# Best Enterprise Data Science and Machine Learning Platforms

## How Many Data Science and Machine Learning Platforms Products Does G2 Track?

**Total Products under this Category:** 1,043

### Category Stats (Aug 2026)

- **Average Rating:** 4.46/5 (↑0.01 vs Jul 2026) The average rating of products in this category, based on all submitted ratings
- **Top Trending Product:** FalkorDB (+5.88%) - Among all products in this category, FalkorDB recorded the largest rating increase compared to last month

_Last updated: August 01, 2026_

## How Does G2 Rank Data Science and Machine Learning Platforms Products?

**Why You Can Trust G2's Software Rankings:**

- 30 Analysts and Data Experts
- 14,200+ Authentic Reviews
- 1,043+ 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.

## G2 Grid® for Data Science and Machine Learning Platforms
 ![G2 Grid® for Data Science and Machine Learning Platforms plotting products by satisfaction and market presence](https://www.g2.com/categories/data-science-and-machine-learning-platforms/grids.png?focus%5B%5D=10470&focus%5B%5D=1327283&focus%5B%5D=21469&focus%5B%5D=7150&focus%5B%5D=989&focus%5B%5D=1308795&focus%5B%5D=24457&focus%5B%5D=52213)

Highlighted products: Databricks, SAS Viya, Gemini Enterprise Agent Platform, Dataiku, Alteryx, IBM watsonx.ai, MATLAB, and Azure Machine Learning.

Underlying data: [Grid® JSON](https://www.g2.com/categories/data-science-and-machine-learning-platforms/grids.json?focus%5B%5D=databricks&focus%5B%5D=sas-sas-viya&focus%5B%5D=gemini-enterprise-agent-platform&focus%5B%5D=dataiku&focus%5B%5D=alteryx&focus%5B%5D=ibm-watsonx-ai&focus%5B%5D=matlab&focus%5B%5D=microsoft-azure-machine-learning&segment=enterprise)

**Sponsored**

### Cloudera

Cloudera is the only hybrid data and AI platform company that large organizations trust to bring AI to their data anywhere it lives. Unlike other providers, Cloudera delivers a consistent cloud experience that converges public clouds, on-prem data centers, and the edge, leveraging a proven open-source foundation. As the pioneer in big data, Cloudera empowers businesses to apply AI and assert control over 100% of their data, in all forms, improving security, governance, and real-time and predictive insights. The world’s largest brands across all industries rely on Cloudera to transform decision-making and ultimately boost bottom lines, safeguard against threats, and save lives. The Cloudera data and AI platform includes: Cloudera AI: Deploy and scale any AI model, anywhere. Cloudera brings compute to governed data where it lives for Private AI anywhere by design. Complete control, security, and governance of mission-critical data, models, agents, and inference ensure faster sovereign AI deployments. Cloudera Data-in-Motion: Make fast decisions from real-time data anywhere. Move data with any structure from any source to any destination seamlessly across hybrid environments, enabling in-the-moment business-critical decisions by processing and analyzing real-time data anywhere, from the edge to AI, as business happens. Cloudera Open Data Lakehouse: Process any data, anywhere, for actionable insights. Make smart decisions with an open data lakehouse powered by Apache Iceberg that delivers trusted, reliable, and unified data to fuel agents, AI applications, and analytics, improving collaboration, breaking silos, and simplifying sharing. Cloudera Unified Data Fabric: Unify security and governance across the entire data estate. Move beyond fragmented data management: Break down silos and connect disparate data sources intelligently and securely to provide a unified view of all organizational data and centralized end-to-end control across complex hybrid data environments.

[Visit website](https://www.g2.com/external_clickthroughs/record?secure%5Bad_program%5D=ppc&secure%5Bad_slot%5D=category_product_list_llm&secure%5Bcategory_id%5D=692&secure%5Bchosen_at%5D=2026-08-05T16%3A52%3A04Z&secure%5Bdisplayable_resource_id%5D=692&secure%5Bdisplayable_resource_type%5D=Category&secure%5Bmedium%5D=sponsored&secure%5Bplacement_reason%5D=page_category&secure%5Bplacement_resource_ids%5D%5B%5D=692&secure%5Bprioritized%5D=false&secure%5Bproduct_id%5D=1886&secure%5Bresource_id%5D=692&secure%5Bresource_type%5D=Category&secure%5Bsource_type%5D=category_page&secure%5Bsource_url%5D=https%3A%2F%2Fwww.g2.com%2Fcategories%2Fdata-science-and-machine-learning-platforms%2Fenterprise&secure%5Btoken%5D=278507373a0f7ef0afdaa4669d4d2488621641ea5f565b69cc85f732ce3840a0&secure%5Burl%5D=https%3A%2F%2Fwww.cloudera.com%2Fproducts%2Fcloudera-data-platform%2Fcdp-demos.html%3Finternal_link%3Dp18%23get-started&secure%5Burl_type%5D=custom_url)

### [Databricks](https://www.g2.com/products/databricks/reviews)

Databricks is the Data and AI company. More than 20,000 organizations worldwide — including adidas, AT&T, Bayer, Block, Mastercard, Rivian, Unilever, and 70% of the Fortune 500 — rely on the Databricks Data + AI Platform to build and scale data and AI apps, analytics, and agents. Headquartered in San Francisco with 30+ offices around the globe, Databricks offers a unified platform that includes Genie, Lakebase, Agent Bricks, Lakeflow, Lakehouse, 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:** 1,330

#### How Do G2 Users Rate Databricks?

- **Application:** 8.7/10 (Category avg: 8.5/10)
- **Managed Service:** 8.5/10 (Category avg: 8.3/10)
- **Natural Language Understanding:** 8.4/10 (Category avg: 8.2/10)
- **Ease of Admin:** 8.4/10 (Category avg: 8.5/10)

#### Who Is the Company Behind Databricks?

- **Seller:** [Databricks Inc.](https://www.g2.com/sellers/databricks-inc)
- **Company Website:** databricks.com
- **Year Founded:** 2013
- **HQ Location:** San Francisco, CA
- **Twitter:** @databricks  
92,269 Twitter followers
- **LinkedIn® Page:** [www.linkedin.com](https://www.g2.com/external_clickthroughs/record?secure%5Bsource_type%5D=product_profile&secure%5Btoken%5D=bddca64732f61b923d96364e8c8eb35711aab4f98797cb00ab071ff24fbdd392&secure%5Burl%5D=https%3A%2F%2Fwww.linkedin.com%2Fcompany%2F3477522%2F&secure%5Burl_type%5D=linkedin_company_website)  
15,627 employees on LinkedIn®

#### Who Uses This Product?

- **Who Uses This:** Data Engineer, Data Analyst
- **Top Industries:** Information Technology and Services, Financial Services
- **Company Size:** 47% Large, 38% Medium

#### What Do G2 Reviewers Say About Databricks?

_AI-generated summary from verified user reviews_

##### Pros

- Users praise the **ease of use** and **comprehensive features** of Databricks for data warehousing and ML applications.
- Users praise the **ease of use** of Databricks, enhancing their experience with intuitive interfaces and reliable services.
- Users appreciate the **seamless integrations** of Databricks with AWS and other tools, enhancing daily operations and efficiency.
- Users value the **seamless collaboration** offered by Databricks, enhancing teamwork on data projects with real-time insights.
- Users praise the **integrated analytical features** of Databricks, enhancing collaborative data processing and insight visualization.

##### Cons

- Users note a **steep learning curve** initially, with confusing permissions and compute modes affecting usability.
- Users note that the **costs can be quite high** for utilizing Databricks effectively, especially for large data projects.
- Users find a **steep learning curve** with Databricks, especially challenging for newcomers to big data tools.
- Users find the **complexity** of Databricks challenging, especially for smaller teams and initial setup processes.
- Users face **complex setup** challenges initially, though support helps simplify the experience over time.

#### What Are Recent G2 Reviews of Databricks?

**["Reliable Platform for Building Scalable Data Pipelines"](https://www.g2.com/survey_responses/databricks-review-13198355)**

**Rating:** 5.0/5.0 stars

_— aravind k._

[Read full review](https://www.g2.com/survey_responses/databricks-review-13198355)

**["Databricks Streamlines ETL and Analytics with Scalable Notebooks"](https://www.g2.com/survey_responses/databricks-review-13181721)**

**Rating:** 5.0/5.0 stars

_— Diana C._

[Read full review](https://www.g2.com/survey_responses/databricks-review-13181721)

#### What Are G2 Users Discussing About Databricks?

- [What does Databricks software do?](https://www.g2.com/discussions/what-does-databricks-software-do) - 3 comments, 1 upvote
- [What is Databricks unified analytics platform?](https://www.g2.com/discussions/what-is-databricks-unified-analytics-platform) - 3 comments
- [What is Lakehouse in Databricks?](https://www.g2.com/discussions/what-is-lakehouse-in-databricks) - 4 comments, 2 upvotes
- [What are the features of Databricks?](https://www.g2.com/discussions/what-are-the-features-of-databricks) - 4 comments, 2 upvotes

### [SAS Viya](https://www.g2.com/products/sas-sas-viya/reviews)

SAS Viya is a cloud-native data and AI platform that enables teams to build, deploy and scale explainable AI that drives trusted, confident decisions. It unites the entire data and AI life cycle and empowers teams to innovate quickly while balancing speed, automation and governance by design. Viya unifies data management, advanced analytics and decisioning in a single platform, so organizations can move from experimentation to production with confidence, delivering measurable business impact that is secure, explainable and scalable across any environment. Key capabilities required to deliver trusted decisions include: • End-to-end clarity across the data and AI life cycle, with built-in lineage, auditability and continuous monitoring to support defensible decisions. • Governance by design, enabling consistent oversight across data, models and decisions to reduce risk and accelerate adoption. • Explainable AI at scale, so insights and outcomes can be understood, validated and trusted by business and regulators alike. • Operationalized analytics, ensuring value continues beyond deployment through monitoring, retraining and life cycle management. • Flexible, cloud-native deployment, allowing organizations to start anywhere and scale everywhere while maintaining control.

