During the 64th edition of the IT Press Tour in New York, VMblog sat down with TextQL‘s CEO Ethan Ding for an eye-opening discussion about enterprise data management. The company’s approach to handling big data and their mission to break vendor lock-in presents an intriguing solution to a costly enterprise problem.
The Data Platform Dilemma
Enterprise data management has hit a critical point. While tools like ChatGPT and various AI solutions work well for documents under 10GB, enterprise-scale data management is a different beast entirely. “If you try to put more than 10 gigabytes of data in an Excel file, your computer starts to fall apart,” Ding explained during our briefing. “But when you start talking to enterprises, you’re dealing with hundreds of thousands of tables, trillions of rows, petabytes of data.”
The Expensive Reality of Platform Lock-In
The current state of enterprise data platforms resembles a high-stakes hotel California – you can check out anytime you like, but you can never leave. At least not without paying an enormous price.
During our briefing, Ding painted a stark picture: “If you’re a new CFO and you want to move all your business logic, not just the data, but the business logic connecting the data together from SAP to NetSuite or vice versa, that’s going to be a Deloitte contract, an Accenture contract over 50 million dollars over five years.”
Even more troubling? That massive investment only moves about 10% of your actual business logic. Think about that for a moment.
Why Traditional Platforms Keep You Trapped
The lock-in strategy isn’t accidental. Traditional platforms have built their business models around making data migration as complex and expensive as possible. They do this through:
- Proprietary query languages
- Unique table formats
- Platform-specific data structures
- Complex data transformation requirements
“Historically, you’ve been only able to really access and use big data in platforms like the database, the Telos, AWS, or Oracle. You have your ERPs, your CRMs, your ITSM systems,” Ding explained. “These platforms have a lot of lock-in because you need to build a lot of algorithmics.”
The Hidden Economic Time Bomb
Here’s where things get interesting. Currently, data platform costs typically represent about 10% of a company’s IT budget, with most costs going to salaries. However, as AI coding agents make data scientists more productive, something unexpected happens – unit costs drop, driving up demand.
This creates a paradox: as efficiency increases and more departments want to leverage data analytics, platform costs could balloon to 50% of IT budgets.
“When data platform costs become 50% of your spending, those 20x markups become a lot less cool,” Ding noted.
TextQL’s Solution: The Rosetta Stone of Data
Founded in December 2022, TextQL has developed what they call a “Rosetta Stone system” for enterprise data.
This system can:
- Handle hundreds of thousands of tables
- Process trillions of rows
- Manage petabytes of data
- Work across multiple platforms
- Reconcile inconsistent data formats
One of the most impressive features is its ability to handle data inconsistencies. As Ding demonstrated, the system can recognize when “Fred” in one database is the same as “Fred Frankel” in another and “[email protected]” in a third – all automatically.
A Real Game-Changer: Pay-As-You-Go Computing
TextQL’s pricing model represents a fundamental shift from traditional platforms. Instead of charging for CPU hours, they bill only for compute time when data is in transit. “We can spin up a really big computer on the fly,” Ding explained. “You don’t have to pay the database provider for hours of runtime. You pay us for minutes in transit.”
This approach allows for more dynamic, real-time analysis. For example, while a traditional data scientist might analyze housing prices monthly by state, TextQL enables analysis by zip code daily, with instant alerts for relevant changes.
The Journey to Success
TextQL’s path hasn’t been smooth sailing. The company has rewritten their entire codebase seven times to get it right. “We lost every customer until January of this year,” Ding candidly shared. “But since January, we haven’t lost a single customer or pilot.”
Their persistence has paid off. With about 12 enterprise clients and revenue approaching $400-500K, they’re projecting $7-7.5 million in revenue. Their success particularly resonates with:
- CFO offices seeking better financial visibility
- Financial services companies handling complex data sets
- Healthcare organizations managing sensitive information
Security and Deployment Flexibility
For organizations with strict security requirements, TextQL offers flexible deployment options. “We deploy our stuff on-prem,” Ding noted. “Whatever they’ve got on premises is good inside their machines. It runs in their system.”
The platform works across major cloud providers, with their most mature deployments on AWS, while building out support for Azure and other platforms.
The Future of Enterprise Data Management
While natural language querying isn’t new – companies have been promising it for 35 years – TextQL’s approach stands out. They’re not just making SQL easier; they’re challenging the fundamental economics of enterprise data platforms.
“If you connect me to a database of infinite complexity, I can answer questions your best data scientist can’t answer in 15 minutes,” Ding stated confidently. This bold claim backs up their mission to democratize enterprise data access while breaking the expensive cycle of vendor lock-in.
Looking Ahead
TextQL’s ambitious vision extends beyond just query tools. They’re planning to develop their own data warehouse infrastructure and offer free dashboard tooling, potentially disrupting another aspect of the traditional data platform market.
For IT leaders tired of paying enormous fees to move their data, TextQL represents more than just another tool – it’s a potential pathway to true data independence. While it’s too early to declare victory over decades-old platform lock-in strategies, TextQL’s approach offers a compelling alternative that could reshape how enterprises manage their data assets.
As organizations continue to grapple with growing data needs and rising platform costs, solutions like TextQL might just be the key to breaking free from traditional vendor lock-in. And for enterprise IT leaders, that’s definitely worth watching.
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