Fivetran

Tomasz Tunguz

@ttunguz

Every year I make a list of predictions & score the previous year's. 2025 was a good year : I scored 7.85 out of 10. 1. The IPO market rips. <see image> Score : 0.6. 46 software IPOs raised $12.3b in 2025, up from 21 IPOs raising $3.8b in 2024. The 2021 peak saw 126 tech IPOs raise over $150b. CoreWeave, Circle, & Figma all successfully debuted with significant market caps. However, we didn't see some of the high-flying IPOs like SpaceX, Stripe, & Databricks go out, although 2026 is a new year. 2. Google continues their surge in AI. Score : 1. Google has reclaimed its position at the apex of the AI landscape, ranking in the top tier of nearly every major category. Gemini 3 represents a fundamental leap in pre-training efficiency & multimodal integration. Gemini 3 Flash has redefined the frontier for performance & latency, becoming the default engine for high-frequency agentic workflows. In the open-source arena, the Gemma models consistently hold the top spots for their weight classes, offering 70B-level reasoning in 27B packages. Even in creative media, Google's video models rank in the top three globally, prioritizing temporal consistency & character stability for enterprise use. 3. Voice becomes a dominant interface for people with AI as speech models are pushed on device & the accuracy/latency astounds. Score : 1. OpenAI reported that ChatGPT voice chat accounts for 19% of total user engagement as of October 2025. Globally, there are now 8.4b voice assistants in use, with 153m users in the US alone. 80% of businesses plan to integrate AI-driven voice into operations by 2026. The prevalence of dictation with Whisper, WisprFlow, & conversations with agents like Gemini Live is now normal. 4. US VC investment remains roughly around $210-$230b, but VC fundraising increases by 20% Score : 0.5. US VC investment hit the mark, landing at approximately $220b for 2025, driven by massive AI rounds. However, the fundraising prediction missed. While deal counts rose 11% in early 2025, actual US VC fundraising is on track for a ~20% decline, totaling roughly $65b for the year. A prolonged liquidity crunch & a slow exit environment kept LPs cautious, despite the enthusiasm for AI. 5. Consolidation is the theme for the Modern Data Stack. Score : 1. 2025 was a record year for data infrastructure M&A, as the "Modern Data Stack" shifted from a collection of best-of-breed tools to a vertical race for integrated platforms. IBM / Confluent : 11b Salesforce / Informatica : 8b DBT / FiveTran : ? CoreWeave / Weights & Biases : 1.7b OpenAI / StatSig : 1.1b Databricks / Neon : 1b The consolidation moved down the stack, proving that the race is now for power, compute, & integrated software. Most notably, CoreWeave's acquisitions signal the rise of the "Full-Stack Hyperscaler," owning everything from the GPU to the MLOps layer. 6. The first $100m ARR company with 30 or fewer employees is created. Cursor hit $100m in ARR with 12 employees. For comparison, Slack had 650 employees at $100m ARR. Ramp had 275. Wiz had 400. Score : 1. AI-native teams have achieved unprecedented efficiency. Cursor hit $100m ARR in January 2025 with just 12 employees, proving that agentic software can scale with minimal headcount. Midjourney continues to defy gravity, reaching $500m ARR with a team of roughly 100. These teams leverage the capital efficiency of agentic software to meet ravenous consumer & enterprise demand. 7. After years of declines, the US web3 engineering population grows by 25% as the government embraces crypto & web3. Score : 1. US Web3 jobs grew by 26% in 2025, reaching 21,600 positions. The regulatory environment shifted significantly, leading to a surge in institutional adoption & a new wave of consumer applications built on decentralized stacks. 8. Data center spending by hyperscalers eclipses $125b for the year as the AI race fuels demand for GPUs. Broadcom is the hottest semiconductor stock of the year. Score : 0.75. Hyperscaler CapEx far exceeded expectations, reaching an estimated $315b to $350b in 2025. Amazon alone spent $100b, followed by Microsoft ($80b) & Google ($75b). Broadcom's stock surged as it became the primary beneficiary of the AI networking buildout, outperforming even NVIDIA in the latter half of the year, but it was third in the domain to Google (62%) & Micron (198%). M 9. Stablecoin supply increases 50% to $300b as more businesses adopt this payment mechanism for B2B payments. Stablecoin volume is greater than 3x Visa's transaction volume. Score : 1. Stablecoin supply hit $310b in December 2025. Monthly adjusted stablecoin volume has now surpassed Visa's network volume, with annual on-chain volume exceeding $46t—nearly 3x Visa's transaction volume. B2B adoption has accelerated as businesses seek faster, cheaper cross-border settlement. 10. Observability, SIEM, & Business Intelligence begin to use the same data lake. Usage-based pricing for many software companies creates a need for a single data lake. The data lake becomes the dominant data architecture across all workloads. Score : 0. While there is some convergence in the use of OpenTelemetry (OTel) for both security & observability, the broader vision of a single data lake for BI, SIEM, & observability has not materialized. Enterprises continue to maintain siloed architectures for performance & compliance reasons, & the cost savings from hybrid lakehouse models haven't been enough to force a total consolidation. https://t.co/1QEY0oXBph

