5.0 **Total Reviews:** 240 **Who Is the Company Behind Salesforce Data 360 (formerly Data Cloud)?** - **Seller:** [Salesforce](https://www.g2.com/sellers/salesforce) - **Company Website:** https://www.salesforce.com/ - **Year Founded:** 1999 - **HQ Location:** San Francisco, CA - **Twitter:** @salesforce (581,299 Twitter followers) - **LinkedIn® Page:** https://www.linkedin.com/company/3185/ (88,363 employees on LinkedIn®) **Who Uses This Product?** - **Who Uses This:** Salesforce Developer - **Top Industries:** Information Technology and Services, Computer Software - **Company Size:** 41% Mid-Market, 35% Enterprise #### What Are Salesforce Data 360 (formerly Data Cloud)'s Pros and Cons? **Pros:** - Platform Integration (79 reviews) - Ease of Use (56 reviews) - Easy Integration (53 reviews) - Data Discovery (39 reviews) - Integrations (38 reviews) **Cons:** - Learning Curve (53 reviews) - Expensive (44 reviews) - Difficult Learning (37 reviews) - Complexity (36 reviews) - Complex Setup (34 reviews) ### 2. [Syncari](https://www.g2.com/products/syncari/reviews) Syncari is an AI-ready, Agentic MDM platform that unifies, governs, and activates trusted data across all your systems, domains, and cloud infrastructure. Built for enterprises navigating the complexity of multi-agent environments and AI-driven operations, Syncari automates core data management workflows—from data modeling and lineage to validation and remediation—without needing heavy IT resources. At the heart of Syncari is its patented multi-directional sync, delivering real-time, bi-directional data consistency across CRMs, ERPs, cloud platforms, and data warehouses—without custom code or middleware. Syncari ensures continuously clean, synchronized, and governed data flows throughout your enterprise and is always ready for analytics, AI models, and operational use. Whether you're powering AI copilots, managing complex entity relationships, or standardizing data pipelines, Syncari helps you move beyond just managing data—to activating it. Why Syncari? -Syncari Agentic MDM™: Designed for orchestrating trusted data across AI agents and teams -Patented Multi-Directional Sync: Real-time updates across all connected platforms -Agentic Ops: Schema sync, field mapping, DQ enforcement, and remediation -Entity Resolution: Consolidate and deduplicate records across domains -Composable + Cloud-First: Built to plug into your existing SaaS and data stack -Low-Code / No-Code: Accessible to IT, data teams, RevOps, and business users alike Core Capabilities Unify, Sync, Automate, Activate, Model, Catalog, Lineage, Transform, Standardize, Verify, Remediate, Observe, Report, Consume Top Use Cases - Customer Master: Build a unified customer profile across GTM systems - Product Master: Align and enrich product data across eCommerce and ERP - Hierarchy Master: Govern legal entities, accounts, and territories - Analytics MDM: Push AI-ready data into BI tools and ML workflows - Data Products: Operationalize governed datasets for internal and external use - Data Quality: Automatically identify, validate, standardize, and remediate data issues across systems - MDM for Snowflake: Sync and manage master data directly inside Snowflake - MDM for GCP: Connect, unify, and activate trusted data in BigQuery and GCP tools - MDM for Your Data Warehouse: Maintain clean, governed, query-ready data across your cloud warehouse infrastructure -MCP Server for your unified data **Average Rating:** 4.8/5.0 **Total Reviews:** 41 **Who Is the Company Behind Syncari?** - **Seller:** [Syncari](https://www.g2.com/sellers/syncari) - **Year Founded:** 2019 - **HQ Location:** Newark, California - **Twitter:** @syncari (236 Twitter followers) - **LinkedIn® Page:** https://www.linkedin.com/company/syncari/ (49 employees on LinkedIn®) **Who Uses This Product?** - **Top Industries:** Computer Software, Information Technology and Services - **Company Size:** 51% Mid-Market, 44% Small-Business ### 3. [Scikiq: Comprehensive Data Management Platform](https://www.g2.com/products/scikiq-comprehensive-data-management-platform/reviews) SCIKIQ help make AI possible for enterprises. SCIKIQ brings together everything an enterprise needs to scale AI, clean data, trusted governance, semantic context, real-time orchestration, and intelligent agents, all in one platform. SCIKIQ brings Data Hub, a Unified Data Layer, a foundational architecture that creates a single version of truth across all data sources, departments, and use cases within the enterprise. SCIKIQ Data Hub brings Data integration, Processing and Curation, Data Governance and Data Visualisation all in one platform. It also brings Gen AI studio, Agentic AI and Auto ML studio for your AI Initiatives. Our Conversation (Self Service) Analytics, prompt to process (data analytics, Dashboards, Agents, insights & products) AI Co-pilot is among the best in the world Recognized by Forrester as top 34 AI enabled platform in the world, By NASSCOM in top 10 in Deep Tech club and By YourStory and Inc Media in Top 30 companies to watch. Selected by AWS to showcase at MWC and AWS re:Invent **Average Rating:** 4.6/5.0 **Total Reviews:** 11 **Who Is the Company Behind Scikiq: Comprehensive Data Management Platform?** - **Seller:** [SCIKIQ](https://www.g2.com/sellers/scikiq) - **Year Founded:** 2023 - **HQ Location:** Gurgaon - **Twitter:** @scikiq (9 Twitter followers) - **LinkedIn® Page:** https://www.linkedin.com/company/SCIKIQ (29 employees on LinkedIn®) **Who Uses This Product?