**Average Rating:** 4.3/5.0

**Total Reviews:** 774

#### How Do G2 Users Rate SAS Viya?

- **Application:** 7.8/10 (Category avg: 8.5/10)
- **Managed Service:** 7.9/10 (Category avg: 8.3/10)
- **Natural Language Understanding:** 7.8/10 (Category avg: 8.2/10)
- **Ease of Admin:** 7.6/10 (Category avg: 8.5/10)

#### Who Is the Company Behind SAS Viya?

- **Seller:** [SAS Institute Inc.](https://www.g2.com/sellers/sas-institute-inc-df6dde22-a5e5-4913-8b21-4fa0c6c5c7c2)
- **Company Website:** www.sas.com
- **Year Founded:** 1976
- **HQ Location:** Cary, NC
- **Twitter:** @SASsoftware  
60,863 Twitter followers
- **LinkedIn® Page:** [www.linkedin.com](https://www.g2.com/external_clickthroughs/record?secure%5Bsource_type%5D=product_profile&secure%5Btoken%5D=64db42c044af5bbad79bd9677a620a6c31a8ff1abf4e7b2a6f1d6ed9561d105d&secure%5Burl%5D=https%3A%2F%2Fwww.linkedin.com%2Fcompany%2F1491%2F&secure%5Burl_type%5D=linkedin_company_website)  
18,638 employees on LinkedIn®

#### Who Uses This Product?

- **Who Uses This:** Student, Biostatistician
- **Top Industries:** Pharmaceuticals, Banking
- **Company Size:** 33% Large, 33% Small

#### What Do G2 Reviewers Say About SAS Viya?

_AI-generated summary from verified user reviews_

##### Pros

- Users value the **ease of use** of SAS Viya, which simplifies data visualization and enhances decision-making efficiency.
- Users value the **sophisticated analytical capabilities** of SAS Viya, enabling easy deployment and real-time decision-making.
- Users appreciate the **advanced analytical methods** offered by SAS Viya, enhancing decision-making and logistical data analysis capabilities.
- Users value the **end-to-end data lifecycle tooling** of SAS Viya, enhancing business insight and strategic decision-making.
- Users love the **intuitive interface** of SAS Viya, making data analysis and model deployment effortless for all skill levels.

##### Cons

- Users find SAS Viya to have a **learning difficulty** , making it challenging for non-technical individuals to navigate effectively.
- Users find the **learning curve steep** , making it challenging for non-technical users to navigate SAS Viya effectively.
- Users find the **visualization complexity** in SAS Viya challenging, particularly for non-technical users and beginners.
- Users struggle with the **difficult learning curve** of SAS Viya, particularly for new and non-technical users.
- Users find the **expensive pricing** of SAS Viya to be a significant barrier to entry for potential adoption.

#### What Are Recent G2 Reviews of SAS Viya?

**["Effective Data Analysis with SAS Viya"](https://www.g2.com/survey_responses/sas-viya-review-11872818)**

**Rating:** 4.5/5.0 stars

_— Fungai J._

[Read full review](https://www.g2.com/survey_responses/sas-viya-review-11872818)

**["SAS Viya: Powerful AI & Data Analysis with Seamless Integrations"](https://www.g2.com/survey_responses/sas-viya-review-11855145)**

**Rating:** 5.0/5.0 stars

_— Verified User in Hospital & Health Care_

[Read full review](https://www.g2.com/survey_responses/sas-viya-review-11855145)

#### What Are G2 Users Discussing About SAS Viya?

- [What is SAS Visual Data Mining and Machine Learning used for?](https://www.g2.com/discussions/what-is-sas-visual-data-mining-and-machine-learning-used-for) - 2 comments

### [Gemini Enterprise Agent Platform](https://www.g2.com/products/gemini-enterprise-agent-platform/reviews)

Google Cloud's comprehensive platform for developers to build, scale, govern and optimize agents and models. It's a single destination for technical teams to build agents that can transform enterprise applications and workflows into powerful agentic systems.

**Average Rating:** 4.3/5.0

**Total Reviews:** 719

#### How Do G2 Users Rate Gemini Enterprise Agent Platform?

- **Application:** 8.3/10 (Category avg: 8.5/10)
- **Managed Service:** 8.3/10 (Category avg: 8.3/10)
- **Natural Language Understanding:** 8.5/10 (Category avg: 8.2/10)
- **Ease of Admin:** 8.0/10 (Category avg: 8.5/10)

#### Who Is the Company Behind Gemini Enterprise Agent Platform?

- **Seller:** [Google](https://www.g2.com/sellers/google)
- **Year Founded:** 1998
- **HQ Location:** Mountain View, CA
- **Twitter:** @google  
31,899,995 Twitter followers
- **LinkedIn® Page:** [www.linkedin.com](https://www.g2.com/external_clickthroughs/record?secure%5Bsource_type%5D=product_profile&secure%5Btoken%5D=fe4a5936665c9702418dd53c477fef5a7baea08078bb117ed67e966fc581b9ec&secure%5Burl%5D=https%3A%2F%2Fwww.linkedin.com%2Fcompany%2F1441%2F&secure%5Burl_type%5D=linkedin_company_website)  
341,888 employees on LinkedIn®
- **Ownership:** NASDAQ:GOOG

#### Who Uses This Product?

- **Who Uses This:** Software Engineer, Data Scientist
- **Top Industries:** Computer Software, Information Technology and Services
- **Company Size:** 43% Small, 29% Large

#### What Do G2 Reviewers Say About Gemini Enterprise Agent Platform?

_AI-generated summary from verified user reviews_

##### Pros

- Users value the **ease of use** of Gemini Enterprise Agent Platform, enhancing productivity and streamlining workflows effectively.
- Users value the **multimodal capabilities** of Gemini, enhancing productivity and streamlining machine learning workflows effectively.
- Users value the **multimodal capabilities** of Gemini, enhancing productivity through reduced manual work in projects.
- Users value the **multimodal capabilities** of Gemini, enhancing productivity by streamlining various tasks and processes.
- Users value the **integrated platform** of Gemini, enhancing productivity by combining various functionalities in a unified system.

##### Cons

- Users find the **pricing ambiguous** with unexpected costs, making budget management a challenge on the Gemini platform.
- Users find the platform's **complexity** ,particularly in navigation and advanced features, challenging, especially for beginners.
- The **learning curve is steep** for new users, especially with complex features and pricing transparency issues.
- Users find the **complexity issues** of the Gemini Enterprise Agent Platform lead to high costs and a steep learning curve.
- Users find the **difficult learning** curve of Gemini Enterprise Agent Platform challenging, especially for newcomers to Google Cloud.

#### What Are Recent G2 Reviews of Gemini Enterprise Agent Platform?

**["Easy AI Agent Creation"](https://www.g2.com/survey_responses/gemini-enterprise-agent-platform-review-13193916)**

**Rating:** 4.5/5.0 stars

_— Belhaje A._

[Read full review](https://www.g2.com/survey_responses/gemini-enterprise-agent-platform-review-13193916)

**["Helped us automate routine work and save hours every week"](https://www.g2.com/survey_responses/gemini-enterprise-agent-platform-review-13212825)**

**Rating:** 4.5/5.0 stars

_— Pavan Simhadri D._

[Read full review](https://www.g2.com/survey_responses/gemini-enterprise-agent-platform-review-13212825)

#### What Are G2 Users Discussing About Gemini Enterprise Agent Platform?

- [What is Google Cloud AI Platform used for?](https://www.g2.com/discussions/what-is-google-cloud-ai-platform-used-for) - 4 comments, 5 upvotes
- [What software libraries does cloud ML engine support?](https://www.g2.com/discussions/what-software-libraries-does-cloud-ml-engine-support) - 4 comments, 5 upvotes
- [How do I use Google cloud platform for machine learning?](https://www.g2.com/discussions/how-do-i-use-google-cloud-platform-for-machine-learning)
- [Is Google Cloud AI free?](https://www.g2.com/discussions/is-google-cloud-ai-free)
- [What is Google AI platform?](https://www.g2.com/discussions/what-is-google-ai-platform) - 3 comments, 3 upvotes

### [Dataiku](https://www.g2.com/products/dataiku/reviews)

Dataiku is the Platform for AI Success: the AI orchestration layer where enterprises build, deploy, and govern analytics, models, and agents at scale. It sits on top of the data platforms, clouds, and AI services you already use, working across all of them without locking you into any one. Dataiku expands who can build production AI, putting the right tools in the hands of data scientists and domain experts alike, from fraud analysts to demand planners. It orchestrates machine learning, rules, LLMs, and agents as one governed system, built on more than a decade of running production AI. Governance is part of the build rather than something bolted on afterward, so teams ship faster while keeping performance, cost, and risk under control. The result: AI that moves from experimentation to trusted, measurable execution now, not in 18 months.

