# Best DataOps Platforms for Small Business *By [Shalaka Joshi](https://research.g2.com/insights/author/shalaka-joshi)* Products classified in the overall DataOps Platforms category are similar in many regards and help companies of all sizes solve their business problems. However, small business features, pricing, setup, and installation differ from businesses of other sizes, which is why we match buyers to the right Small Business DataOps Platforms to fit their needs. Compare product ratings based on reviews from enterprise users or connect with one of G2's buying advisors to find the right solutions within the Small Business DataOps Platforms category. In addition to qualifying for inclusion in the DataOps Platforms category, to qualify for inclusion in the Small Business DataOps Platforms category, a product must have at least 10 reviews left by a reviewer from a small business. ## How Many DataOps Platforms Products Does G2 Track? **Total Products under this Category:** 102 ### Category Stats (May 2026) - **Average Rating**: 4.6/5 (↑0.01 vs Apr 2026) - **New Reviews This Quarter**: 98 - **Buyer Segments**: Mid-Market 46% │ Enterprise 30% │ Small-Business 24% - **Top Trending Product**: Cloudera Data Platform (+0.155) *Last updated: May 18, 2026* ## How Does G2 Rank DataOps Platforms Products? **Why You Can Trust G2's Software Rankings:** - 30 Analysts and Data Experts - 4,500+ Authentic Reviews - 102+ 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. --- **Sponsored** ### QuerySurge QuerySurge is an enterprise-grade data quality platform that leverages AI to continuously automate data validation across your entire ecosystem ‐ from data warehouses and big data lakes to BI reports and enterprise applications. With AI-powered test creation, scalable architecture, and the leading DevOps for Data CI/CD integration, QuerySurge ensures data integrity at every stage of the pipeline. Automated Data Validation Use Cases: QuerySurge provides a smart, AI-driven, data validation & ETL testing solution for your automated testing needs. - Data Warehouse / ETL Testing - DevOps for Data / Continuous Testing - Data Migration Testing - Business Intelligence (BI) Report Testing - Big Data Testing - Enterprise Application Data Testing What QuerySurge Provides: - Automation of your manual data validation and testing process - Ease-of-use, low-code/no-code features - Generative AI capabilities for test creation - Testing across 200+ data platforms - Integration into your CI/CD DataOps pipeline - Acceleration of your data analysis - Ensurance of regulatory compliance Key Features: - Data Connection Wizard provides an easy way to link to your data stores - Visual Query Wizard builds table-to-table and column-to-column tests without writing SQL - Generative AI module automatically creates transformation tests in bulk - DevOps for Data provides a RESTful API with 110+ calls and Swagger documentation and integrates into CI/CD pipelines - Create Custom Tests and modularize functions with snippets, set thresholds, stage data, check data types & duplicate rows, full text search, and asset tagging - Schedule tests to run immediately, at a predetermined date & time, or after any event from a build/release, CI/CD, DevOps, or test management solution - Multi-project support in a single instance, new Global Admin user, assign users and agents, import and export projects, and user activity log reports - Webhooks provide real-time integrations with DevOps, CI/CD, test management, and alerting tools - Ready-for-Analytics provides seamless integration with QuerySurge and your BI tool or open-source Metabase to create custom reports and dashboards and gain deeper, real-time insights into your data validation and ETL testing workflows - Data Analytics Dashboards and Data Intelligence Reports track, analyze, and communicate data quality [Visit website](https://www.g2.com/external_clickthroughs/record?secure%5Bad_program%5D=ppc&secure%5Bad_slot%5D=category_product_list&secure%5Bcategory_id%5D=2686&secure%5Bdisplayable_resource_id%5D=2686&secure%5Bdisplayable_resource_type%5D=Category&secure%5Bmedium%5D=sponsored&secure%5Bplacement_reason%5D=page_category&secure%5Bplacement_resource_ids%5D%5B%5D=2686&secure%5Bprioritized%5D=false&secure%5Bproduct_id%5D=54942&secure%5Bresource_id%5D=2686&secure%5Bresource_type%5D=Category&secure%5Bsource_type%5D=category_page&secure%5Bsource_url%5D=https%3A%2F%2Fwww.g2.com%2Fcategories%2Fdataops-platforms%2Fsmall-business&secure%5Btoken%5D=edfda299fe374af1d2c8c2516a1590d9e5bcca11720ca76c9cf75a7ec64e9845&secure%5Burl%5D=https%3A%2F%2Fwww.querysurge.com%2Fget-started%2Fprivate-demo%3Futm_source%3DG2%26utm_medium%3Dcpc%26utm_campaign%3DG2-reviews&secure%5Burl_type%5D=book_demo) --- ## What