** - **Company Size:** 36% Small-Business, 36% Enterprise #### What Are Scikiq: Comprehensive Data Management Platform's Pros and Cons? **Pros:** - Ease of Use (4 reviews) - Data Management (3 reviews) - Functionality (3 reviews) - Data Integration (2 reviews) - Easy Setup (2 reviews) **Cons:** - Complexity Issues (2 reviews) - Complexity (1 reviews) - Data Management (1 reviews) - Expensive (1 reviews) - Integration Issues (1 reviews) ### 4. [DataBahn](https://www.g2.com/products/databahn/reviews) DataBahn.ai is redefining how enterprises manage the explosion of security and operational data in the AI era. Our AI-powered data pipeline and fabric platform helps organizations securely collect, enrich, orchestrate, and optimize enterprise data—including security, application, observability, and IoT/OT telemetry—for analytics, automation, and AI. With native support for over 500 integrations and built-in enrichment capabilities, DataBahn streamlines fragmented data workflows and reduces SIEM and infrastructure costs from day one. The platform requires no specialist training, enabling security and IT teams to extract insights in real time and adapt quickly to new demands. We've helped Fortune 500 and Global 2000 companies reduce data processing costs by over 50% and automate more than 80% of their data engineering workloads. Our founding team brings decades of experience in cybersecurity and infrastructure, having previously managed environments ingesting more than 12 petabytes of data per day. That deep domain expertise informs our bold, opinionated approach to solving one of the biggest pain points in enterprise infrastructure: how to unify and act on fragmented, fast-growing data streams. Purpose-built for scale, speed, and simplicity, DataBahn replaces patchwork stacks with a single intuitive solution that accelerates time to value and turns security data from a cost center into a strategic asset. **Average Rating:** 4.8/5.0 **Total Reviews:** 4 **Who Is the Company Behind DataBahn?** - **Seller:** [DataBahn](https://www.g2.com/sellers/databahn-2b28b768-4c25-4022-98bb-222bee851d98) - **HQ Location:** Dallas, US - **LinkedIn® Page:** https://www.linkedin.com/company/databahn-ai/ (51 employees on LinkedIn®) **Who Uses This Product?** - **Company Size:** 50% Enterprise, 25% Mid-Market #### What Are DataBahn's Pros and Cons? **Pros:** - Integrations (1 reviews) - Scalability (1 reviews) - Streamlining Processes (1 reviews) **Cons:** - Complex Setup (1 reviews) - Difficult Learning (1 reviews) ### 5. [Exportly](https://www.g2.com/products/exportly/reviews) Exportly.ai is a sales automation platform that connects prospecting with downstream sales tools to help revenue teams streamline outbound workflows and manage account data at scale. It is designed for sales development representatives (SDRs), account executives, and revenue operations leaders at mid-sized and enterprise B2B companies that manage high volumes of outbound prospecting. Exportly reduces manual effort and ensures consistent, accurate data across teams and systems. In larger sales organizations, outbound teams face complexity when exporting leads, enriching data, and ensuring records remain consistent across multiple tools. Exportly.ai addresses this by automating the capture, validation, and syncing of account and contact information. This allows SDRs and AEs to focus on outreach, while RevOps teams maintain confidence that data quality and workflows remain reliable at scale. The platform is particularly useful in scenarios where organizations need to: - Build structured outbound lists - Enrich and validate records with additional firmographic and demographic data. - Standardize formatting and remove duplicates before syncing to CRMs or outreach platforms. - Provide SDR teams with clean, ready-to-use lists for outbound sequences. - Improve operational efficiency and data governance across larger teams. Key features include: - Capture leads directly from websites without manual exporting. - Clay Enrichment: Append accurate and detailed contact information. - CRM Syncing: Push structured data into CRMs and outbound platforms to maintain consistency. - Outbound Readiness: Deliver SDRs prospect lists optimized for cadences and workflows. - Operational Efficiency: Reduce time spent on manual processes while ensuring scalable, reliable data handling. Exportly.ai is most relevant for mid-sized and enterprise companies seeking to optimize the performance of established outbound sales programs. Exportly creates a standardized process that supports data accuracy, operational efficiency, and scalable outbound activity. In summary, Exportly.ai simplifies prospect data management and enables larger sales teams to run outbound campaigns more effectively. **Average Rating:** 4.8/5.0 **Total Reviews:** 3 **Who Is the Company Behind Exportly?** - **Seller:** [Exportly](https://www.g2.com/sellers/exportly) - **Year Founded:** 2019 - **HQ Location:** San Francisco, Minnesota, United States - **LinkedIn® Page:** https://www.linkedin.com/company/befrontier (104 employees on LinkedIn®) **Who Uses This Product?** - **Company Size:** 67% Mid-Market #### What Are Exportly's Pros and Cons? **Pros:** - Affordable (1 reviews) - Contact Information (1 reviews) - CRM Integration (1 reviews) - Daily Use (1 reviews) - Data Accuracy (1 reviews) **Cons:** - CRM Issues (1 reviews) - Missing Features (1 reviews) ### 6. [Vast Data](https://www.g2.com/products/vast-data/reviews) VAST delivers the first AI Operating System, natively unifying and orchestrating storage, database, and compute to unleash the true power of agentic computing and data-intensive applications.​ **Average Rating:** 4.7/5.0 **Total Reviews:** 6 **Who Is the Company Behind Vast Data?