Should I Build It Should I Build It
20 Apr 2025
Developer Tools

Microerp system which is heavily customisable and easily deployable on ...

...cloud with new data ase architecture which uses olap database instead of oltp

Confidence
Engagement
Net use signal
Net buy signal

Idea type: Freemium

People love using similar products but resist paying. You’ll need to either find who will pay or create additional value that’s worth paying for.

Should You Build It?

Build but think about differentiation and monetization.

Your are here

You're venturing into the MicroERP space, focusing on customization and cloud deployment with a unique OLAP database architecture. This places you in the 'Freemium' category. The existence of 4 similar products suggests medium competition, so differentiation will be key. With an average of 6 comments across similar product launches indicating a medium level of engagement, this shows there is interest but you should prioritize strong communication and iteration based on feedback. Your challenge will be converting enthusiastic users of your free version into paying customers. To succeed, you'll need to identify the core value drivers of your MicroERP system and how you can offer premium features that provide tangible benefits that will justify your target users to pay.

Recommendations

  1. Start by identifying your ideal customer profile. Who needs a highly customizable, easily deployable MicroERP system? Focus on specific industries or company sizes where your OLAP database architecture offers a clear advantage over traditional OLTP systems. This targeted approach will help you refine your marketing and sales efforts.
  2. Given that you're in the Freemium category, identify which users get the most value from the free version of your MicroERP. Understand their pain points and usage patterns. This information will be crucial for designing premium features that directly address their needs and encourage them to upgrade.
  3. Following up from that, create premium features that offer significant value to your high-value free users. Think about advanced analytics, custom reporting, integrations with other business tools, or priority support. These features should directly address the needs of your target users and provide a clear incentive for them to upgrade.
  4. Consider focusing on charging teams or organizations rather than individual users. Larger entities are often more willing to pay for software solutions that streamline their operations and provide advanced capabilities. Offering team-based pricing can also increase your revenue potential and encourage broader adoption of your MicroERP system.
  5. Offer personalized help or consulting services to premium users. This can include onboarding assistance, custom configuration, or ongoing support. Providing personalized support can significantly enhance customer satisfaction and retention, as well as justify a higher price point.
  6. Based on the criticism from similar products, you need to offer clear documentation and onboarding for your users. Many potential customers might have questions, and addressing them through FAQs, clear and searchable documentation and well-maintained knowledge-bases is critical. This creates trust between you and your customers and reduces friction.
  7. Finally, test different pricing approaches with small groups of users. This will allow you to gather data on price sensitivity and optimize your pricing strategy. Experiment with different pricing tiers, feature bundles, and payment options to find the most effective approach for your target market.

Questions

  1. What specific performance benefits does your OLAP database architecture provide compared to traditional OLTP systems in a MicroERP context, and how can you quantify these benefits for potential customers?
  2. Considering the competitive landscape, what unique features or integrations can you offer that will differentiate your MicroERP system from existing solutions and justify a premium price point?
  3. How will you balance the features offered in the free version of your MicroERP system with the premium features, ensuring that the free version is valuable enough to attract users while still incentivizing them to upgrade?

Your are here

You're venturing into the MicroERP space, focusing on customization and cloud deployment with a unique OLAP database architecture. This places you in the 'Freemium' category. The existence of 4 similar products suggests medium competition, so differentiation will be key. With an average of 6 comments across similar product launches indicating a medium level of engagement, this shows there is interest but you should prioritize strong communication and iteration based on feedback. Your challenge will be converting enthusiastic users of your free version into paying customers. To succeed, you'll need to identify the core value drivers of your MicroERP system and how you can offer premium features that provide tangible benefits that will justify your target users to pay.