Are the Top-Rated DataOps Platforms Products in 2026? ### 1. [Databricks](https://www.g2.com/products/databricks/reviews) Databricks is a unified data and AI platform that helps organizations build, govern and scale data pipelines, analytics, machine learning, AI applications and agents. More than 20,000 organizations worldwide — including adidas, AT&T, Bayer, Block, Mastercard, Rivian, Unilever, and 70% of the Fortune 500 — rely on Databricks to work with enterprise data and AI at scale. Headquartered in San Francisco with 30+ offices around the globe, Databricks offers a unified platform that includes Agent Bricks, Lakeflow, Lakehouse, Lakebase, Genie and Unity Catalog. Founded in 2013 by the original creators of Apache Spark™, Delta Lake, MLflow and Unity Catalog, Databricks is built on an open lakehouse architecture that brings data, analytics and AI together. The platform is used by data engineers, data scientists, analysts, developers, machine learning teams, AI teams and business users to collaborate across the full data and AI lifecycle. Key Databricks capabilities include: - Data engineering: Build, automate and manage reliable batch, streaming and real-time data pipelines. - Analytics and business intelligence: Run SQL analytics, create dashboards and enable business teams to explore data. - Data governance: Discover, secure and manage data and AI assets across teams, clouds and workloads. - Machine learning and AI: Develop models, build generative AI applications and create production-grade AI agents. - Data applications: Build and deploy data-driven applications using governed enterprise data. Available across AWS, Azure and Google Cloud, Databricks helps organizations work across clouds, reduce data silos and simplify collaboration across teams and tools. Customers use Databricks for use cases such as customer personalization, fraud detection, predictive maintenance, real-time analytics, cybersecurity, healthcare research, financial risk management, supply chain optimization and AI-powered decision-making. Databricks is used across industries including financial services, healthcare and life sciences, retail, manufacturing, energy and the public sector. Organizations use the platform to modernize data infrastructure, accelerate AI adoption and turn enterprise data into business value. **Average Rating:** 4.6/5.0 **Total Reviews:** 754 **How Do G2 Users Rate Databricks?** - **Data Observability:** 8.7/10 (Category avg: 8.9/10) - **Testing capabilities:** 8.7/10 (Category avg: 8.6/10) - **Ease of Use:** 8.9/10 (Category avg: 9.0/10) - **What is your organization's estimated ROI on the product (payback period in months)?:** 10/10 (Category avg: 10/10) **Who Is the Company Behind Databricks?** - **Seller:** [Databricks Inc.](https://www.g2.com/sellers/databricks-inc) - **Company Website:** https://databricks.com - **Year Founded:** 2013 - **HQ Location:** San Francisco, CA - **Twitter:** @databricks (90,749 Twitter followers) - **LinkedIn® Page:** https://www.linkedin.com/company/3477522/ (14,779 employees on LinkedIn®) **Who Uses This Product?** - **Who Uses This:** Data Engineer, Senior Data Engineer - **Top Industries:** Information Technology and Services, Financial Services - **Company Size:** 44% Enterprise, 41% Mid-Market #### What Are Databricks's Pros and Cons? **Pros:** - Features (288 reviews) - Ease of Use (278 reviews) - Integrations (189 reviews) - Collaboration (150 reviews) - Data Management (150 reviews) **Cons:** - Learning Curve (112 reviews) - Expensive (97 reviews) - Steep Learning Curve (96 reviews) - Missing Features (69 reviews) - Complexity (64 reviews) ### 2. [Boost.space](https://www.g2.com/products/boost-space/reviews) Boost.space is the #1 AI-Ready Data Sync platform on G2—recognized with over 100 customer-voted badges. ⭐️ Today's enterprises are investing heavily in AI, but most initiatives fail. Why? Because AI is "stateless"—it has no memory—and it's running on chaotic data fragmented across hundreds of applications. This data chaos costs companies an average of $15 million annually and wastes nearly 12 hours per employee every week.   