** - **Seller:** [Vast Data](https://www.g2.com/sellers/vast-data) - **Year Founded:** 2016 - **HQ Location:** United States - **Twitter:** @VAST_Data (5,790 Twitter followers) - **LinkedIn® Page:** https://www.linkedin.com/company/vast-data (977 employees on LinkedIn®) **Who Uses This Product?** - **Company Size:** 33% Small-Business, 33% Enterprise #### What Are Vast Data's Pros and Cons? **Pros:** - Storage Solutions (3 reviews) - Data Management (2 reviews) - Performance (2 reviews) - Scalability (2 reviews) - Simple (2 reviews) **Cons:** - Complex Setup (1 reviews) - Connection Issues (1 reviews) - Connectivity Issues (1 reviews) - Expensive (1 reviews) - Pricing Issues (1 reviews) ### 7. [Promethium](https://www.g2.com/products/promethium/reviews) Promethium delivers self-service data at AI scale through its revolutionary Instant Data Fabric™ — the first agentic platform purpose-built for modern enterprises. Unlike traditional data architectures that require complex ETL pipelines and data movement, Promethium provides real-time, zero-copy access to distributed data across cloud, on-premises, and SaaS platforms. The platform's 360° Context Engine aggregates technical and business metadata to ensure accurate, contextual responses, while Mantra™, our Data Answer Agent, enables teams to build and share reusable data products instantly. Promethium empowers data teams to respond 10x faster to business questions while maintaining enterprise-grade governance and security. **Average Rating:** 4.2/5.0 **Total Reviews:** 13 **Who Is the Company Behind Promethium?** - **Seller:** [Promethium](https://www.g2.com/sellers/promethium) - **Year Founded:** 2018 - **HQ Location:** Menlo Park, US - **Twitter:** @PromethiumI (363 Twitter followers) - **LinkedIn® Page:** https://www.linkedin.com/company/pm61data/ (38 employees on LinkedIn®) **Who Uses This Product?** - **Company Size:** 46% Mid-Market, 31% Enterprise #### What Are Promethium's Pros and Cons? **Pros:** - Insights (4 reviews) - Analytics (3 reviews) - Collaboration (2 reviews) - Data Management (2 reviews) - Data Visualization (2 reviews) **Cons:** - Complexity (1 reviews) - Complex Usage (1 reviews) - Difficult Learning (1 reviews) - Lacking Features (1 reviews) - Limited Features (1 reviews) ### 8. [Rayven](https://www.g2.com/products/rayven/reviews) What is Rayven? Rayven is an operational software platform that delivers an AI data fabric - connecting every system, data source, and data stream across a business into a single managed environment, then letting teams build custom apps, AI agents, workflow automations, dashboards, and MCP servers for direct AI model connectivity on top. It is the platform for organisations that need to act on operational data in real-time, deploy AI that actually works in production + build software that fits the way their business operates - without replacing existing systems or waiting 18 months for results. The Problem Rayven Solves Most organisations already have the systems and data they need. The challenge is fragmentation. ERP systems, SCADA platforms, IoT devices, databases, cloud tools, and files all generate valuable data - but it sits in silos, impossible to act on in real-time. The result: manual reporting, disconnected workflows, and AI projects that fail before reaching production. Industry research shows 95% of AI projects never ship - most because the underlying data layer is not clean, connected, or ready. Rayven builds that foundation first, then activates it. The Rayven Platform Rayven operates across five unified layers, delivered as a single managed environment: - Integration: More than 600 pre-built connectors pull data from IT, OT, IoT, files, APIs, databases, and data streams - bidirectionally, in real-time. Connects industrial protocols (OPC UA, Modbus, MQTT, BACnet) alongside cloud platforms, business systems, and proprietary tools. - Data: All connected data lands in a single managed platform - structured, governed + AI-ready. Real-time processing, ETL pipelines, data lakes, and AI model training handled in one place. - Execution: Automation rules, predictive models + agentic AI run directly on live operational data. Rules-based logic, machine learning, and goal-seeking autonomous agents all operate in one execution environment. - Presentation: Custom apps, dashboards, portals, conversational interfaces, and mobile applications deployed from the same platform - built for specific workflows, not generic reporting. - Security, Governance + Hosting: Role-based access control, data lineage, audit trails, AES-256 encryption, data residency controls, and enterprise-grade infrastructure - included as standard. AI Capabilities Rayven includes ten native AI capabilities built directly into the platform: 1. Custom AI agents (goal-seeking, action-taking) 2. Predictive analytics and machine learning 3. Conversational analytics 4. Real-time and continuous model training 5. AI-led workflow automation 6. Multimodal processing (documents, video, images, audio) 7. Anomaly and risk detection 8. Forecasting and optimisation 9. Vision and edge AI inference 10. Generative operational summaries MCP server support enables direct connectivity for AI models including Claude, GPT, and others. What Gets Built Rayven customers build and deploy: - Custom operational apps and field applications. - AI agents that monitor conditions, detect anomalies + take corrective action autonomously. - Predictive maintenance and performance models running on live plant data. - Real-time dashboards and executive reporting tools. - Workflow automations spanning IT and OT systems. - Customer and partner portals. - Data pipelines and integration layers. - White-label software products delivered under partner brands. Key