Recommendations

  1. Start by identifying your ideal customer profile. Who needs a highly customizable, easily deployable MicroERP system? Focus on specific industries or company sizes where your OLAP database architecture offers a clear advantage over traditional OLTP systems. This targeted approach will help you refine your marketing and sales efforts.
  2. Given that you're in the Freemium category, identify which users get the most value from the free version of your MicroERP. Understand their pain points and usage patterns. This information will be crucial for designing premium features that directly address their needs and encourage them to upgrade.
  3. Following up from that, create premium features that offer significant value to your high-value free users. Think about advanced analytics, custom reporting, integrations with other business tools, or priority support. These features should directly address the needs of your target users and provide a clear incentive for them to upgrade.
  4. Consider focusing on charging teams or organizations rather than individual users. Larger entities are often more willing to pay for software solutions that streamline their operations and provide advanced capabilities. Offering team-based pricing can also increase your revenue potential and encourage broader adoption of your MicroERP system.
  5. Offer personalized help or consulting services to premium users. This can include onboarding assistance, custom configuration, or ongoing support. Providing personalized support can significantly enhance customer satisfaction and retention, as well as justify a higher price point.
  6. Based on the criticism from similar products, you need to offer clear documentation and onboarding for your users. Many potential customers might have questions, and addressing them through FAQs, clear and searchable documentation and well-maintained knowledge-bases is critical. This creates trust between you and your customers and reduces friction.
  7. Finally, test different pricing approaches with small groups of users. This will allow you to gather data on price sensitivity and optimize your pricing strategy. Experiment with different pricing tiers, feature bundles, and payment options to find the most effective approach for your target market.

Questions

  1. What specific performance benefits does your OLAP database architecture provide compared to traditional OLTP systems in a MicroERP context, and how can you quantify these benefits for potential customers?
  2. Considering the competitive landscape, what unique features or integrations can you offer that will differentiate your MicroERP system from existing solutions and justify a premium price point?
  3. How will you balance the features offered in the free version of your MicroERP system with the premium features, ensuring that the free version is valuable enough to attract users while still incentivizing them to upgrade?

  • Confidence: Medium
    • Number of similar products: 4
  • Engagement: Medium
    • Average number of comments: 6
  • Net use signal: 15.7%
    • Positive use signal: 19.6%
    • Negative use signal: 3.9%
  • Net buy signal: -3.9%
    • Positive buy signal: 0.0%
    • Negative buy signal: 3.9%

This chart summarizes all the similar products we found for your idea in a single plot.

The x-axis represents the overall feedback each product received. This is calculated from the net use and buy signals that were expressed in the comments. The maximum is +1, which means all comments (across all similar products) were positive, expressed a willingness to use & buy said product. The minimum is -1 and it means the exact opposite.

The y-axis captures the strength of the signal, i.e. how many people commented and how does this rank against other products in this category. The maximum is +1, which means these products were the most liked, upvoted and talked about launches recently. The minimum is 0, meaning zero engagement or feedback was received.

The sizes of the product dots are determined by the relevance to your idea, where 10 is the maximum.

Your idea is the big blueish dot, which should lie somewhere in the polygon defined by these products. It can be off-center because we use custom weighting to summarize these metrics.

Similar products

Relevance

VulcanSQL – Serve high-concurrency, low-latency API from OLAP

05 Jul 2023 Database API Developer Tools

Hi HN,I wanted to share an exciting new open-source project: "VulcanSQL"! If you're interested in seamlessly transitioning your operational and analytical use cases from data warehouses and databases to the edge API server, this open-source data API framework might be just what you're looking for.VulcanSQL (https://vulcansql.com/) is suitable for following use cases:* Customer-facing analytics - expose analytics in your SaaS product for customers to understand how the product is performing for them via customer dashboards, insights, and reports.* Data Sharing - sharing data with partners, vendors, or customers, which requires a secure and scalable way to expose data.* Internal tools - Integration with internal tools like Retools.it leverages the impressive capabilities of DuckDB as a caching layer. This combination brings about cost reduction and a significant boost in performance, making it an excellent choice for high-concurrency, low-latency scenarios that OLAP not suitable for.By utilizing VulcanSQL, you can move remote data computing in cloud data warehouses, such as Snowflake and BigQuery to the edge. This embedded approach ensures that your analytics and automation processes can be executed efficiently and seamlessly, even in resource-constrained environments.GitHub: https://github.com/Canner/vulcan-sql

Users are questioning how the product differs from cube.dev and expressing concerns about redundancy due to ClickHouse's capabilities.

