Like most companies in general and especially tech startups, HarperDB has overcome many challenges to get to where we are today– which is the most exciting place we’ve been as a company thus far. We’ve learned that we were a couple years too early to market, and that being too early can surprisingly be more difficult than being too late. Over the years, we have explored different solutions and industries to find the right product-market fit, which has been a major roadblock. We learned from and built upon these experiences, for example if we hadn’t ventured into IIoT, HarperDB would not be what it is today in terms of scale and distributed capability. Due to perseverance, we have now positioned HarperDB as the only Globally Distributed Edge Data Platform, providing unprecedented value to our customers through avenues such as Edge Computing, AI/ML, APIs, and third-party integrations.
Considered a lean startup, HarperDB has achieved much more than competitors with much less funding under our belt. With 100K total HarperDB deployments and 10K community members/subscribers, our team continues to expand the product to meet the dynamic needs of our innovative customers. 2022 was HarperDB’s highest year in sales yet, and we expanded our enterprise partnerships and customer base, now working with companies like Lumen, Akamai, Google, Verizon, and Equinix to bring an end-to-end solution to the market.
More Reason to Celebrate
- HarperDB is thrilled to be announced as one of Built in Colorado’s Best Places to Work, ranked at number two on the Best 2023 Startups list. Staying true to our core values as a company, our leadership has ensured that this continues to be a safe, fair, and enjoyable place to work, even through stages of rapid growth.
- HarperDB’s CEO, Stephen Goldberg, was just named the 2023 Bill Daniels Ethical Leader of the Year. Now in its eighth year, the award recognizes local leaders that demonstrate remarkable integrity and ethics in business, exemplifying the ethical principles practiced by cable television pioneer Bill Daniels.
- We just released HarperDB 4.0, which integrates with open-source connectivity platform NATS to enable limitless data distribution. Learn more in this SiliconAngle article.
As we wrap up 2022 and gain momentum for 2023, I sat down with HarperDB’s CEO & Co-Founder, Stephen Goldberg, for a brief Q&A:
What are HarperDB’s current strategic initiatives?
We started the company with the idea of trying to make the easiest database in the world that is also massively scalable. As we evolve, we still want to solve that, but we can also provide a lot of value driving low latency use cases because HarperDB is uniquely positioned as a fully distributed platform that allows for quickly distributing data globally anywhere on earth. So for now we are focused on distributed capabilities as well as performance.
Looking ahead, we will be focused on improving HarperDB as a platform. The product is extremely performant, easy to use, and highly distributable as is, but it could still use work as a platform in making developers’ lives easier so that they can have a global application platform in one place. This ties into edge computing because right now you can have HarperDB anywhere in the world, but in the future, we want that to be an entirely seamless process so that you can deploy globally with the click of a button.
Why is HarperDB focused on Edge Computing and how is the edge helping organizations that we work with?
Originally we were focused on IIoT and IoT, which is actually different from edge computing. IoT is really about the things (devices, etc.) in the field. While HarperDB has the ability to continue playing a role in that, where we can add the most value is at the edge– a step back from IoT. We are taking what is also the cloud and making it more local, closer to the end user, and much more distributed.
We accidentally built the most distributed database in the world that is uniquely horizontally scalable, so we found that our technology is really meaningful in these use cases where it can be deployed anywhere.
Telecom companies for example have noticed that HarperDB can be deployed anywhere in their network and solve a lot of problems around edge computing. Interestingly, people think that 5G makes edge computing easier, but in a lot of ways, it can make it more difficult. A lot of companies are dealing with major congestion issues due to different pipes of data going in and out from the cloud and now to and from the edge. This complex congestion in the data pipeline causes high latency and high cost. Because HarperDB can make your data available at the edge, edge computing can become real. You can build your entire application on HarperDB, so now you really have everything you need, along with the ability to use 5G and other globally distributed infrastructure now available.
What projects are you most excited about right now?
We’ve talked a lot about one of our customers named Edison Interactive. They were struggling with high latency and lack of real-time decision making, and we were able to simplify the transition to a distributed architecture, ultimately reducing latency from 5 seconds down to 20 milliseconds or less. (You can learn more about this case study on our website or on AWS’s blog)
We’re currently exploring similar use cases in industries like gaming, media, manufacturing, oil and gas, etc. Some of this we can’t quite talk about yet, but big things are happening. Overall, I’m not as excited about one specific area as much as being excited about the convergence of all these things and all these ideas that we’ve been talking about for a while finally becoming real.
What are some of the adoption challenges that enterprises face with Edge Computing?
There are some challenges around organizations taking the patterns that they’re comfortable with in the cloud and applying that to the edge. Security is obviously one that can also become interesting. It’s really important to understand that the edge, while similar to cloud, can be quite different.
The biggest challenge with implementing an edge strategy is the interoperability of the different partnerships that you need in place.
AWS made cloud so easy because they have everything you need consolidated into one package. At the edge, there is no dominant player enabling you to put your whole stack in one place, so organizations must put different solutions and partnerships together to achieve their end goal. With HarperDB, one large benefit is that we can run anywhere, on anything, and it doesn’t matter who’s above or below us– you get the same experience anywhere.
Is there space for AI and Machine Learning in Edge Computing? How does it all tie together?
We’re really excited about AI and machine learning (ML) on the edge. We’re already working on some projects in this space, Kevin from our team built a machine learning use case with HarperDB using TensorFlow for a customer. Machine learning is awesome for understanding your data after the fact in the cloud, but at the edge, you can do real-time ML and personalized content experiences and personalized interactions. ML and AI can require huge amounts of compute and huge amounts of data, but if you distribute that, you can do really exciting things such as having human interaction-like levels of data at the edge. By distributing to the edge you reduce the barrier to entry, reduce latency and cost, etc.
How is HarperDB partnering with other organizations to make Edge Computing real?
We’re partnered with Verizon, we worked with them on the Edison use case. Companies like Akamai are helping us distribute our technology globally. HarperDB is also partnering with a lot of cloud providers to run on their edge offerings with Wavelength and MEC (Multi-Access Edge Computing). These partnerships are exciting because to deliver a globally distributed platform, it takes more than just one piece of the puzzle, so these companies allow us to deliver a robust solution to our customers.
Predictions related to Edge, Cloud, and IoT moving forward in the next 5-10 years?
All of these siloed areas are moving towards a more powerful convergence. Machine learning and AI is one discipline, you also have data science, 5G, and different edge offerings. Then there’s a different sector of edge computing without 5G, which is much more distributed using existing technologies like containerization, Kubernetes, and other fabric-level technologies, to create a highly distributed edge. You also have blockchain, and so on. So we have this fairly fragmented set of disciplines which are beginning to converge and overlap. It’s too siloed right now but there is a gravitational pull that’s moving them towards each other.
Once these disciplines become more overlapped, we’ll begin to see more incredible use cases coming to fruition and the future becomes real. You have robotics, real-world human interaction with true AI (not just ML), and personalized interaction. For example, imagine walking into a store or hotel room and the entire experience is tailored to you, autonomous vehicles, etc… All of these different moving parts coming together will make these ambitions real, and it’s exciting, to say the least.
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