Differentiators vs. Point solutions (Zapier, MuleSoft, Power BI, DataRobot): point solutions do one thing well but force teams to stitch together five separate tools to cover integration, data, AI, presentation, and governance. Rayven replaces the stack. vs. Traditional enterprise platforms (SAP, Oracle, Palantir): enterprise platforms take 12-18 months and seven figures to implement. Rayven deploys in two to 12 weeks at fixed scope and fixed price. vs. Low-code app builders (Mendix, OutSystems): app builders handle the presentation layer but do not solve the underlying data and integration problem. Rayven covers the full stack. Technology Compatibility Rayven is fully technology-agnostic and works alongside existing systems: - Cloud platforms: Microsoft Azure, Google Cloud + AWS - Business systems: SAP, Salesforce, Oracle, and Microsoft 365 - OT platforms: Siemens, Rockwell, Schneider Electric, and Ignition - Industrial protocols: OPC UA, Modbus, MQTT, BACnet, and EtherNet/IP - IoT devices: any device with a data output - Custom and proprietary systems via API, webhook, or direct connector Nothing needs to be replaced. Every existing investment is preserved. Who Uses Rayven Rayven serves businesses from growth-stage to large enterprise across 24+ industries globally - manufacturing, mining, construction, infrastructure, logistics, utilities, financial services, healthcare, agriculture, government, and more. Customers across Australia, Europe, North America, South America, and Africa. Named customers include Anglo American, Fulton Hogan, Glencore, Vodafone, NSW Ports, CSIRO, Collective Intelligence, Ramjack, and AngloGold Ashanti. Delivery Options - DIY: Full platform access. Internal teams build and deploy independently. - Done-For-You: Australia-based delivery team. Fixed scope, fixed price, two to 12 weeks from brief to go-live. - Hybrid: Guided delivery first, with the customer's team taking increasing ownership over time. By the Numbers - More than 600 pre-built connectors. - Ten native AI capabilities. - More than 240 deployments live globally. - Rated 5/5 across more than 140 independent reviews. - Deploys 66% faster than traditional development. - Two to 12 weeks to first working solution. - Rayven exists to close the gap: 95% of AI projects never reach production (industry average). **Average Rating:** 4.9/5.0 **Total Reviews:** 29 **Who Is the Company Behind Rayven?** - **Seller:** [Rayven](https://www.g2.com/sellers/rayven) - **Year Founded:** 2016 - **HQ Location:** Sydney, AU - **Twitter:** @RayvenIOT (56 Twitter followers) - **LinkedIn® Page:** https://www.linkedin.com/company/rayveniot/ (29 employees on LinkedIn®) **Who Uses This Product?** - **Top Industries:** Retail - **Company Size:** 67% Mid-Market, 50% Small-Business #### What Are Rayven's Pros and Cons? **Pros:** - Ease of Use (61 reviews) - Features (49 reviews) - Automation (44 reviews) - Customization (42 reviews) - Data Management (36 reviews) **Cons:** - Learning Curve (32 reviews) - Difficult Learning (30 reviews) - Learning Difficulty (25 reviews) - Complex Setup (21 reviews) - Setup Complexity (19 reviews) ### 9. [Hammerspace](https://www.g2.com/products/hammerspace/reviews) Hammerspace is the high-performance data platform built to simplify and optimize AI infrastructure at scale. It makes all your data immediately accessible – anywhere across on-premises and cloud environments – without copying or migrating data into new silos. By integrating with existing storage, networking, and applications, Hammerspace creates a unified, high-speed data backbone for AI, enabling organizations to accelerate every stage of the AI pipeline while eliminating data silos. What are the most important features of Hammerspace? ~Global Namespace: Unifies fragmented file and object data into a single global namespace that spans sites, clouds and storage systems. ~Parallel File System Architecture: Deliver the performance and scale for AI and HPC workloads without a proprietary client. ~Data Orchestration: Automate the flow of data and bring data to the compute that needs it no matter where it is located. ~Data-in-Place Assimilation: Make millions of files visible and accessible instantly - without complex data migrations. Don’t migrate - assimilate! ~Tier 0 Storage: Use server-local NVMe as a tier of high-performance shared storage What benefits or ROI should users look for when evaluating Hammerspace? ~AI/HPC Performance and Scale: Hammerspace delivers performance for AI and HPC with a parallel file system architecture ~Eliminate Data Silos: Unify fragmented unstructured data into a global namespace AI-Ready Data: Turn fragmented, unstructured data into AI-Ready data with an AI Data Platform. ~Hybrid-Cloud Agility: Make hybrid-cloud and multi-cloud computing and storage a reality with a global file system and policy-based data orchestration. ~Improved Productivity: Eliminate data copy sprawl, and stop manually copying data between disparate storage systems. Spend more time building, and less time managing data. **Average Rating:** 4.5/5.0 **Total Reviews:** 3 **Who Is the Company Behind Hammerspace?** - **Seller:** [Hammerspace](https://www.g2.com/sellers/hammerspace) - **Year Founded:** 2018 - **HQ Location:** Redwood City, US - **Twitter:** @Hammerspace_Inc (733 Twitter followers) - **LinkedIn® Page:** https://www.linkedin.com/company/hammerspace/ (231 employees on LinkedIn®) **Who Uses This Product?** - **Company Size:** 33% Mid-Market, 33% Small-Business ### 10. [Megarray](https://www.g2.com/products/megarray/reviews) Megarray is designed to provide operating capabilities to manage all the social media, SEO, content marketing, and video marketing through a single platform. **Average Rating:** 5.0/5.0 **Total Reviews:** 1 **Who Is the Company Behind Megarray?