Velvet
4.64
0
Velvet unifies data for teams, enabling real-time queries, AI analysis, and collaborative visualizations from unlimited sources.
What is Velvet?
Velvet is a unified data platform designed to support product and engineering teams at high-growth startups. It allows users to perform complex SQL queries, leverage AI for parsing large data sets, and collaborate by turning queries into interactive visuals such as tables, graphs, and alerts accessible to the entire team. Velvet offers functionality such as real-time data through query API endpoints and the capacity to store unlimited data from various sources like databases, third-party tools, and events. The platform assists in shipping real-time features, capturing real-time data, and tracking data movement over time. By facilitating data transformation, enabling collaboration, and providing AI assistance for analysis, Velvet optimizes data workflows and product development processes.
Who created Velvet?
Velvet was created by a team associated with the platform, and its launch date was December 6, 2023. The platform was designed to support product and engineering teams at high-growth startups by enabling users to perform complex SQL queries, leverage AI for parsing large data sets, collaborate effectively, and visualize data for the entire team. Velvet offers features such as real-time data utilization, query API endpoints for storing unlimited data, and capabilities for team members to act as data engineers.
What is Velvet used for?
- Product development - writing and executing complex SQL queries, parsing large data volumes with AI, capturing real-time data, transforming queries into tables, graphs, or alerts, and shipping real-time, data-driven product features.
- Data workflow optimization
- Real-time feature shipping
- Data collaboration support
- Analysis of AI features - evaluating costs, usage, and performance of models, features, and versions
- Data visualization - turning queries into visual forms like tables and graphs
- Data transformation - querying disparate data sources, shipping real-time features, modifying data workflow
- Cross-source data queries support
- Data analysis from third-party tools and events
- Parsing large amounts of data with AI
- Performing complex SQL queries
- Parsing large data volumes using AI
- Capturing real-time data from various sources
- Transforming queries into tables, graphs, or alerts
- Shipping real-time, data-driven product features
- Accelerating development workflows
- Analyzing data from third-party tools and events
- Using AI to parse vast amounts of data
- Facilitating data transformation
- Supporting collaboration of data engineering
Who is Velvet for?
- Software engineers
- Data engineers
- Product Managers
How to use Velvet?
To use Velvet for your data needs, follow these steps:
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Complex SQL Queries: Write and execute complex SQL queries with Velvet.
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AI Data Parsing: Utilize AI to parse large data volumes efficiently.
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Real-Time Data Capture: Capture real-time data from various sources for dynamic insights.
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Data Transformation: Transform queries into tables, graphs, or alerts for visualization.
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Collaboration and Workflow: Collaborate effectively by sharing visualized data insights across the team.
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Query API Endpoints: Save queries as API endpoints for quick and easy access to relevant data.
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Data Analysis: Analyze data from third-party tools and events for comprehensive insights.
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Unified Data Platform: Benefit from a unified platform that streamlines data access and workflow optimization.
By following these steps, you can unlock the full potential of Velvet in enhancing your data analysis and product development processes.
Pros
- Transforms team into data engineers
- Enables data query from disparate sources
- Offers real-time feature shipping
- Allows complex SQL writing
- Facilitates large data parsing
- Turns queries into visual data
- Data stored as query API endpoints
- Supports real-time data for product development
- Permits ingestion of any data source
- Allows access to queries as API endpoints
Cons
- Limited to high-growth startups
- No explicit support for non-SQL languages
- Real-time data might affect performance
- Possible user overwhelm with unlimited data
- Could favor tech-savvy users
- No offline mode mentioned
Velvet FAQs
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How does Velvet transform all team members into data engineers?
- Velvet empowers all team members to act as data engineers by enabling them to query disparate data sources, utilize real-time data to develop features, and fine-tune their team's data workflow.
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What kind of data can Velvet store?
- Velvet has the capacity to store unlimited data and capture real-time data from various sources such as your own database, third-party tools, and events.
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What functionalities does the AI sidekick in Velvet provide?
- The AI sidekick in Velvet facilitates users to execute complex queries across all data and helps in producing visualizations that track data movement over time.
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How can Velvet aid in shipping real-time features?
- Velvet aids in shipping real-time features by enabling users to use real-time data for building features and guide product development workflows.
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Can Velvet help in improving my team's data collaboration?
- Yes, Velvet can enhance a team's data collaboration by transforming complex queries into accessible tables, graphs, and alerts, fostering a culture of data-driven collaboration.
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Is Velvet suitable for all types of startups?
- Yes, Velvet is crafted for high-growth startups but its features such as real-time data transformation make it beneficial for a variety of startup types.
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How does Velvet facilitate data transformation?
- Velvet facilitates data transformation by enabling users to query disparate data sources, ship real-time features, and modify their team's data workflow.
Get started with Velvet
Velvet reviews
Elena Petrov
February 16, 2025
What do you like most about using Velvet?
I love how Velvet brings together data from multiple sources seamlessly. The ability to perform complex SQL queries and visualize the results in real-time is a game-changer for our team.
What do you dislike most about using Velvet?
The initial learning curve can be a bit steep, especially for team members who are not familiar with SQL or data analysis.
What problems does Velvet help you solve, and how does this benefit you?
Velvet helps us streamline our data workflows. By having real-time access to data from various sources, we can make informed decisions quickly, which is essential for our product development process.
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Jasper Nguyen
February 7, 2025
What do you like most about using Velvet?
The AI-driven analysis features are remarkable! They allow us to gain insights from large datasets without needing extensive data science expertise.
What do you dislike most about using Velvet?
Sometimes, the platform can be slow when pulling data from multiple sources, especially during peak hours.
What problems does Velvet help you solve, and how does this benefit you?
Velvet helps us efficiently track data movement and visualize trends over time, making it easier for our teams to monitor product performance and user engagement.
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Sofia Almeida
February 15, 2025
What do you like most about using Velvet?
I appreciate the collaborative aspect of Velvet. Being able to share visualizations and insights with my team enhances our discussions and decision-making.
What do you dislike most about using Velvet?
The customization options for visualizations are somewhat limited; I would love more flexibility in how I present data.
What problems does Velvet help you solve, and how does this benefit you?
Velvet has significantly improved our team's data accessibility. We can quickly analyze performance metrics, which helps us iterate on our products more effectively.
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