**Average Rating:** 4.4/5.0

**Total Reviews:** 213

#### How Do G2 Users Rate Dataiku?

- **Application:** 8.3/10 (Category avg: 8.5/10)
- **Managed Service:** 8.2/10 (Category avg: 8.3/10)
- **Natural Language Understanding:** 7.8/10 (Category avg: 8.2/10)
- **Ease of Admin:** 8.0/10 (Category avg: 8.5/10)

#### Who Is the Company Behind Dataiku?

- **Seller:** [Dataiku](https://www.g2.com/sellers/dataiku)
- **Company Website:** Dataiku.com
- **Year Founded:** 2013
- **HQ Location:** New York, NY
- **Twitter:** @dataiku  
22,917 Twitter followers
- **LinkedIn® Page:** [www.linkedin.com](https://www.g2.com/external_clickthroughs/record?secure%5Bsource_type%5D=product_profile&secure%5Btoken%5D=e59ec8fccc02ecc4f883419e54da56d3f6fc8b1e556153f0cc01cd05e3b77faa&secure%5Burl%5D=https%3A%2F%2Fwww.linkedin.com%2Fcompany%2Fdataiku%2F&secure%5Burl_type%5D=linkedin_company_website)  
1,619 employees on LinkedIn®

#### Who Uses This Product?

- **Who Uses This:** Data Scientist, Data Analyst
- **Top Industries:** Financial Services, Pharmaceuticals
- **Company Size:** 60% Large, 22% Medium

#### What Do G2 Reviewers Say About Dataiku?

_AI-generated summary from verified user reviews_

##### Pros

- Users appreciate how Dataiku facilitates **easy ML development** , allowing focus on building models without the complexity.
- Users love the **ease of use** in Dataiku, simplifying complex tasks and enhancing their data analysis experience.
- Users appreciate the **ease of usability** in Dataiku, enabling collaboration for both technical and non-technical users.
- Users appreciate the **easy integrations** of Dataiku, facilitating smooth collaboration and deployment across various analytics tools.
- Users benefit from the **productivity improvement** of Dataiku, enabling faster project development and enhanced career growth.

##### Cons

- Users find the **steep learning curve** of Dataiku challenging, making it tough for beginners to master the platform.
- Users find the **steep learning curve** challenging for beginners, impacting their ability to effectively use Dataiku.
- Users find the **difficult learning** curve challenging, particularly for beginners navigating advanced features.
- Users experience **slow performance** with Dataiku when handling large datasets, affecting efficiency and productivity.
- Users find Dataiku **expensive** , especially for smaller organizations and projects, impacting accessibility and affordability.

#### What Are Recent G2 Reviews of Dataiku?

**["Unified, Low-Code Platform That Boosts End-to-End Data & AI Productivity"](https://www.g2.com/survey_responses/dataiku-review-13125252)**

**Rating:** 4.5/5.0 stars

_— Ravindra N._

[Read full review](https://www.g2.com/survey_responses/dataiku-review-13125252)

**["Build Faster Workflows with Connected Data from many providers or distinct data sources"](https://www.g2.com/survey_responses/dataiku-review-13120436)**

**Rating:** 4.5/5.0 stars

_— Adalberto G._

[Read full review](https://www.g2.com/survey_responses/dataiku-review-13120436)

#### What Are G2 Users Discussing About Dataiku?

- [Is Dataiku an ETL tool?](https://www.g2.com/discussions/is-dataiku-an-etl-tool)
- [Is Dataiku web based?](https://www.g2.com/discussions/is-dataiku-web-based)
- [What is DSS Dataiku?](https://www.g2.com/discussions/what-is-dss-dataiku)
- [What is Dataiku DSS used for?](https://www.g2.com/discussions/what-is-dataiku-dss-used-for)

### [Alteryx](https://www.g2.com/products/alteryx/reviews)

Alteryx, through it's Alteryx One platform, helps enterprises transform complex, disconnected data into a clean, AI-ready state. Whether you’re creating financial forecasts, analyzing supplier performance, segmenting customer data, analyzing employee retention, or building competitive AI applications from your proprietary data, Alteryx One makes it easy to cleanse, blend, and analyze data to unlock the unique insights that drive impactful decisions. AI-Guided Analytics Alteryx automates and simplifies every stage of data preparation and analysis, from validation and enrichment to predictive analytics and automated insights. Incorporate generative AI directly into your workflows to streamline complex data tasks and generate insights faster. Unmatched flexibility, whether you prefer code-free workflows, natural language commands, or low-code options, Alteryx adapts to your needs. Trusted. Secure. Enterprise-Ready. Alteryx is trusted by over half of the Global 2000 and 19 of the top 20 global banks. With built-in automation, governance, and security, your workflows can scale and maintain compliance while delivering consistent results. And it doesn’t matter if your systems are on-premises, hybrid, or in the cloud; Alteryx fits effortlessly into your infrastructure. Easy to Use. Deeply Connected. What truly sets Alteryx apart is our focus on efficiency and ease of use for analysts and our active community of 700,000 Alteryx users to support you at every step of your journey. With seamless integration to data everywhere including platforms like Databricks, Snowflake, AWS, Google, SAP, and Salesforce, our platform helps unify siloed data and accelerate getting to insights. Visit Alteryx.com for more information, and to start your free trial.

**Average Rating:** 4.6/5.0

**Total Reviews:** 857

#### How Do G2 Users Rate Alteryx?

- **Application:** 8.7/10 (Category avg: 8.5/10)
- **Managed Service:** 7.9/10 (Category avg: 8.3/10)
- **Natural Language Understanding:** 7.9/10 (Category avg: 8.2/10)
- **Ease of Admin:** 8.3/10 (Category avg: 8.5/10)

#### Who Is the Company Behind Alteryx?

- **Seller:** [Alteryx](https://www.g2.com/sellers/alteryx)
- **Company Website:** www.alteryx.com
- **Year Founded:** 1997
- **HQ Location:** Irvine, CA
- **Twitter:** @alteryx  
26,149 Twitter followers
- **LinkedIn® Page:** [www.linkedin.com](https://www.g2.com/external_clickthroughs/record?secure%5Bsource_type%5D=product_profile&secure%5Btoken%5D=ae8a7629c5a6d593caff29361a6ee3fb670df11992dd94a9656c66461078b340&secure%5Burl%5D=https%3A%2F%2Fwww.linkedin.com%2Fcompany%2F903031%2F&secure%5Burl_type%5D=linkedin_company_website)  
2,304 employees on LinkedIn®

#### Who Uses This Product?

- **Who Uses This:** Data Analyst, Analyst
- **Top Industries:** Financial Services, Accounting
- **Company Size:** 63% Large, 21% Medium

#### What Do G2 Reviewers Say About Alteryx?

_AI-generated summary from verified user reviews_

##### Pros

- Users appreciate the **ease of use** of Alteryx, finding it user-friendly and efficient for non-technical users.
- Users appreciate the **automation capabilities** of Alteryx, enhancing speed and efficiency in data preparation and analysis.
- Users love the **intuitive design** of Alteryx, making data management and workflow creation effortless and efficient.
- Users find Alteryx to be **very easy to learn and use** , enhancing their data workflow and automation experience.
- Users appreciate the **efficiency** of Alteryx, enabling quick data processing and streamlined workflows without complex coding.

##### Cons

- Users mention that Alteryx has a **high cost** which can be challenging for small teams and startups.
- Users find a **steep learning curve** for advanced features, making it challenging for beginners to master Alteryx quickly.
- Users point out the **missing features** in Alteryx, such as limited connectors and issues with output flexibility.
- Users find **learning difficulty** in Alteryx due to confusing tools and troubleshooting errors, especially for beginners.
- Users encounter **slow performance** when processing large datasets, impacting efficiency and usability in Alteryx.

#### What Are Recent G2 Reviews of Alteryx?

**["Makes Data Prep Faster with an Intuitive Drag-and-Drop Workflow"](https://www.g2.com/survey_responses/alteryx-review-13190742)**

**Rating:** 4.5/5.0 stars

_— Anushka S._

[Read full review](https://www.g2.com/survey_responses/alteryx-review-13190742)

**["Scales Operations and Saves Time with Automated Data Workflows"](https://www.g2.com/survey_responses/alteryx-review-13047637)**

**Rating:** 4.5/5.0 stars

_— Ihor B._

[Read full review](https://www.g2.com/survey_responses/alteryx-review-13047637)

### [IBM watsonx.ai](https://www.g2.com/fr/products/ibm-watsonx-ai/reviews)

Watsonx.ai fait partie de la plateforme IBM watsonx qui réunit de nouvelles capacités d'IA générative, alimentées par des modèles de base et l'apprentissage automatique traditionnel dans un studio puissant couvrant le cycle de vie de l'IA. Avec watsonx.ai, vous pouvez construire, entraîner, valider, ajuster et déployer des capacités d'IA générative, des modèles de base et d'apprentissage automatique avec facilité et créer des applications d'IA en une fraction du temps avec une fraction des données.