** - **Seller:** [Megarray](https://www.g2.com/sellers/megarray) - **Year Founded:** 2015 - **HQ Location:** Jasola, IN - **LinkedIn® Page:** http://www.linkedin.com/company/megarray-india (1 employees on LinkedIn®) **Who Uses This Product?** - **Company Size:** 50% Mid-Market, 50% Small-Business ### 11. [Verdantis Master Data Management Suite](https://www.g2.com/products/verdantis-master-data-management-suite/reviews) Verdantis MDM Suite is an AI-native master data management software built specifically for asset-intensive industries like Oil & Gas, Mining, Energy, Utilities, and Manufacturing. Unlike generic MDM platforms, it is engineered from the ground up to handle the complexity of industrial data across materials, customers, vendors, and services, making it the go-to solution for enterprises that cannot afford data inconsistencies in their operations. Harmonize tackles legacy data by automating the cleansing, deduplication, and normalization of data accumulated from ERP migrations, acquisitions, and multi-site operations, turning years of messy records into clean, usable master data. Integrity keeps that data clean going forward through business rules, validation checks, and change workflows that teams configure themselves, ensuring ongoing master data governance around your standards. MDM Suite also includes a set of AI tools built for industrial data challenges. AutoDoc extracts structured data from engineering drawings, BOMs, and datasheets using OCR and contextual AI. SpareSeek surfaces equivalent, alternate, and obsolete parts across vendor catalogs. TransAI translates and localizes data into regional languages and technical standards for global teams. Auto-Enrichment automatically populates missing attributes across master data using AI models trained on industrial data. Verdantis connects natively with SAP S/4HANA, SAP ECC, Oracle EAM, IBM Maximo, and Microsoft Dynamics 365, and deploys on cloud, on-premise, or hybrid infrastructure. **Average Rating:** 4.5/5.0 **Total Reviews:** 6 **Who Is the Company Behind Verdantis Master Data Management Suite?** - **Seller:** [Verdantis](https://www.g2.com/sellers/verdantis) - **Year Founded:** 2004 - **HQ Location:** Princeton, US - **LinkedIn® Page:** https://www.linkedin.com/company/verdantis-inc/ (74 employees on LinkedIn®) **Who Uses This Product?** - **Company Size:** 67% Enterprise, 50% Mid-Market #### What Are Verdantis Master Data Management Suite's Pros and Cons? **Pros:** - Ease of Use (5 reviews) - Data Management (4 reviews) - Data Accuracy (3 reviews) - Data Quality (3 reviews) - Time-saving (3 reviews) **Cons:** - Complex Setup (2 reviews) - Difficult Setup (2 reviews) - Setup Difficulty (2 reviews) - Complexity (1 reviews) - Data Management Issues (1 reviews) ### 12. [AI Data Platform](https://www.g2.com/products/ai-data-platform/reviews) DataGOL is an AI-powered Business Agility Platform which brings Data, AI and Applications under one roof. Empowering small and medium-sized businesses with simple, affordable, and easy-to-use data tools that drive growth. The DataGOL platform eliminates complexity, integrates seamlessly with existing systems, and delivers quick, measurable results, enabling businesses to harness the power of data like large enterprises — without the need for big budgets or specialized skills. **Who Is the Company Behind AI Data Platform?** - **Seller:** [DataGOL](https://www.g2.com/sellers/datagol) - **Year Founded:** 2024 - **HQ Location:** Princeton, US - **LinkedIn® Page:** https://www.linkedin.com/company/datagol (9 employees on LinkedIn®) ### 13. [BrightCat Data](https://www.g2.com/products/brightcat-data/reviews) BrightCat Data is the unified property intelligence layer for the Canadian real estate market. We track 5.8 million residential properties and 297,000 commercial properties across Canada weekly, using persistent matchkeys to preserve full property lifecycle history across every listing, price change, and transaction. Six integrated datasets — Listings, Sold, Rentals, Commercial, Core, and PreMovers — delivered through Snowflake Marketplace Secure Data Share and MCP connector for AI agents. Used by enterprise teams in insurance, banking, telecom, and direct marketing for risk detection, collateral monitoring, pre-mover customer acquisition, and trigger-based campaigns. 12 years of continuous weekly tracking. The only Canadian provider combining pre-mover signals, lifecycle tracking, renovation detection, and a repeat-sale home price index in a single integrated dataset. **Who Is the Company Behind BrightCat Data?** - **Seller:** [BrightCat Data](https://www.g2.com/sellers/brightcat-data) - **HQ Location:** Toronto, CA - **LinkedIn® Page:** https://www.linkedin.com/company/brightcat-data-analytics-inc/ (2 employees on LinkedIn®) ### 14. [Capalyze](https://www.g2.com/products/capalyze/reviews) Capalyze is the only product on the market that leverages natural language to drive both web data extraction and spreadsheet-style analysis. It seamlessly integrates data extraction and analysis into automated workflows, empowering users with end-to-end capabilities in data integration, analysis, and visualization — enabling truly data-driven decision making. **Who Is the Company Behind Capalyze?