Users question the product's differentiation and find it redundant given the presence of ClickHouse.

Avatar
8
2
-50.0%
-50.0%
2
8
Relevance

MotherDuck – a serverless data analytics platform powered by DuckDB

22 Jun 2023 Developer Tools

Hi folks.. Co-founder and Head of Produck at MotherDuck. We're building a new type of analytics data platform based on an exciting open source project DuckDB!We just launched today, so please head over to our website and request an invite[0]!When we first started MotherDuck a little over a year ago, we realized that the modern data platforms like BigQuery and Snowflake are of exceptional quality. They're also very mature, packing diverse set of features across a variety of use cases. So it doesn't seem like a good idea to go and compete with them...But then we found DuckDB. DuckDB changes everything - suddenly virtually any CPU in virtually any place and on any environment can be used for analytics. You can run DuckDB in the browser or a Lambda, in Python or R, in the cloud or on your laptop. Suddenly the modern cloud data warehouse looks a lot like a black-box mainframe in the cloud.So we bet big on DuckDB. We invented a new way[1] to take OSS to market - we struck an exclusive cloud partnership with the DuckDB team, and we're working in close collaboration on a common goal.We've built a serverless cloud analytics service - a place for you to store your data, query that data in SQL, share and collaborate, and leverage MotherDuck using a plethora of third party tools like dbt, HEX, and cloudquery.However, we did something very unique again - and something that's only possible with DuckDB. For any DuckDB instance out there, you can simply run '.open md:', and your DuckDB instance is suddenly supercharged by MotherDuck - you get additional capabilities like faster secure access to S3 and sharing, and you get a new type of query execution we're calling 'hybrid mode', in which your DuckDB instance is working in concert with MotherDuck-hosted DuckDB instances to execute queries in concert on data wherever it lives. In short, we intelligently route stages of queries to the right location, enabling things like seamlessly joining data on your laptop with data on S3.We've also built a web application with a catalog and a SQL IDE. We put DuckDB in our app using WASM, so we're able to cache query results and provide a low-latency interactive query results explorer so that you can sort, filter, and even pivot your data at the speed of thought.We're currently Beta, so we're slowly accepting users from the waitlist. We plan on marching towards GA and could use your help in finding out where we can improve![0] https://motherduck.com/[1] https://www.madrona.com/motherduck-jordan-tigani-duckdbs-hannes-muhleisen-partnerships-commercializing-open-source-projects/

Users are excited about the news and congratulate the DuckDB team. They are particularly enthusiastic about the ability to run both local and remote queries.

Avatar
17
2
50.0%
2
17
50.0%
Relevance

MotherDuck - Now GA: the ducking simple analytics data warehouse

12 Jun 2024 Data & Analytics Database Developer Tools

The cloud SQL analytics platform that helps you do more with your data. A unique architecture enables dual query execution across local machines and the cloud, letting you experience smooth workflows and ultra-efficient performance that won’t break the bank.

MotherDuck's Product Hunt launch garnered positive feedback, with users expressing excitement about its cloud SQL analytics, innovative data infrastructure, and simplified data management. The platform's ability to blend local and cloud queries, along with its unique UI, was well-received. Questions were raised regarding plan structure, data consistency, latency management, ideal customer profiles, and future evolution. Users also appreciated the smooth workflows and efficient performance enabled by dual query execution, as well as the potential cost savings from local queries. One user suggested custom architecture and microchip development for the future.

Users criticized the difficulty in finding plan structures, needing clear directions for navigation. Another concern raised was about the product's ability to scale with large datasets while maintaining performance.

Avatar
293
19
21.1%
19
293
21.1%
Top