**Average Rating:** 4.4/5.0

**Total Reviews:** 139

#### How Do G2 Users Rate IBM watsonx.ai?

- **Application:** 8.8/10 (Category avg: 8.5/10)
- **Service géré:** 8.5/10 (Category avg: 8.3/10)
- **Compréhension du langage naturel:** 8.6/10 (Category avg: 8.2/10)
- **Facilité d’administration:** 8.5/10 (Category avg: 8.5/10)

#### Who Is the Company Behind IBM watsonx.ai?

- **Vendeur:** [IBM](https://www.g2.com/fr/sellers/ibm)
- **Site Web de l'entreprise:** www.ibm.com
- **Année de fondation:** 1911
- **Emplacement du siège social:** Armonk, New York, United States
- **Twitter:** @IBMSecurity  
74,660 abonnés Twitter
- **Page LinkedIn®:** [www.linkedin.com](https://www.g2.com/fr/external_clickthroughs/record?secure%5Bsource_type%5D=product_profile&secure%5Btoken%5D=14b544adaece4fdbc987f1d7f7028048c22259946811200cc751263825586af9&secure%5Burl%5D=https%3A%2F%2Fwww.linkedin.com%2Fcompany%2F1009%2F&secure%5Burl_type%5D=linkedin_company_website)  
328,202 employés sur LinkedIn®

#### Who Uses This Product?

- **Who Uses This:** Consultant
- **Top Industries:** Technologie de l'information et services, Logiciels informatiques
- **Company Size:** 41% Small, 32% Large

#### What Do G2 Reviewers Say About IBM watsonx.ai?

_AI-generated summary from verified user reviews_

##### Pros

- Les utilisateurs apprécient la **facilité d'utilisation** d'IBM watsonx.ai, facilitant une intégration plus rapide de l'IA et une gestion efficace.
- Les utilisateurs apprécient la **variété de modèles** d'IBM watsonx.ai, permettant un entraînement personnalisé sur des modèles existants pour une performance améliorée.
- Les utilisateurs apprécient **l'intégration transparente de l'IA de niveau entreprise** dans IBM watsonx.ai, améliorant la prise de décision et l'efficacité des flux de travail.
- Les utilisateurs apprécient le **studio intégré de qualité entreprise** d'IBM watsonx.ai pour une formation en IA sans faille et des informations fiables.
- Les utilisateurs apprécient l' **intégration IA de niveau entreprise** d'IBM watsonx.ai, améliorant la prise de décision et les opérations commerciales de manière efficace.

##### Cons

- Les utilisateurs trouvent la **courbe d'apprentissage difficile** d'IBM watsonx.ai intimidante, ce qui la rend moins accessible pour les nouveaux venus et les petites équipes.
- Les utilisateurs trouvent la **configuration complexe** d'IBM watsonx.ai difficile, ce qui la rend moins adaptée aux petites équipes et aux débutants.
- Les utilisateurs trouvent la **courbe d'apprentissage abrupte** d'IBM watsonx.ai difficile, ce qui le rend moins accessible pour les équipes non techniques.
- Les utilisateurs trouvent le produit **cher** et difficile pour les petites équipes, citant des coûts élevés et des exigences de configuration complexes.
- Les utilisateurs trouvent la **configuration complexe** d'IBM watsonx.ai difficile, surtout pour les débutants et les petites équipes.

#### What Are Recent G2 Reviews of IBM watsonx.ai?

**["Studio d'IA unifié et gouverné avec des performances solides et des intégrations IBM transparentes"](https://www.g2.com/fr/survey_responses/ibm-watsonx-ai-review-13184421)**

**Rating:** 4.0/5.0 stars

_— Manan S._

[Read full review](https://www.g2.com/fr/survey_responses/ibm-watsonx-ai-review-13184421)

**["Plateforme complète tout-en-un pour construire et tester des flux de travail d'IA"](https://www.g2.com/fr/survey_responses/ibm-watsonx-ai-review-13196706)**

**Rating:** 4.0/5.0 stars

_— Manish D._

[Read full review](https://www.g2.com/fr/survey_responses/ibm-watsonx-ai-review-13196706)

### [MATLAB](https://www.g2.com/products/matlab/reviews)

MATLAB is a high-level programming and numeric computing environment widely utilized by engineers and scientists for data analysis, algorithm development, and system modeling. It offers a desktop environment optimized for iterative analysis and design processes, coupled with a programming language that directly expresses matrix and array mathematics. The Live Editor feature enables users to create scripts that integrate code, output, and formatted text within an executable notebook. Key Features and Functionality: - Data Analysis: Tools for exploring, modeling, and analyzing data. - Graphics: Functions for visualizing and exploring data through various plots and charts. - Programming: Capabilities to create scripts, functions, and classes for customized workflows. - App Building: Facilities to develop desktop and web applications. - External Language Interfaces: Integration with languages such as Python, C/C++, Fortran, and Java. - Hardware Connectivity: Support for connecting MATLAB to various hardware platforms. - Parallel Computing: Ability to perform large-scale computations and parallelize simulations using multicore desktops, GPUs, clusters, and cloud resources. - Deployment: Options to share MATLAB programs and deploy them to enterprise applications, embedded devices, and cloud environments. Primary Value and User Solutions: MATLAB streamlines complex mathematical computations and data analysis tasks, enabling users to develop algorithms and models efficiently. Its comprehensive toolboxes and interactive apps facilitate rapid prototyping and iterative design, reducing development time. The platform's scalability allows for seamless transition from research to production, supporting deployment on various systems without extensive code modifications. By integrating with multiple programming languages and hardware platforms, MATLAB provides a versatile environment that addresses the diverse needs of engineers and scientists across industries.

**Average Rating:** 4.5/5.0

**Total Reviews:** 750

#### How Do G2 Users Rate MATLAB?

- **Application:** 8.6/10 (Category avg: 8.5/10)
- **Managed Service:** 8.3/10 (Category avg: 8.3/10)
- **Natural Language Understanding:** 8.5/10 (Category avg: 8.2/10)
- **Ease of Admin:** 8.4/10 (Category avg: 8.5/10)

#### Who Is the Company Behind MATLAB?

- **Seller:** [MathWorks](https://www.g2.com/sellers/mathworks)
- **Year Founded:** 1984
- **HQ Location:** Natick, MA
- **Twitter:** @MATLAB  
105,142 Twitter followers
- **LinkedIn® Page:** [www.linkedin.com](https://www.g2.com/external_clickthroughs/record?secure%5Bsource_type%5D=product_profile&secure%5Btoken%5D=6dbb518e9679f4f3158244b1c49a1caf60257ab06a669303d999c534715b2674&secure%5Burl%5D=https%3A%2F%2Fwww.linkedin.com%2Fcompany%2F1194036%2F&secure%5Burl_type%5D=linkedin_company_website)  
7,985 employees on LinkedIn®

#### Who Uses This Product?

- **Who Uses This:** Student, Graduate Research Assistant
- **Top Industries:** Higher Education, Research
- **Company Size:** 42% Large, 31% Small

#### What Do G2 Reviewers Say About MATLAB?

_AI-generated summary from verified user reviews_

##### Pros

- Users find MATLAB's **ease of use** remarkable, enabling intuitive data analysis, visualization, and application development seamlessly.
- Users admire MATLAB for its **powerful data analysis and visualization tools** , enabling impactful and professional presentation of results.
- Users highlight MATLAB's **excellent visualization tools** , allowing for clear and professional presentations of complex data.
- Users value the **rich variety of toolboxes** in MATLAB, enhancing efficiency and confidence in their engineering tasks.
- Users appreciate MATLAB for its **powerful simulation capabilities** and seamless transition from ideas to practical solutions.

##### Cons

- Users find MATLAB to be **expensive** , particularly due to high licensing costs and additional toolboxes for functionality.
- Users experience **slow performance** with MATLAB, particularly on less powerful machines, impacting their productivity during complex tasks.
- Users note the **high system requirements** of MATLAB, leading to slower performance on less powerful machines.
- Users struggle with **expensive licensing** costs for MATLAB, posing a barrier for individuals and small companies.
- Users experience **lagging performance** during high resource usage, affecting efficiency and requiring improvements for better usability.

#### What Are Recent G2 Reviews of MATLAB?

**["Powerful Math and Visualization Tools That Boost Productivity"](https://www.g2.com/survey_responses/matlab-review-12811316)**

**Rating:** 5.0/5.0 stars

_— Dipendu M._

[Read full review](https://www.g2.com/survey_responses/matlab-review-12811316)

**["A Robust Powerhouse for Advanced Engineering Simulations and Modeling"](https://www.g2.com/survey_responses/matlab-review-12689149)**

**Rating:** 4.0/5.0 stars

_— Wafa M._

[Read full review](https://www.g2.com/survey_responses/matlab-review-12689149)

#### What Are G2 Users Discussing About MATLAB?

- [What is MATLAB used for?](https://www.g2.com/discussions/what-is-matlab-used-for) - 1 comment
- [Can I use Matlab for free?](https://www.g2.com/discussions/can-i-use-matlab-for-free) - 3 comments
- [What is Matlab written in?](https://www.g2.com/discussions/what-is-matlab-written-in) - 1 comment
- [Is Matlab a programming language or software?](https://www.g2.com/discussions/is-matlab-a-programming-language-or-software) - 1 comment
- [What is Matlab software used for?](https://www.g2.com/discussions/what-is-matlab-software-used-for) - 1 comment