** - **Seller:** [Dream Number](https://www.g2.com/sellers/dream-number) - **HQ Location:** N/A - **Twitter:** @univerHQ (136 Twitter followers) - **LinkedIn® Page:** https://www.linkedin.com/company/No-Linkedin-Presence-Added-Intentionally-By-DataOps (1 employees on LinkedIn®) ### 15. [Cinchy](https://www.g2.com/products/cinchy-cinchy/reviews) With the Cinchy Data Collaboration platform liberate data from applications and control and connect as data products in a network, eliminating the need for future data integration. Build a more agile data ecosystem that makes change simple, rapidly accelerates business outcomes, and fosters collaborative intelligence across your enterprise. With Cinchy, cure the pains of integration to deliver projects at half the cost and time, improve data governance with universal data access controls, and provide data access to business users for self-serve reporting and analytics. **Average Rating:** 4.8/5.0 **Total Reviews:** 19 **Who Is the Company Behind Cinchy?** - **Seller:** [Cinchy](https://www.g2.com/sellers/cinchy) - **Year Founded:** 2017 - **HQ Location:** Toronto, ON - **Twitter:** @itscinchy (462 Twitter followers) - **LinkedIn® Page:** https://www.linkedin.com/company/16200640/ (41 employees on LinkedIn®) **Who Uses This Product?** - **Top Industries:** Financial Services - **Company Size:** 53% Mid-Market, 37% Enterprise ### 16. [Cohesity DataProtect delivered as a service](https://www.g2.com/products/cohesity-dataprotect-delivered-as-a-service/reviews) Cohesity DataProtect delivered as a service is an enterprise-class, fully managed cloud backup solution designed to protect critical data across SaaS applications, cloud-native services, and on-premises environments. By eliminating the need for on-premises infrastructure, it simplifies data protection through a unified platform that offers policy-based automation, global visibility, and rapid recovery capabilities. This service ensures data security with immutable backups, strong encryption, and strict access controls, providing organizations with a reliable and scalable solution to safeguard their data assets. Key Features and Functionality: - Comprehensive Protection: Safeguards a wide range of workloads, including SaaS applications, cloud-native services, and on-premises data sources, ensuring holistic data coverage. - Simplified Management: Offers a single, intuitive user interface for managing all backup and recovery tasks, reducing operational complexity and enhancing efficiency. - Cost Optimization: Utilizes advanced data reduction techniques and eliminates infrastructure maintenance costs, providing transparent and predictable pricing models. - Robust Security: Features immutable, tamper-resistant backups with strong encryption and strict privileged access controls to protect against cyber threats. - Intelligent Automation: Employs policy-based automation, flexible retention policies, and seamless cross-source search capabilities to streamline backup and recovery processes. Primary Value and Problem Solved: Cohesity DataProtect delivered as a service addresses the challenges of managing and protecting data across diverse environments by providing a unified, cloud-native solution that simplifies backup operations, enhances data security, and reduces costs. It enables organizations to focus on strategic initiatives by offloading the complexities of data protection, ensuring rapid recovery, and maintaining compliance with industry standards. **Who Is the Company Behind Cohesity DataProtect delivered as a service?** - **Seller:** [Cohesity](https://www.g2.com/sellers/cohesity) - **Year Founded:** 2013 - **HQ Location:** San Jose, CA - **Twitter:** @Cohesity (29,273 Twitter followers) - **LinkedIn® Page:** https://www.linkedin.com/company/3750699/ (7,721 employees on LinkedIn®) ### 17. [Collate](https://www.g2.com/products/collate-collate/reviews) Collate has developed a data management platform that provides AI-driven automation for data discovery, observability, and governance, enabling businesses to improve productivity, reduce costs by consolidating tooling, and mitigate risks through automated compliance and governance standards **Who Is the Company Behind Collate?** - **Seller:** [Collate](https://www.g2.com/sellers/collate) - **HQ Location:** San Francisco, US - **LinkedIn® Page:** https://www.linkedin.com/company/collate-software/ (8 employees on LinkedIn®) ### 18. [DataOS](https://www.g2.com/products/dataos/reviews) DataOS is the data activation layer for AI, applications, and analytics. It sits on top of an organization’s existing data stack and unifies semantics, governance, quality, lineage, and access into a single, reusable operating capability, without requiring rip-and-replace. Built to serve not only human analysts but also AI agents and automated workflows, DataOS makes data consistent, trusted, and ready for action at machine speed. DataOS delivers AI-ready data through four core pillars: 1) Context Data becomes usable when meaning travels with it. DataOS aligns shared definitions for entities, metrics, dimensions, and relationships so dashboards, apps, and agents interpret information the same way. 2) Trust AI systems require runtime confidence. DataOS combines centralized policy decisions with distributed enforcement, declarative data quality checks, and end-to-end lineage for auditability and debugging. 3) Action Different consumers need different interfaces. DataOS provides a unified query layer and standardized access patterns such as SQL, APIs, and agent-ready interfaces, with guardrails like intent and result validation. 4) Productization DataOS treats reusable data products as the unit of scale. These bundle semantics, governance, quality signals, ownership, documentation, lifecycle management, and versioning, making data scale the way software does. **Who Is the Company Behind DataOS?