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Timeplus Journey to Open Source Part II: How We Got Here

Updated: Oct 4

When we came out of stealth in March 2022, I shared my thoughts on why we founded Timeplus. I described the core market problem as “the whole data process - from ingestion to analytics - just isn’t designed for real-time streaming.” There are good individual tools and frameworks to build stream processing and analytics, but no singular platform that deliver on the promise of:


1) Unified streaming and historical analytics

2) Low latency

3) Ease-of-use


We went to market with the promise of providing “fast, powerful and intuitive” real-time analytics. Our hypotheses were that “faster companies win,” and that matching low-latency stream processing with powerful, easy-to-use functionality would be a winning combination for developers.


Were we right?


Generally, yes. Developers do want low-latency, and they do need powerful functionality to complete their most complex tasks. But I think we misunderstood where the real customer pain point was at first. The promise of better performance is really just table stakes.


There are a multitude of “single use” data infrastructure vendors competing for their slice of the market. Many of them also promise better performance than established industry frameworks, but their products only solve a narrow part of engineers’ problems. Working with “single use” infrastructure introduces layers of complexity and redundancy.


So how are we differentiated in this sea of vendors? Through customer feedback, we realized our real strength was the ability to simplify the building and operationalizing of streaming processing and analytics without sacrificing performance or functionality and bringing complexities. And by unification and simplifying, we eliminate the need for “single use” data infrastructure.


Developers value Timeplus because we enable simplicity in execution, with a single SQL query, a single platform, and a single binary from which to observe and take action on your data. Our developer community is finding unique value from Timeplus through our:

  • Lightweight and distributed streaming processing and storage engines

  • Unified platform for streaming and historical data processing via SQL

  • Single binary, without dependencies

Building “great” requires intense discipline and focus. Like many startups, we’ve faced the challenges of building a deeply ambitious, technically challenging product in the face of limited resources. We’ve solved this by going all-in on building through product and engineering, and are thrilled to have seen strong market traction in spite of investing relatively fewer resources in marketing.


Among the more than 250 customers who have set up their workspaces with Timeplus, we’ve seen particularly strong traction in financial services and IoT use cases. Engineers are choosing Timeplus for large-scale, mission-critical data problems. Or, in the words of Ms. Ling Wang, head of IT at Huatai Securities, “In today’s rapidly changing markets, businesses must go real-time or become obsolete, Timeplus fills a major gap in the market. It combines ease of use, SQL that supports streaming, and speed. It makes extracting insights from streaming data even easier, saving us from writing thousands of lines of code and hundreds of hours of development. The ability to monitor and analyze massive amounts of real-time investment data leads to greater risk control and cost analysis.”


Building from work of the ClickHouse team, we are solving an incredibly difficult technical challenge: creating an elegant, easy-to-use unified streaming and historical analytics platform in a single binary. It’s an amazing one-two combo of best-in-class real-time OLAP analytics (ClickHouse) and powerful and lightweight streaming processing and incremental analytics capabilities (Timeplus).


Making ”unified” easy will drastically transform how data engineers and analysts work. We are proud of what we’ve built, and are excited to make significant contributions back to the ClickHouse community. We can’t wait to see what developers, hobbyists, and enthusiasts will build.


Visit Proton on GitHub to get started!

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