### [Azure Machine Learning](https://www.g2.com/products/microsoft-azure-machine-learning/reviews)

Azure Machine Learning is an enterprise-grade service that facilitates the end-to-end machine learning lifecycle, enabling data scientists and developers to build, train, and deploy models efficiently. Key Features and Functionality: - Data Preparation: Quickly iterate data preparation on Apache Spark clusters within Azure Machine Learning, interoperable with Microsoft Fabric. - Feature Store: Increase agility in shipping your models by making features discoverable and reusable across workspaces. - AI Infrastructure: Take advantage of purpose-built AI infrastructure uniquely designed to combine the latest GPUs and InfiniBand networking. - Automated Machine Learning: Rapidly create accurate machine learning models for tasks including classification, regression, vision, and natural language processing. - Responsible AI: Build responsible AI solutions with interpretability capabilities. Assess model fairness through disparity metrics and mitigate unfairness. - Model Catalog: Discover, fine-tune, and deploy foundation models from Microsoft, OpenAI, Hugging Face, Meta, Cohere, and more using the model catalog. - Prompt Flow: Design, construct, evaluate, and deploy language model workflows with prompt flow. - Managed Endpoints: Operationalize model deployment and scoring, log metrics, and perform safe model rollouts. Primary Value and Solutions Provided: Azure Machine Learning accelerates time to value by streamlining prompt engineering and machine learning model workflows, facilitating faster model development with powerful AI infrastructure. It streamlines operations by enabling reproducible end-to-end pipelines and automating workflows with continuous integration and continuous delivery (CI/CD). The platform ensures confidence in development through unified data and AI governance with built-in security and compliance, allowing compute to run anywhere for hybrid machine learning. Additionally, it promotes responsible AI by providing visibility into models, evaluating language model workflows, and mitigating fairness, biases, and harm with built-in safety systems.

**Average Rating:** 4.3/5.0

**Total Reviews:** 87

#### How Do G2 Users Rate Azure Machine Learning?

- **Application:** 8.8/10 (Category avg: 8.5/10)
- **Managed Service:** 8.9/10 (Category avg: 8.3/10)
- **Natural Language Understanding:** 8.7/10 (Category avg: 8.2/10)
- **Ease of Admin:** 8.3/10 (Category avg: 8.5/10)

#### Who Is the Company Behind Azure Machine Learning?

- **Seller:** [Microsoft](https://www.g2.com/sellers/microsoft)
- **Year Founded:** 1975
- **HQ Location:** Redmond, Washington
- **Twitter:** @microsoft  
13,091,739 Twitter followers
- **LinkedIn® Page:** [www.linkedin.com](https://www.g2.com/external_clickthroughs/record?secure%5Bsource_type%5D=product_profile&secure%5Btoken%5D=9458f51bd6ded48ad432a804f19ad736469f007787569b63827154231c315630&secure%5Burl%5D=https%3A%2F%2Fwww.linkedin.com%2Fcompany%2Fmicrosoft%2F&secure%5Burl_type%5D=linkedin_company_website)  
231,632 employees on LinkedIn®
- **Ownership:** MSFT

#### Who Uses This Product?

- **Who Uses This:** Software Engineer
- **Top Industries:** Information Technology and Services, Computer Software
- **Company Size:** 40% Large, 33% Small

#### What Do G2 Reviewers Say About Azure Machine Learning?

_AI-generated summary from verified user reviews_

##### Pros

- Users find Azure Machine Learning to be **easy to use** , facilitating seamless data management and model implementation.
- Users appreciate the **scalability and integration** of Azure Machine Learning, enhancing AI deployment across various applications.
- Users appreciate the **excellent customer support** of Azure Machine Learning, with helpful documentation and community assistance available.
- Users appreciate the **ease of use and rich features** of Azure Machine Learning for effective data management.
- Users appreciate the **efficiency** of Azure Machine Learning for launching and monitoring jobs seamlessly, enhancing productivity.

##### Cons

- Users find the **learning curve challenging** , requiring time and effort to navigate the platform's tools effectively.
- Users find Azure Machine Learning's **difficult navigation** frustrating due to its disordered interface and non-intuitive workflows.
- Users find the **user interface disorganized** , leading to confusion and excessive clicking to locate options.
- Users find the **complex interface** of Azure Machine Learning non-intuitive, complicating their workflow and experience.
- Users face a **difficult learning curve** with Azure Machine Learning, especially if they are new to the platform.

#### What Are Recent G2 Reviews of Azure Machine Learning?

**["An Enterprise-Grade Way to Operationalize ML"](https://www.g2.com/survey_responses/azure-machine-learning-review-12853548)**

**Rating:** 4.0/5.0 stars

_— Vytas J._

[Read full review](https://www.g2.com/survey_responses/azure-machine-learning-review-12853548)

**["Cost-Efficient Medical Data Integration Backed by Great Support"](https://www.g2.com/survey_responses/azure-machine-learning-review-12845990)**

**Rating:** 5.0/5.0 stars

_— Giridharan U._

[Read full review](https://www.g2.com/survey_responses/azure-machine-learning-review-12845990)

#### What Are G2 Users Discussing About Azure Machine Learning?

- [What is Azure Machine Learning Studio used for?](https://www.g2.com/discussions/what-is-azure-machine-learning-studio-used-for) - 1 comment
- [What type of data analysis is azure machine learning studio intended for?](https://www.g2.com/discussions/what-type-of-data-analysis-is-azure-machine-learning-studio-intended-for)
- [What are the key features of Azure Machine Learning?](https://www.g2.com/discussions/what-are-the-key-features-of-azure-machine-learning)
- [How do I use Microsoft Azure for machine learning?](https://www.g2.com/discussions/how-do-i-use-microsoft-azure-for-machine-learning)
- [What is Azure Machine Learning Studio?](https://www.g2.com/discussions/what-is-azure-machine-learning-studio)

### [IBM watsonx.data](https://www.g2.com/products/ibm-watsonx-data/reviews)

IBM® watsonx.data® helps you access, integrate and understand all your data —structured and unstructured—across any environment. It optimizes workloads for price and performance while enforcing consistent governance across sources, formats and teams. Watch the demo to learn how watsonx.data empowers you to build gen AI apps and powerful AI agents. Free Trial available: https://ibm.biz/Watsonx-data\_Trial

**Average Rating:** 4.4/5.0

**Total Reviews:** 167

#### How Do G2 Users Rate IBM watsonx.data?

- **Application:** 5.8/10 (Category avg: 8.5/10)
- **Managed Service:** 7.2/10 (Category avg: 8.3/10)
- **Natural Language Understanding:** 8.0/10 (Category avg: 8.2/10)
- **Ease of Admin:** 7.9/10 (Category avg: 8.5/10)

#### Who Is the Company Behind IBM watsonx.data?

- **Seller:** [IBM](https://www.g2.com/sellers/ibm)
- **Company Website:** www.ibm.com
- **Year Founded:** 1911
- **HQ Location:** Armonk, New York, United States
- **Twitter:** @IBMSecurity  
74,660 Twitter followers
- **LinkedIn® Page:** [www.linkedin.com](https://www.g2.com/external_clickthroughs/record?secure%5Bsource_type%5D=product_profile&secure%5Btoken%5D=14b544adaece4fdbc987f1d7f7028048c22259946811200cc751263825586af9&secure%5Burl%5D=https%3A%2F%2Fwww.linkedin.com%2Fcompany%2F1009%2F&secure%5Burl_type%5D=linkedin_company_website)  
328,202 employees on LinkedIn®

#### Who Uses This Product?

- **Who Uses This:** Software Engineer, CEO
- **Top Industries:** Information Technology and Services, Computer Software
- **Company Size:** 34% Small, 32% Large

#### What Do G2 Reviewers Say About IBM watsonx.data?

_AI-generated summary from verified user reviews_

##### Pros

- Users appreciate the **ease of use** of IBM watsonx.data, finding it reliable and efficient for data management tasks.
- Users value the **organized data integration** and intuitive interface of IBM watsonx.data, enhancing efficiency and analytics.
- Users value the **organized and efficient data management** of IBM watsonx.data, enhancing analytics and reporting tasks seamlessly.
- Users value the **seamless data source integration** in IBM watsonx.data, enhancing flexibility and efficiency for diverse projects.
- Users value the **ability to unify data across hybrid environments** , enhancing flexibility and driving informed decision-making.

##### Cons

- Users find the **learning curve steep** , making initial setup and navigation challenging for newcomers to IBM watsonx.data.
- Users find the **complexity** of setting up IBM watsonx.data a barrier, especially for newcomers to IBM technologies.
- Users find the **pricing steep** for IBM watsonx.data, making it less accessible for smaller businesses and projects.
- Users find the **difficult setup** of IBM watsonx.data time-consuming, with a steep learning curve and complex configurations.
- Users find IBM watsonx.data **difficult to navigate** , especially for beginners and those unfamiliar with AI and data analytics.