Boost.space solves this foundational problem by creating a new category of enterprise infrastructure: the AI Memory Layer. We are not just another application; we are the persistent, unified memory that your entire AI and automation ecosystem needs to function intelligently. Our platform connects to over 2,400 apps to dismantle data silos, creating a single source of truth (SSOT) for all your business data. But unlike passive data warehouses, Boost.space is an active, read-write memory. Our real-time, three-way synchronization engine allows AI agents to not only read unified data but also act on it by writing changes back to your operational tools. At the heart of this is our Model Context Protocol (MCP), an "AI-Ready USB-C Port" for your enterprise that allows you to prompt your business in natural language. Whether you're building an AI-Ready PIM for e-commerce or an AI-Ready CDP for marketing, Boost.space provides the essential foundation, trusted by leaders like ŠKODA to make their data AI-ready. **Average Rating:** 4.6/5.0 **Total Reviews:** 327 **How Do G2 Users Rate Boost.space?** - **Data Observability:** 8.4/10 (Category avg: 8.9/10) - **Testing capabilities:** 8.4/10 (Category avg: 8.6/10) - **Ease of Use:** 7.3/10 (Category avg: 9.0/10) - **What is your organization's estimated ROI on the product (payback period in months)?:** 10/10 (Category avg: 10/10) **Who Is the Company Behind Boost.space?** - **Seller:** [Boost.space s.r.o.](https://www.g2.com/sellers/boost-space-s-r-o) - **Year Founded:** 2017 - **HQ Location:** Prague, CZ - **Twitter:** @boostspace (80 Twitter followers) - **LinkedIn® Page:** https://www.linkedin.com/company/boost-space/?originalSubdomain=cz (43 employees on LinkedIn®) **Who Uses This Product?** - **Who Uses This:** CEO, Founder - **Top Industries:** Marketing and Advertising, Consulting - **Company Size:** 99% Small-Business, 1% Mid-Market #### What Are Boost.space's Pros and Cons? **Pros:** - Integrations (221 reviews) - Automation (211 reviews) - Easy Integrations (163 reviews) - Features (150 reviews) - Easy Integration (135 reviews) **Cons:** - Learning Curve (180 reviews) - Steep Learning Curve (153 reviews) - Learning Difficulty (65 reviews) - Complex Setup (45 reviews) - Beginner Difficulty (42 reviews) ### 3. [dbt](https://www.g2.com/products/dbt/reviews) dbt is a transformation workflow that lets data teams quickly and collaboratively deploy analytics code following software engineering best practices like modularity, portability, CI/CD, and documentation. Now anyone who knows SQL can build production-grade data pipelines. **Average Rating:** 4.7/5.0 **Total Reviews:** 205 **How Do G2 Users Rate dbt?** - **Data Observability:** 8.7/10 (Category avg: 8.9/10) - **Testing capabilities:** 8.9/10 (Category avg: 8.6/10) - **Ease of Use:** 9.0/10 (Category avg: 9.0/10) - **What is your organization's estimated ROI on the product (payback period in months)?:** 10/10 (Category avg: 10/10) **Who Is the Company Behind dbt?** - **Seller:** [Fivetran](https://www.g2.com/sellers/fivetran) - **Year Founded:** 2012 - **HQ Location:** Oakland, CA - **Twitter:** @fivetran (5,731 Twitter followers) - **LinkedIn® Page:** https://www.linkedin.com/company/fivetran/ (1,738 employees on LinkedIn®) **Who Uses This Product?** - **Who Uses This:** Data Engineer, Analytics Engineer - **Top Industries:** Information Technology and Services, Computer Software - **Company Size:** 56% Mid-Market, 27% Small-Business #### What Are dbt's Pros and Cons? **Pros:** - Ease of Use (38 reviews) - Features (22 reviews) - Automation (19 reviews) - Transformation (17 reviews) - Integrations (15 reviews) **Cons:** - Limited Functionality (14 reviews) - Dependency Issues (12 reviews) - Steep Learning Curve (10 reviews) - Error Handling (9 reviews) - Error Reporting (9 reviews) ### 4. [5X](https://www.g2.com/products/5x/reviews) 5X is an end-to-end data and AI platform. The platform organizes your data regardless of source or format. Whether you have a dedicated data team or not, our platform
transforms fragmented data into actionable insights and apps. The customer feedback we get most often is, "This is self-explanatory," and "It's super easy to use." And that is exactly what our goal was—to create a powerful, all-in-one platform that's incredibly easy to use.  