** - **Seller:** [The Modern Data Company](https://www.g2.com/sellers/the-modern-data-company) - **Year Founded:** 2019 - **HQ Location:** Palo Alto, US - **LinkedIn® Page:** https://www.linkedin.com/company/themoderndatacompany/ (182 employees on LinkedIn®) ### 19. [dataX.ai](https://www.g2.com/products/datax-ai/reviews) dataX.ai is a trailblazing data science company specializing in automated solutions for B2B eCommerce product content. Our goal is to minimize manual effort in data processing and management, enhancing accuracy and enabling scalable operations. With more than a decade of experience crafting AI-powered solutions, we have become a trusted partner to eContent managers, as innovation meets precision in executing seamless data workflows. Headquartered in Plano, Texas, we have offices spread across India and Japan, empowering modern businesses to remain agile, competitive, and thrive in the digital era. **Average Rating:** 4.4/5.0 **Total Reviews:** 4 **Who Is the Company Behind dataX.ai?** - **Seller:** [CrowdANALYTIX](https://www.g2.com/sellers/crowdanalytix) - **Year Founded:** 2012 - **HQ Location:** Plano, US - **Twitter:** @data_x_ai (16 Twitter followers) - **LinkedIn® Page:** https://www.linkedin.com/company/crowdanalytix (115 employees on LinkedIn®) **Who Uses This Product?** - **Company Size:** 50% Small-Business, 25% Enterprise ### 20. [dmaya](https://www.g2.com/products/dmaya/reviews) The AI design platform purpose-built for agencies, teams, and freelancers. Generate production-ready UI designs, iterate with clients, present work that wins. Every AI tool on the market today targets solo enthusiasts who want to build something on their own. They generate code, not designs. They skip the planning phase. They don't understand that in agencies and teams, design comes before development — and client sign-off comes before everything. You need to present concepts to stakeholders. You need to iterate on visual direction before anyone writes a line of code. You need a tool that respects the design process — not one that skips it entirely. dMaya is built for the way professional teams actually work. **Who Is the Company Behind dmaya?** - **Seller:** [dMaya](https://www.g2.com/sellers/dmaya) - **HQ Location:** N/A - **LinkedIn® Page:** https://www.linkedin.com/company/No-Linkedin-Presence-Added-Intentionally-By-DataOps (1 employees on LinkedIn®) ### 21. [Factr](https://www.g2.com/products/factr/reviews) Factr helps businesses, teams, and individuals find and share the information they need, and make better decisions. **Average Rating:** 4.5/5.0 **Total Reviews:** 1 **Who Is the Company Behind Factr?** - **Seller:** [Factr](https://www.g2.com/sellers/factr) - **Year Founded:** 2013 - **HQ Location:** Brooklyn, US - **Twitter:** @Factr (247 Twitter followers) - **LinkedIn® Page:** https://www.linkedin.com/company/factr/ (6 employees on LinkedIn®) **Who Uses This Product?** - **Company Size:** 100% Small-Business ### 22. [Finden](https://www.g2.com/products/finden/reviews) Finden is an AI workspace that unifies, automates and helps run your business — Connect all your data, across drives, devices, tools and applications — Organize files, enrich your data, chat with your data, and automatically find what matters in your Memory Bank. Finden enables businesses of all sizes to: - Improve productivity and operations: help you work with your data seamlessly, gain insights, reduce silo workflows and automate actions - Save time: less time sorting your data and more automation - Reduce costs: reduce number of SaaS tools and cloud storage. - Be more sustainable: manage inefficient use of data (more than 30% of data is redundant) - Remain secure: privacy is key - your data never used for any AI training. **Average Rating:** 5.0/5.0 **Total Reviews:** 2 **Who Is the Company Behind Finden?** - **Seller:** [Finden](https://www.g2.com/sellers/finden) - **HQ Location:** Boca Raton, US - **LinkedIn® Page:** https://www.linkedin.com/company/finden4me/ (1 employees on LinkedIn®) **Who Uses This Product?** - **Company Size:** 150% Small-Business #### What Are Finden's Pros and Cons? **Pros:** - Ease of Use (2 reviews) - Easy Access (2 reviews) - Features (2 reviews) - Search Efficiency (2 reviews) - Speed (2 reviews) **Cons:** - Integration Issues (1 reviews) ### 23. [Inflectiv](https://www.g2.com/products/inflectiv/reviews) Inflectiv is a software platform that enables users to convert unstructured information into structured datasets that can be queried by AI agents and applications. The product supports ingesting documents, research materials, operational knowledge, and selected real-world data sources, and transforms them into structured, machine-readable formats optimized for AI workflows. Inflectiv allows users to create datasets, manage access permissions, and expose these datasets to AI agents, automation workflows, and external applications through queries and integrations. The platform is designed to support use cases such as AI copilots, compliance automation, research assistants, and agent-based workflows. The product also includes functionality for dataset versioning, usage tracking, and monetization, allowing dataset creators to control access and earn from usage. Inflectiv integrates with existing AI infrastructure and agent frameworks, enabling structured data to be used across different environments without requiring custom data pipelines. Inflectiv is used by developers, AI teams, and organizations that need reliable, structured data as input for AI agents and automated systems. **Who Is the Company Behind Inflectiv?