#### What Are Recent G2 Reviews of IBM watsonx.data?

**["Clean, Smooth UI with Excellent Onboarding and Infrastructure Visuals"](https://www.g2.com/survey_responses/ibm-watsonx-data-review-13204444)**

**Rating:** 4.0/5.0 stars

_— Aliasgar B._

[Read full review](https://www.g2.com/survey_responses/ibm-watsonx-data-review-13204444)

**["Powerful Query Performance and Governance, But a Steep Onboarding Learning Curve"](https://www.g2.com/survey_responses/ibm-watsonx-data-review-12836202)**

**Rating:** 4.0/5.0 stars

_— Arkajit D._

[Read full review](https://www.g2.com/survey_responses/ibm-watsonx-data-review-12836202)

### [Amazon SageMaker](https://www.g2.com/products/amazon-sagemaker/reviews)

Amazon SageMaker is a fully managed service that enables data scientists and developers to build, train, and deploy machine learning (ML) models at scale. It provides a comprehensive suite of tools and infrastructure, streamlining the entire ML workflow from data preparation to model deployment. With SageMaker, users can quickly connect to training data, select and optimize algorithms, and deploy models in a secure and scalable environment. Key Features and Functionality: - Integrated Development Environments (IDEs): SageMaker offers a unified, web-based interface with built-in IDEs, including JupyterLab and RStudio, facilitating seamless development and collaboration. - Pre-built Algorithms and Frameworks: It includes a selection of optimized ML algorithms and supports popular frameworks like TensorFlow, PyTorch, and Apache MXNet, allowing flexibility in model development. - Automated Model Tuning: SageMaker can automatically tune models to achieve optimal accuracy, reducing the time and effort required for manual adjustments. - Scalable Training and Deployment: The service manages the underlying infrastructure, enabling efficient training of models on large datasets and deploying them across auto-scaling clusters for high availability. - MLOps and Governance: SageMaker provides tools for monitoring, debugging, and managing ML models, ensuring robust operations and compliance with enterprise security standards. Primary Value and Problem Solved: Amazon SageMaker addresses the complexity and resource-intensive nature of developing and deploying ML models. By offering a fully managed environment with integrated tools and scalable infrastructure, it accelerates the ML lifecycle, reduces operational overhead, and enables organizations to derive insights and value from their data more efficiently. This empowers businesses to innovate rapidly and implement AI solutions without the need for extensive in-house expertise or infrastructure management.

**Average Rating:** 4.3/5.0

**Total Reviews:** 54

#### How Do G2 Users Rate Amazon SageMaker?

- **Application:** 8.6/10 (Category avg: 8.5/10)
- **Managed Service:** 9.1/10 (Category avg: 8.3/10)
- **Natural Language Understanding:** 9.3/10 (Category avg: 8.2/10)
- **Ease of Admin:** 8.4/10 (Category avg: 8.5/10)

#### Who Is the Company Behind Amazon SageMaker?

- **Seller:** [Amazon Web Services (AWS)](https://www.g2.com/sellers/amazon-web-services-aws-3e93cc28-2e9b-4961-b258-c6ce0feec7dd)
- **Year Founded:** 2006
- **HQ Location:** Seattle, WA
- **Twitter:** @awscloud  
2,232,483 Twitter followers
- **LinkedIn® Page:** [www.linkedin.com](https://www.g2.com/external_clickthroughs/record?secure%5Bsource_type%5D=product_profile&secure%5Btoken%5D=072881eee28a2afe24f8d1bda9f20e3e146b9fb4b214f216411ce2ed6898b31e&secure%5Burl%5D=https%3A%2F%2Fwww.linkedin.com%2Fcompany%2Famazon-web-services%2F&secure%5Burl_type%5D=linkedin_company_website)  
147,094 employees on LinkedIn®
- **Ownership:** NASDAQ: AMZN

#### Who Uses This Product?

- **Top Industries:** Information Technology and Services, Computer Software
- **Company Size:** 33% Medium, 33% Large

#### What Do G2 Reviewers Say About Amazon SageMaker?

_AI-generated summary from verified user reviews_

##### Pros

- Users find Amazon SageMaker's **ease of use** exceptional, enabling quick adaptation and efficient model training with user-friendly features.
- Users appreciate the **seamless AI integration** of Amazon SageMaker, enhancing the efficiency of the machine learning lifecycle.
- Users appreciate the **superior computing power** of Amazon SageMaker, significantly reducing model training time and enhancing efficiency.
- Users value the **exceptional efficiency** of Amazon SageMaker, significantly reducing model training time and streamlining workflows.
- Users commend the **fast processing** capabilities of Amazon SageMaker, significantly reducing model training time and enhancing usability.

##### Cons

- Users find Amazon SageMaker **expensive** , with complex pricing that leads to unexpected costs for training and deployments.
- Users find the **pricing structure complex** and often face high costs with long training jobs and deployments.
- Users find that the **complexity of pricing** in Amazon SageMaker can lead to unexpected costs and confusion.
- Users note a **steep learning curve** with Amazon SageMaker, particularly for those new to AWS services and setups.
- Users experience a **difficult learning curve** during the initial setup of Amazon SageMaker, which can hinder productivity.

#### What Are Recent G2 Reviews of Amazon SageMaker?

**["End-to-End ML Platform That Streamlines the Full Lifecycle"](https://www.g2.com/survey_responses/amazon-sagemaker-review-13180609)**

**Rating:** 4.5/5.0 stars

_— Atharva P._

[Read full review](https://www.g2.com/survey_responses/amazon-sagemaker-review-13180609)

**["Fully Managed End-to-End ML in AWS with Powerful Distributed Training"](https://www.g2.com/survey_responses/amazon-sagemaker-review-12853074)**

**Rating:** 4.0/5.0 stars

_— Hem J._

[Read full review](https://www.g2.com/survey_responses/amazon-sagemaker-review-12853074)

#### What Are G2 Users Discussing About Amazon SageMaker?

- [What is Amazon SageMaker used for?](https://www.g2.com/discussions/what-is-amazon-sagemaker-used-for)
- [Is AWS SageMaker good?](https://www.g2.com/discussions/is-aws-sagemaker-good) - 1 upvote
- [Who uses SageMaker?](https://www.g2.com/discussions/who-uses-sagemaker)
- [How do you use Amazon SageMaker?](https://www.g2.com/discussions/how-do-you-use-amazon-sagemaker)
- [What does Amazon SageMaker do?](https://www.g2.com/discussions/what-does-amazon-sagemaker-do)

### [Snowflake](https://www.g2.com/products/snowflake/reviews)

Snowflake makes enterprise AI easy, efficient and trusted. Thousands of companies around the globe, including hundreds of the world’s largest, use Snowflake’s AI Data Cloud to share data, build applications, and power their business with AI. The era of enterprise AI is here. Learn more at snowflake.com (NYSE: SNOW).

**Average Rating:** 4.5/5.0

**Total Reviews:** 712

#### How Do G2 Users Rate Snowflake?

- **Application:** 9.2/10 (Category avg: 8.5/10)
- **Managed Service:** 9.0/10 (Category avg: 8.3/10)
- **Natural Language Understanding:** 8.6/10 (Category avg: 8.2/10)
- **Ease of Admin:** 8.7/10 (Category avg: 8.5/10)

#### Who Is the Company Behind Snowflake?

- **Seller:** [Snowflake, Inc.](https://www.g2.com/sellers/snowflake-inc)
- **Company Website:** www.snowflake.com
- **Year Founded:** 2012
- **HQ Location:** 135 Constitution Drive, Menlo Park CA
- **Twitter:** @SnowflakeDB  
278 Twitter followers
- **LinkedIn® Page:** [www.linkedin.com](https://www.g2.com/external_clickthroughs/record?secure%5Bsource_type%5D=product_profile&secure%5Btoken%5D=ad18ff73a9b8bb34dd1b98a6ba1c6be57f7364939ad352612ecc483aba05d2b2&secure%5Burl%5D=https%3A%2F%2Fwww.linkedin.com%2Fcompany%2Fsnowflake-computing%2F&secure%5Burl_type%5D=linkedin_company_website)  
11,308 employees on LinkedIn®

#### Who Uses This Product?

- **Who Uses This:** Data Engineer, Data Analyst
- **Top Industries:** Information Technology and Services, Computer Software
- **Company Size:** 45% Medium, 43% Large

#### What Do G2 Reviewers Say About Snowflake?

_AI-generated summary from verified user reviews_

##### Pros

- Users appreciate the **ease of use** of Snowflake, finding it fast and effective for data sharing and analytics.
- Users value the **reliable features** of Snowflake, enjoying its intuitive interface and seamless data integration for analytics.
- Users find Snowflake's **data management capabilities** excellent for efficiently aggregating and querying across multiple datasets.
- Users admire the **seamless scalability** of Snowflake, effortlessly accommodating work demands and ensuring optimal performance.
- Users appreciate the **fast data analysis** of Snowflake, enabling quick insights without infrastructure worries.

##### Cons

- Users find Snowflake's **high costs** burdensome, especially for small businesses with limited budgets.
- Users find **feature limitations** in Snowflake, such as lack of code blocks and challenge in permissions management.
- Users find that **cost management** requires discipline, as unexpected charges can accumulate quickly without careful monitoring.
- Users find the **cost structure difficult to optimize** , leading to unexpectedly high initial expenses during implementation.
- Users find Snowflake's **limited features** in dynamic scripts and monitoring hinder flexibility and usability.

#### What Are Recent G2 Reviews of Snowflake?

**["Elastic Scaling and Fast Analytics with Snowflake"](https://www.g2.com/survey_responses/snowflake-review-13129003)**

**Rating:** 4.5/5.0 stars

_— Ravindra N._

[Read full review](https://www.g2.com/survey_responses/snowflake-review-13129003)

**["Snowflake Simplifies Data Management at Scale"](https://www.g2.com/survey_responses/snowflake-review-12898129)**

**Rating:** 4.0/5.0 stars

_— Harshil A._

[Read full review](https://www.g2.com/survey_responses/snowflake-review-12898129)

#### What Are G2 Users Discussing About Snowflake?

- [What is Snowflake used for?](https://www.g2.com/discussions/what-is-snowflake-used-for) - 2 comments, 1 upvote

### [Teradata Autonomous Knowledge Platform](https://www.g2.com/products/teradata-autonomous-knowledge-platform/reviews)

Teradata Autonomous Knowledge Platform activates enterprise intelligence by unifying data, knowledge and business context to achieve tangible outcomes. With Teradata, organizations can provide agents with full context for impact when it matters. Our solution lets businesses connect and scale on premises, in the cloud, or through a hybrid approach. Teradata delivers real business value with AI. Learn more at Teradata.com.