The modern data stack has evolved. It's no longer about stitching together vendors. The next-generation modern data stack is an all-in-one platform that offers speed, simplicity, and decreased cost of ownership. That's exactly what we have created at 5X. Companies use 5X for multiple reasons: 1) Speed & productivity. All-in-one data platforms are incredibly efficient. We've seen companies build use cases on day 1.  Contact us to see if you qualify for a free 48 hour jumpstart! 🚀 2) Decrease your total cost of ownership by 30% compared to building your own platform. This doesn't account the people hours needed to support a platform build 🤯 3) Use our full stack data consultancy for support on data engineering & analytics 👨‍💻 5X was founded in 2020 with presence in the USA, Singapore, UK and India. Our global team is 70+ people strong and rapidly growing. We’ve recently raised our seed round from Flybridge Capital and backed by top founders from companies like Datadog, Preset, Astronomer, Mode, Rudderstack and other prominent angel investors. For more information, visit 5X.co We don't just talk about speed and simplicity; we back it up with proof. Speak to us about our 48-hour jumpstart where we can build an end-to-end use case for you in 48 hours for free. **Average Rating:** 4.9/5.0 **Total Reviews:** 81 **How Do G2 Users Rate 5X?** - **Data Observability:** 9.1/10 (Category avg: 8.9/10) - **Testing capabilities:** 9.0/10 (Category avg: 8.6/10) - **Ease of Use:** 9.5/10 (Category avg: 9.0/10) - **What is your organization's estimated ROI on the product (payback period in months)?:** 6.1/10 (Category avg: 10/10) **Who Is the Company Behind 5X?** - **Seller:** [5X](https://www.g2.com/sellers/5x) - **Year Founded:** 2020 - **HQ Location:** San Francisco - **Twitter:** @DataWith5x (49 Twitter followers) - **LinkedIn® Page:** https://www.linkedin.com/company/datawith5x/ (128 employees on LinkedIn®) **Who Uses This Product?** - **Top Industries:** Computer Software, Financial Services - **Company Size:** 56% Mid-Market, 40% Small-Business #### What Are 5X's Pros and Cons? **Pros:** - Ease of Use (28 reviews) - Customer Support (18 reviews) - Features (14 reviews) - Integrations (13 reviews) - Data Integration (10 reviews) **Cons:** - Steep Learning Curve (5 reviews) - Complex Setup (4 reviews) - Feature Limitations (4 reviews) - Learning Curve (4 reviews) - Difficult Setup (3 reviews) ### 5. [Flip](https://www.g2.com/products/kanerika-flip/reviews) FLIP by Kanerika is an AI-powered, low-code/no-code platform that automates enterprise workflows, streamlines data operations, and accelerates migrations — all without the need for technical expertise. It empowers teams to modernize faster, reduce manual effort, and focus on business outcomes. Key Capabilities: Automated Data Reconciliation Low-Code/No-Code DataOps Migration Accelerators AI Workforce Accounts Payable Automation FLIP helps organizations simplify data management, enhance accuracy, and accelerate digital transformation across industries. **Average Rating:** 5.0/5.0 **Total Reviews:** 13 **How Do G2 Users Rate Flip?** - **Data Observability:** 9.2/10 (Category avg: 8.9/10) - **Testing capabilities:** 10.0/10 (Category avg: 8.6/10) - **Ease of Use:** 10.0/10 (Category avg: 9.0/10) - **What is your organization's estimated ROI on the product (payback period in months)?:** 3.3/10 (Category avg: 10/10) **Who Is the Company Behind Flip?** - **Seller:** [Kanerika](https://www.g2.com/sellers/kanerika) - **Year Founded:** 2015 - **HQ Location:** Austin, US - **LinkedIn® Page:** http://www.linkedin.com/company/kanerika (307 employees on LinkedIn®) **Who Uses This Product?** - **Who Uses This:** Co-Founder - **Top Industries:** Computer Software - **Company Size:** 92% Small-Business, 23% Mid-Market #### What Are Flip's Pros and Cons? **Pros:** - Features (10 reviews) - Ease of Use (9 reviews) - Fast Processing (7 reviews) - Data Syncing (6 reviews) - Customization (5 reviews) **Cons:** - Complex Setup (4 reviews) - Expensive (4 reviews) - Steep Learning Curve (4 reviews) - Missing Features (3 reviews) - Integration Issues (2 reviews) ### 6. [ServiceNow Workflow Data Fabric](https://www.g2.com/products/servicenow-workflow-data-fabric/reviews) Workflow Data Fabric is the AI‑ready data foundation of the ServiceNow AI Platform. It connects to any data—structured, unstructured, and streaming—contextualizes it with business meaning and governance, and controls it with lineage and policies so employees and AI agents can confidently act on real‑time information to prevent disruptions, resolve requests faster, and optimize