** - **Seller:** [Inflectiv](https://www.g2.com/sellers/inflectiv) - **HQ Location:** Dubai, AE - **LinkedIn® Page:** https://www.linkedin.com/company/inflectivai/ (12 employees on LinkedIn®) ### 24. [KGNN - Knowledge Graph Neural Network](https://www.g2.com/products/kgnn-knowledge-graph-neural-network/reviews) Equitus KGNN is an automated data unification platform in the knowledge graph and AI data infrastructure category. It is designed for enterprise organizations seeking to ingest, structure, and contextualize large volumes of structured and unstructured data without relying on traditional ETL processes. KGNN automates the transformation of disparate enterprise data into semantically enriched, AI-ready knowledge to support use cases such as analytics, business intelligence (BI), and generative AI (GenAI) deployment. Equitus KGNN uses a combination of natural language processing (NLP), machine learning (ML), and semantic technologies to dynamically build a self-constructing RDF knowledge graph. This semantic core enables organizations to extract entities, relationships, and contextual meaning from raw data—including documents, logs, and databases—and transform it into structured, vectorized formats optimized for advanced analytics and AI model consumption. Equitus KGNN is suited for: Enterprises operating across fragmented data systems. Organizations needing contextualized data for AI, BI, or compliance use cases. Teams looking to unify legacy and modern systems without redesigning infrastructure. Key Capabilities: Automated Data Ingestion: Handles structured and unstructured sources without manual pipelines. Semantic Auto-Mapping: Dynamically generates a schema-less RDF knowledge graph. Federated Integration: Enables bi-directional data exchange across legacy and modern platforms. Real-Time Vectorization: Prepares data for AI models, RAG/CAG pipelines, and vector search. Governance and Provenance: Maintains full data lineage, security, and compliance controls. Benefits: Reduce reliance on manual data engineering by 80%. Minimize latency with near real-time data processing. Improve AI accuracy and explainability through contextual enrichment. Ensure compatibility with secure, on-premise, or air-gapped environments. Minimum System Requirements: IBM Power10/11 40 Cores 512GB RAM 4TB SSD (usable) RedHat OpenShift 4.18 X86/GPU 24 Cores 256GB RAM Nvidia GPU with 24GB+ 4TB SSD (usable) RedHat OpenShift 4.18 Equitus KGNN is built for scalability, edge-readiness, and enterprise-grade deployment, enabling seamless data unification across the full lifecycle of AI and analytics initiatives. **Who Is the Company Behind KGNN - Knowledge Graph Neural Network?** - **Seller:** [Equitus](https://www.g2.com/sellers/equitus) - **HQ Location:** N/A - **LinkedIn® Page:** https://www.linkedin.com/company/equitus (1 employees on LinkedIn®) ### 25. [MyDataWork](https://www.g2.com/products/mydatawork/reviews) MyDataWork is a workspace for data analysts, analytics engineers, and BI developers who manage recurring work across multiple files, tools, and stakeholders. It brings together asset cataloging, data lineage visualization, use case tracking, business outcome measurement, and AI-powered analysis in one place built specifically for how analysts actually work. Most analytics teams operate without a central record of their work. Files live in folders. Context lives in people's heads. The value of data investment stays invisible until someone asks — and by then, reconstructing the answer takes longer than it should. MyDataWork fixes that at the individual analyst level and scales the benefit to managers, IT leaders, and the organization as a whole. Asset catalog and data lineage MyDataWork reads metadata from local files — Excel, SQL, Python, Alteryx, Tableau, Power BI, CSV — and cloud platforms including GitHub, dbt Cloud, Databricks, and Snowflake to build a live asset catalog automatically. No manual entry required. Data lineage is built from the same metadata, showing which files feed which reports and which pipelines support which dashboards. External dependencies — data sources referenced in files but not yet tracked — are surfaced with amber flagging so invisible risks become visible before they cause problems. Use case tracking and outcome measurement Analysts connect their assets to documented use cases that record what each deliverable is for, who depends on it, what the objective is, and how progress is measured against a baseline and target. Estimated and realized value is tracked across the portfolio. A statistical outlier detection layer flags reported values that look unusual relative to comparable work — helping analysts walk into stakeholder conversations with numbers they can defend. AI-powered analysis Six AI features help analysts go further: use case recommendations, reuse opportunity identification, automation candidate analysis, external marketplace data discovery, tool migration and modernization evaluation, and a context-aware workspace assistant available on every screen. Integrations and export MyDataWork integrates with Jira to push use case updates directly to tickets with one click. Portfolio summaries export as PowerPoint or PDF for leadership conversations and governance reviews — no app access required for stakeholders. Built for individual analysts and analytics teams of any size who want to organize their work, demonstrate its value, and hand off context without losing institutional knowledge. **Who Is the Company Behind MyDataWork?** - **Seller:** [MyDataWork](https://www.g2.com/sellers/mydatawork) - **HQ Location:** N/A - **LinkedIn® Page:** https://www.linkedin.com/company/mydatawork/ (1 employees on LinkedIn®) ## What Is Data Management Software? [IT Infrastructure Software](https://www.g2.com/categories/it-infrastructure)