**Average Rating:** 4.3/5.0

**Total Reviews:** 356

#### How Do G2 Users Rate Teradata Autonomous Knowledge Platform?

- **Application:** 8.3/10 (Category avg: 8.5/10)
- **Managed Service:** 8.3/10 (Category avg: 8.3/10)
- **Natural Language Understanding:** 7.9/10 (Category avg: 8.2/10)
- **Ease of Admin:** 8.0/10 (Category avg: 8.5/10)

#### Who Is the Company Behind Teradata Autonomous Knowledge Platform?

- **Seller:** [Teradata Autonomous Knowledge Platform](https://www.g2.com/sellers/teradata-autonomous-knowledge-platform)
- **Year Founded:** 1979
- **HQ Location:** San Diego, CA
- **Twitter:** @Teradata  
93,113 Twitter followers
- **LinkedIn® Page:** [www.linkedin.com](https://www.g2.com/external_clickthroughs/record?secure%5Bsource_type%5D=product_profile&secure%5Btoken%5D=06895b9a8db4fa478ba7da480ccd214a14ef698abd028e4642e62f189e82b650&secure%5Burl%5D=https%3A%2F%2Fwww.linkedin.com%2Fcompany%2F1466%2F&secure%5Burl_type%5D=linkedin_company_website)  
9,941 employees on LinkedIn®
- **Ownership:** NYSE:TDC

#### Who Uses This Product?

- **Who Uses This:** Data Engineer, Software Engineer
- **Top Industries:** Information Technology and Services, Financial Services
- **Company Size:** 69% Large, 22% Medium

#### What Do G2 Reviewers Say About Teradata Autonomous Knowledge Platform?

_AI-generated summary from verified user reviews_

##### Pros

- Users highlight the **extreme performance** of the Teradata Autonomous Knowledge Platform, especially for processing large data volumes efficiently.
- Users value the **high performance query execution** in Teradata, enhancing their business analytics capabilities significantly.
- Users value the **scalability** of Teradata Autonomous Knowledge Platform, enhancing data integration and operational efficiency significantly.
- Users commend the **high performance and speed** of Teradata, efficiently processing large datasets without issues.
- Users value the **fast processing of large datasets** with Teradata, praising its performance and stability during operations.

##### Cons

- Users find the **steep learning curve** of Teradata Autonomous Knowledge Platform challenging, impacting adoption and productivity temporarily.
- Users find the **steep learning curve** of Teradata Autonomous Knowledge Platform challenging, particularly for those lacking technical expertise.
- Users find the **complexity** of Teradata's platform challenging, particularly for non-technical users and new adopters.
- Users express concerns over the **cost management requirements** needed to avoid potential misusage and performance issues.
- Users feel the **high cost** of Teradata Autonomous Knowledge Platform is a significant drawback affecting accessibility.

#### What Are Recent G2 Reviews of Teradata Autonomous Knowledge Platform?

**["Teradata Vantage Fast Query Performance and Strong Analytics for Big Data"](https://www.g2.com/survey_responses/teradata-autonomous-knowledge-platform-review-12821668)**

**Rating:** 5.0/5.0 stars

_— Muzammil M._

[Read full review](https://www.g2.com/survey_responses/teradata-autonomous-knowledge-platform-review-12821668)

**["Teradata Vantage Excels at Big Data Processing and Advanced Analytics"](https://www.g2.com/survey_responses/teradata-autonomous-knowledge-platform-review-12739181)**

**Rating:** 4.5/5.0 stars

_— Nijat I._

[Read full review](https://www.g2.com/survey_responses/teradata-autonomous-knowledge-platform-review-12739181)

#### What Are G2 Users Discussing About Teradata Autonomous Knowledge Platform?

- [What does Teradata Data Lab do?](https://www.g2.com/discussions/what-does-teradata-data-lab-do)
- [Is Teradata a premiership?](https://www.g2.com/discussions/is-teradata-a-premiership)
- [What is Teradata Vantage?](https://www.g2.com/discussions/what-is-teradata-vantage)
- [How much does Teradata cost?](https://www.g2.com/discussions/how-much-does-teradata-cost)
- [What is Sandbox in Teradata?](https://www.g2.com/discussions/what-is-sandbox-in-teradata)

### [Deep Learning VM Image](https://www.g2.com/products/deep-learning-vm-image/reviews)

Deep Learning VM Images are pre-configured virtual machine images optimized for data science and machine learning tasks. These images come with essential machine learning frameworks and tools pre-installed, enabling users to deploy and scale machine learning models efficiently on Google Cloud's infrastructure. Key Features and Functionality: - Pre-installed Frameworks: Support for TensorFlow Enterprise, TensorFlow, PyTorch, and generic high-performance computing, catering to various machine learning needs. - Operating System Options: Based on Debian 11 and Ubuntu 22.04, providing flexibility and compatibility with different environments. - Comprehensive Python Environment: Includes Python 3.10 with a suite of libraries such as NumPy, SciPy, Matplotlib, Pandas, NLTK, Pillow, scikit-image, OpenCV, and scikit-learn, facilitating a robust development experience. - JupyterLab Integration: Offers JupyterLab notebook environments for rapid prototyping and interactive development. - GPU Acceleration: Equipped with the latest NVIDIA drivers and packages, including CUDA 11.x and 12.x, CuDNN, and NCCL, to leverage GPU capabilities for accelerated computation. Primary Value and User Solutions: Deep Learning VM Images streamline the setup process for machine learning projects by providing ready-to-use environments with pre-installed frameworks and tools. This reduces the time and effort required for configuration, allowing data scientists and machine learning practitioners to focus on model development and experimentation. The integration with Google Cloud's scalable infrastructure ensures that users can efficiently manage and scale their machine learning workloads, whether they require CPU or GPU resources. Regular updates and community support further enhance the reliability and performance of these VM images, making them a valuable resource for accelerating machine learning initiatives.

**Average Rating:** 4.4/5.0

**Total Reviews:** 52

#### How Do G2 Users Rate Deep Learning VM Image?

- **Application:** 8.8/10 (Category avg: 8.5/10)
- **Managed Service:** 8.4/10 (Category avg: 8.3/10)
- **Natural Language Understanding:** 8.5/10 (Category avg: 8.2/10)
- **Ease of Admin:** 8.8/10 (Category avg: 8.5/10)

#### Who Is the Company Behind Deep Learning VM Image?

- **Seller:** [Google](https://www.g2.com/sellers/google)
- **Year Founded:** 1998
- **HQ Location:** Mountain View, CA
- **Twitter:** @google  
31,899,995 Twitter followers
- **LinkedIn® Page:** [www.linkedin.com](https://www.g2.com/external_clickthroughs/record?secure%5Bsource_type%5D=product_profile&secure%5Btoken%5D=fe4a5936665c9702418dd53c477fef5a7baea08078bb117ed67e966fc581b9ec&secure%5Burl%5D=https%3A%2F%2Fwww.linkedin.com%2Fcompany%2F1441%2F&secure%5Burl_type%5D=linkedin_company_website)  
341,888 employees on LinkedIn®
- **Ownership:** NASDAQ:GOOG

#### Who Uses This Product?

- **Top Industries:** Information Technology and Services, Computer Software
- **Company Size:** 47% Small, 33% Medium

#### What Do G2 Reviewers Say About Deep Learning VM Image?

_AI-generated summary from verified user reviews_

##### Pros

- Users value the **pre-installed ML frameworks and tools** of Deep Learning VM Image, enhancing efficiency in projects.
- Users love the **ease of use** of Deep Learning VM Image, enabling quick deployment and seamless integration.
- Users value the **easy integrations with cloud services** , which streamline deployment and enhance productivity seamlessly.
- Users benefit from the **fast processing** capabilities of Deep Learning VM Image, enhancing efficiency in deep learning projects.
- Users benefit from the **exceptional speed** of Deep Learning VM Image, significantly accelerating data processing and workflow efficiency.

##### Cons

- Users find the **costs can escalate** with frequent usage, leading to concerns about affordability over time.
- Users express concerns about **high costs** associated with usage, which can escalate for larger-scale operations.
- Users face **high computational costs** and latency issues with Deep Learning VM Image, impacting overall performance and expenses.
- Users find the **steep learning curve** challenging, making it difficult for beginners to navigate the Deep Learning VM Image.
- Users report a **steep learning curve** that can overwhelm new users and hinder effective use of Deep Learning VM Image.