operations—all on one platform. How Workflow Data Fabric turns data into instant action Connect Unify data from systems like Salesforce, SAP, Workday, data lakes, and event streams in real time without duplication or fragile point‑to‑point integrations. With Zero Copy Connectors, Stream Connect, External Content Connectors, and Integration Hub, WDF simplifies architecture and cuts integration cost and time. Contextualize Give data business meaning and make it trustworthy with an active Data Catalog, embedded governance, and lineage. Use Knowledge Graph to map relationships (e.g., customers, assets, orders) so AI agents and workflows understand context and make accurate decisions in the flow of work. Control Apply policies, permissions, and compliance guards across connected sources so the right people and AI agents access the right data, at the right time, with full auditability and traceability—no more shadow copies or opaque pipelines. **Average Rating:** 4.3/5.0 **Total Reviews:** 134 **How Do G2 Users Rate ServiceNow Workflow Data Fabric?** - **Data Observability:** 8.1/10 (Category avg: 8.9/10) - **Testing capabilities:** 8.1/10 (Category avg: 8.6/10) - **Ease of Use:** 8.0/10 (Category avg: 9.0/10) - **What is your organization's estimated ROI on the product (payback period in months)?:** 10/10 (Category avg: 10/10) **Who Is the Company Behind ServiceNow Workflow Data Fabric?** - **Seller:** [ServiceNow](https://www.g2.com/sellers/servicenow) - **Company Website:** https://www.servicenow.com/ - **Year Founded:** 2004 - **HQ Location:** Santa Clara, CA - **Twitter:** @servicenow (55,054 Twitter followers) - **LinkedIn® Page:** https://www.linkedin.com/company/29352/ (32,701 employees on LinkedIn®) **Who Uses This Product?** - **Who Uses This:** Software Engineer - **Top Industries:** Information Technology and Services, Computer Software - **Company Size:** 46% Enterprise, 26% Mid-Market #### What Are ServiceNow Workflow Data Fabric's Pros and Cons? **Pros:** - Ease of Use (37 reviews) - Integrations (34 reviews) - Automation (30 reviews) - Efficiency Improvement (26 reviews) - Data Management (25 reviews) **Cons:** - Complex Setup (23 reviews) - Difficult Setup (17 reviews) - Expensive (15 reviews) - Slow Performance (14 reviews) - Complexity (13 reviews) ### 7. [Hightouch](https://www.g2.com/products/hightouch/reviews) Hightouch is the leading data and Agentic Marketing Platform for modern marketing teams. Trusted by brands like Domino’s, Autotrader, cars.com, Superhuman (formerly Grammarly), and PetSmart, Hightouch helps marketers deliver personalized experiences, optimize performance, and move faster with data and AI. With Hightouch, business users can drive revenue, grow brand awareness, and maximize ROI without relying on engineering. Hightouch’s Composable Customer Data Platform (CDP), named a Leader in the 2026 Gartner® Magic Quadrant™ for Customer Data Platforms, collects behavioral data, resolves identities into unified Customer 360 profiles, builds audiences, syncs to 300+ destinations (including leading ad platforms), and measures campaign impact—directly from your cloud data warehouse. On top of this foundation, Hightouch’s Agentic Marketing Platform uses your complete data and all of the context from your marketing and advertising tools to power true end-to-end lifecycle and performance marketing across paid and owned channels. Purpose-built agents help you go from analyzing campaign performance, to ideating new campaigns, to generating creative, to building segments and cross-channel journeys, to activating audiences and optimization signals back into your ad platforms and downstream tools—often in minutes instead of weeks. Hightouch is built for security, compliance, and scale. Your data stays in your environment—Hightouch never becomes a system of record—and the platform meets SOC 2 Type II, HIPAA, ISO-27001, GDPR, CCPA, and Privacy Shield standards, so even the most regulated organizations can confidently use customer data to power marketing. This approach gives global teams a single, trusted foundation for activation while preserving strong governance, clear audit trails, and regional data residency requirements. **Average Rating:** 4.6/5.0 **Total Reviews:** 392 **How Do G2 Users Rate Hightouch?** - **Data Observability:** 8.4/10 (Category avg: 8.9/10) - **Testing capabilities:** 8.1/10 (Category avg: 8.6/10) - **Ease of Use:** 9.2/10 (Category avg: 9.0/10) - **What is your organization's estimated ROI on the product (payback period in months)?:** 10/10 (Category avg: 10/10) **Who Is the Company Behind Hightouch?