#### What Are Recent G2 Reviews of Deep Learning VM Image?

**["Preconfigured GPU AI Environment That Speeds Up Deep Learning on Google Cloud"](https://www.g2.com/survey_responses/deep-learning-vm-image-review-13155676)**

**Rating:** 4.5/5.0 stars

_— LOKESH G._

[Read full review](https://www.g2.com/survey_responses/deep-learning-vm-image-review-13155676)

**["Ready to Use Deep Learning Environment That Saves Time"](https://www.g2.com/survey_responses/deep-learning-vm-image-review-13206817)**

**Rating:** 4.5/5.0 stars

_— Sattwik M._

[Read full review](https://www.g2.com/survey_responses/deep-learning-vm-image-review-13206817)

### [IBM Decision Optimization](https://www.g2.com/products/ibm-decision-optimization/reviews)

IBM Decision Optimization is a family of prescriptive analytics products that combines mathematical and AI techniques to help with business decision-making including operational, tactical and strategic planning and scheduling use cases. The solutions enable business decision-makers to choose the optimal course of action from millions of alternatives when faced with decisions that involve multiple variables, trade-off possibilities and complex constraints. The solution incorporates powerful optimization solvers namely CPLEX Optimizer and CP Optimizer to solve the breadth of optimization problems including mathematical and constraint programming and constraint-based scheduling models. Learn more about this portfolio here https://www.ibm.com/analytics/decision-optimization IBM ILOG CPLEX Optimization Studio is one of the products within the IBM Decision Optimization portfolio. Organizations across industries are using IBM ILOG CPLEX Optimization Studio to drive operational efficiency and generate significant ROI by optimizing planning, scheduling, pricing and other business decisions. The offering provides users the flexibility to develop optimization models either using general programming language APIs like Python, Java, or using Optimization Programming Language (OPL). The powerful CPLEX optimization engines can deliver the power necessary to solve very large, real- world optimization problems at the speed required for today’s interactive decision optimization applications. Learn more about this product here - https://www.ibm.com/products/ilog-cplex-optimization-studio IBM Decision Optimization is also included within Watson Studio Premium for Cloud Pak for Data to enable data science teams to capitalize on the power of prescriptive analytics and build innovative solutions using a combination of techniques like machine learning and optimization. Data science teams can easily demonstrate business value of optimization by leveraging tools like visual dashboards & modeling assistant to quickly build models, test/evaluate multiple scenarios, solve using powerful optimization engines and deploy the models easily . IBM Decision Optimization solutions bring more than 30 years of experience in the field and is a proven optimization technology and organizations across industries are using IBM Decision Optimization solutions to run their mission-critical decision-making applications and have benefited by way of reduction in operating costs, increase in revenue and accelerated time to value.

**Average Rating:** 4.5/5.0

**Total Reviews:** 35

#### How Do G2 Users Rate IBM Decision Optimization?

- **Application:** 8.3/10 (Category avg: 8.5/10)
- **Managed Service:** 8.3/10 (Category avg: 8.3/10)
- **Natural Language Understanding:** 7.3/10 (Category avg: 8.2/10)
- **Ease of Admin:** 8.7/10 (Category avg: 8.5/10)

#### Who Is the Company Behind IBM Decision Optimization?

- **Seller:** [IBM](https://www.g2.com/sellers/ibm)
- **Year Founded:** 1911
- **HQ Location:** Armonk, New York, United States
- **Twitter:** @IBMSecurity  
74,660 Twitter followers
- **LinkedIn® Page:** [www.linkedin.com](https://www.g2.com/external_clickthroughs/record?secure%5Bsource_type%5D=product_profile&secure%5Btoken%5D=14b544adaece4fdbc987f1d7f7028048c22259946811200cc751263825586af9&secure%5Burl%5D=https%3A%2F%2Fwww.linkedin.com%2Fcompany%2F1009%2F&secure%5Burl_type%5D=linkedin_company_website)  
328,202 employees on LinkedIn®
- **Ownership:** SWX:IBM

#### Who Uses This Product?

- **Top Industries:** Computer Software, Financial Services
- **Company Size:** 59% Large, 22% Small

#### What Are Recent G2 Reviews of IBM Decision Optimization?

**["leveraging data resources"](https://www.g2.com/survey_responses/ibm-decision-optimization-review-8714924)**

**Rating:** 4.5/5.0 stars

_— James C._

[Read full review](https://www.g2.com/survey_responses/ibm-decision-optimization-review-8714924)

**["In-depth analytics.. for a price."](https://www.g2.com/survey_responses/ibm-decision-optimization-review-8681163)**

**Rating:** 4.5/5.0 stars

_— Andrew M._

[Read full review](https://www.g2.com/survey_responses/ibm-decision-optimization-review-8681163)

#### What Are G2 Users Discussing About IBM Decision Optimization?

- [What is IBM Decision Optimization used for?](https://www.g2.com/discussions/what-is-ibm-decision-optimization-used-for)
- [What is IBM ILOG cplex optimization studio?](https://www.g2.com/discussions/what-is-ibm-ilog-cplex-optimization-studio)
- [Which IBM offering would be considered best for Prescriptive Analytics?](https://www.g2.com/discussions/which-ibm-offering-would-be-considered-best-for-prescriptive-analytics)
- [What is decision optimization?](https://www.g2.com/discussions/what-is-decision-optimization)
- [What is IBM decision optimization?](https://www.g2.com/discussions/what-is-ibm-decision-optimization)

### [Posit Team](https://www.g2.com/products/posit-team/reviews)

Posit is a Public Benefit Corporation building open-source software and an enterprise data science platform. We created the RStudio IDE, Shiny, Positron, and Quarto — tools used by millions of data scientists, machine learning engineers, and researchers worldwide, including teams at 25% of the Fortune Global 100. Our commercial products help organizations put those tools into production: Posit Workbench provides centralized development environments supporting Positron, RStudio, VS Code, and Jupyter; Posit Connect handles publishing and deployment for Shiny, AI applications, Streamlit, Dash, FastAPI, Flask, Bokeh, and more; and Posit Package Manager provides security-compliant package management for R and Python.

**Average Rating:** 4.5/5.0

**Total Reviews:** 567

#### How Do G2 Users Rate Posit Team?

- **Application:** 8.4/10 (Category avg: 8.5/10)
- **Managed Service:** 8.3/10 (Category avg: 8.3/10)
- **Natural Language Understanding:** 8.6/10 (Category avg: 8.2/10)
- **Ease of Admin:** 8.3/10 (Category avg: 8.5/10)

#### Who Is the Company Behind Posit Team?

- **Seller:** [Posit](https://www.g2.com/sellers/posit)
- **Year Founded:** 2009
- **HQ Location:** Boston, US
- **Twitter:** @posit\_pbc  
120,874 Twitter followers
- **LinkedIn® Page:** [www.linkedin.com](https://www.g2.com/external_clickthroughs/record?secure%5Bsource_type%5D=product_profile&secure%5Btoken%5D=291e2e1530a4de1dc8ce16ea96948375d8dd3891a186f3101d5f2b110c8b2509&secure%5Burl%5D=https%3A%2F%2Fwww.linkedin.com%2Fcompany%2F1978648%2F&secure%5Burl_type%5D=linkedin_company_website)  
442 employees on LinkedIn®

#### Who Uses This Product?

- **Who Uses This:** Research Assistant, Graduate Research Assistant
- **Top Industries:** Higher Education, Information Technology and Services
- **Company Size:** 48% Large, 26% Medium

#### What Do G2 Reviewers Say About Posit Team?

_AI-generated summary from verified user reviews_

##### Pros

- Users find Posit to be **highly user-friendly** , enabling efficient analysis and simplifying integration with existing tools.
- Users appreciate Posit's **leadership in innovation** and seamless integration, enhancing their productivity and workflow efficiency.
- Users value Posit's **commitment to open source software** , enhancing accessibility and integration for R programming.
- Users value the **responsive customer support** of Posit Team, enhancing their experience with excellent guidance and assistance.
- Users appreciate the **easy integrations** of Posit Team, allowing seamless workflow and reducing setup complications.

##### Cons

- Users experience **slow performance** when handling large datasets, disrupting workflow and requiring significant system resources.
- Users experience a **steep learning curve** with Posit Team, making initial setup and advanced features challenging.
- Users experience **performance issues** with Posit, particularly when handling larger datasets and during high usage.
- Users face a **steep learning curve** with Posit Team, making initial setup and advanced features challenging for newcomers.
- Users experience **lagging performance** with Posit, particularly when handling large datasets, impacting overall productivity.

#### What Are Recent G2 Reviews of Posit Team?

**["Posit Team Makes Biostatistical Work Reproducible, Collaborative, and Secure"](https://www.g2.com/survey_responses/posit-team-review-12977958)**

**Rating:** 5.0/5.0 stars

_— Donald S._

[Read full review](https://www.g2.com/survey_responses/posit-team-review-12977958)

**["Exceptional Open-Source Data Science Tools with Great Documentation and R/Python Support"](https://www.g2.com/survey_responses/posit-team-review-13022732)**

**Rating:** 5.0/5.0 stars

_— Omer F. Y._

[Read full review](https://www.g2.com/survey_responses/posit-team-review-13022732)

#### What Are G2 Users Discussing About Posit Team?

- [What is the difference between RStudio desktop and Rstudio server?](https://www.g2.com/discussions/what-is-the-difference-between-rstudio-desktop-and-rstudio-server)
- [What is the difference between R and R studio?](https://www.g2.com/discussions/what-is-the-difference-between-r-and-r-studio)
- [Is R Studio free?](https://www.g2.com/discussions/is-r-studio-free)
- [Which software is used for R programming?](https://www.g2.com/discussions/which-software-is-used-for-r-programming) - 1 comment

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