** - **Seller:** [Hightouch](https://www.g2.com/sellers/hightouch) - **Company Website:** https://hightouch.com/ - **Year Founded:** 2021 - **HQ Location:** San Francisco, US - **Twitter:** @HightouchData (3,110 Twitter followers) - **LinkedIn® Page:** https://www.linkedin.com/company/hightouchio/ (477 employees on LinkedIn®) **Who Uses This Product?** - **Who Uses This:** Data Engineer, Software Engineer - **Top Industries:** Computer Software, Information Technology and Services - **Company Size:** 63% Mid-Market, 25% Small-Business #### What Are Hightouch's Pros and Cons? **Pros:** - Ease of Use (16 reviews) - Easy Integration (12 reviews) - Customer Support (9 reviews) - Easy Integrations (9 reviews) - Easy Setup (9 reviews) **Cons:** - Expensive (5 reviews) - Pricing Issues (5 reviews) - Integration Issues (4 reviews) - Slow Performance (4 reviews) - Syncing Issues (4 reviews) ### 8. [Y42](https://www.g2.com/products/y42-y42/reviews) Y42’s Turnkey Data Orchestration Platform with embedded Observability gives data practitioners a unified space to reliably build, monitor, and maintain the flow of data to power their business analytics and AI applications. Y42 provides native integration of best-of-breed open-source data tools, comprehensive data governance, and better collaboration for data teams. With Y42, organizations enjoy increased accessibility to data and can make data-driven decisions reliably and efficiently. **Average Rating:** 4.9/5.0 **Total Reviews:** 21 **How Do G2 Users Rate Y42?** - **Data Observability:** 9.2/10 (Category avg: 8.9/10) - **Testing capabilities:** 9.6/10 (Category avg: 8.6/10) - **Ease of Use:** 9.4/10 (Category avg: 9.0/10) - **What is your organization's estimated ROI on the product (payback period in months)?:** 10/10 (Category avg: 10/10) **Who Is the Company Behind Y42?** - **Seller:** [Y42](https://www.g2.com/sellers/y42-f0288f79-5826-460d-ba84-59d0f8b2f3b3) - **Year Founded:** 2020 - **HQ Location:** Berlin, DE - **Twitter:** @y42dotcom (278 Twitter followers) - **LinkedIn® Page:** https://www.linkedin.com/company/64543299 (23 employees on LinkedIn®) **Who Uses This Product?** - **Company Size:** 52% Small-Business, 38% Mid-Market ### 9. [Mozart Data](https://www.g2.com/products/mozart-data-mozart-data/reviews) Backed by award-winning data analyst support, Mozart Data is the fastest way to set up scalable, reliable data infrastructure that doesn’t need to be maintained by you. Mozart Data’s all-in-one modern data platform empowers anyone to easily centralize, organize, and analyze their data without engineering resources. Instead of piecing together multiple tools, companies get everything they need to spin up a data stack in an hour — ETL, a data warehouse, and a data transformation tool — and gain visibility into their data pipelines. Join other data-driven companies, like Zeplin, Rippling, Modern Treasury, and Tempo, that are already getting the most out of their data. Learn more at https://www.mozartdata.com **Average Rating:** 4.6/5.0 **Total Reviews:** 68 **How Do G2 Users Rate Mozart Data?** - **Data Observability:** 8.7/10 (Category avg: 8.9/10) - **Testing capabilities:** 8.0/10 (Category avg: 8.6/10) - **Ease of Use:** 9.3/10 (Category avg: 9.0/10) - **What is your organization's estimated ROI on the product (payback period in months)?:** 10/10 (Category avg: 10/10) **Who Is the Company Behind Mozart Data?** - **Seller:** [Mozart Data](https://www.g2.com/sellers/mozart-data) - **Year Founded:** 2020 - **HQ Location:** San Francisco, US - **Twitter:** @MozartData (447 Twitter followers) - **LinkedIn® Page:** https://www.linkedin.com/company/mozartdata/ (16 employees on LinkedIn®) **Who Uses This Product?** - **Top Industries:** Computer Software, Financial Services - **Company Size:** 53% Small-Business, 47% Mid-Market ## What Is DataOps Platforms? [IT Infrastructure Software](https://www.g2.com/categories/it-infrastructure) ## What Software Categories Are Similar to DataOps Platforms? - [Data Quality Tools](https://www.g2.com/categories/data-quality) - [ETL Tools](https://www.g2.com/categories/etl-tools) - [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) - [Reverse ETL Software](https://www.g2.com/categories/reverse-etl) - [Data Observability Software](https://www.g2.com/categories/data-observability)