Tanay Jaipuria

@tanayj

Busy week for M&amp;A in and around AI: • OpenAI acquires Statsig (~$1.1B, all-stock) • Atlassian acquires The Browser Company ($610M cash) • Fivetran acquires Tobiko Data • CoreWeave acquires OpenPipe • Cato Networks acquires Aim Security

Lenny Pruss

@lennypruss

We met @jthandy, @drewbanin & @connormcarthur back in 2018 when @getdbt was a niche tool for data cool kids. Since then, they’ve built a movement, redefining how analysts and engineers work with data. Today, @fivetran and dbt Labs are joining forces to create a dominant data platform company with combined $600M+ ARR and 10K+ customers. Insane how far they've come from humble beginnings. This is still just the start. 🚀🚀🚀

Barry McCardel

@barrald

I’m happy for everyone… but I don’t think data is over! The promise of the modern data stack was that it would be easy to move all your data into one place, transform it into usable form, and then expose it to people to make better decisions. The last few years have been effectively a first draft of that, but AI is going to finally deliver the full potential. We are seeing a wave of change coming for the whole stack: 1. At the storage/query layer, we’re starting to see glimmers of companies thinking iceberg-first, with the warehouses demoted to query engines on top of open format data they have sovereignty over. This will make it much easier to do things like semantic search, process real-time, and lower query costs (very important as agents drive a lot of volume). This is going to be a big change (and @fivetran is sneakily pushing it!) 2. at the transformation layer, it’s obvious that AI can make the process of building, maintaining, and observing data pipelines 100x easier. We’re seeing sparks, but no fire, but I suspect that will change as more teams are figuring out how to apply agentic patterns (and dbt is perfectly positioned here) 3. At the consumption layer, our relationship with the data is already changing, as natural language becomes a first class entry point, and agents can partner with us to think through problems and explore new paths. Data remains one of the most important and most unsolved problems in companies, and none of the other AI stuff works without us being better at it. It’s an exciting time and I am personally optimistic that George, Tristan, and the combined Fishtran team can push us even further and faster 📈💜

Jamin Ball

@jaminball

Huge congrats to the @dbt_labs and @fivetran teams on their merger! Cant wait to see what they accomplish together The combined company will have ~$600m ARR and north of 10k customers https://t.co/6mGdI01dap

Rifat Ahmed

@Rifat_EE

The ETL business is quietly dying,, and one open source project just fired the last shot. For 20 years, moving data from your production database to a warehouse has been a $30 billion a year industry. Fivetran,Airbyte,Snowflake pipelines, All of it built on one assumption )- your production DB cannot handle real questions. Spice AI 2.0 just proved that wrong :: --> A query that used to take 65 minutes now runs in 5.3 seconds. Same test, 26x faster. --> Live data from Postgres, MySQL, and MongoDB reaches any agent within 2 seconds. No pipelines, No waiting. --> Every agent gets its own sandboxed view. The production database never sees the wrong query. Why this ends an industry : )- The whole ETL stack existed to protect production databases from heavy queries. Spice does that at the query layer instead. )- Every agent company was rebuilding this inhouse at ten times the cost. Now it is one download. )- MIT license, open source, runs on your own boxes. For 20 years, moving data was the business. Now the data does not have to move,, And the industry that moved it just ran out of story.

George Fraser

Co-founder & CEO

George Fraser co-founded Fivetran in 2012 and has served as CEO throughout, guiding it from a Y Combinator startup into a global leader in automated data movement, and now leads the merged Fivetran + dbt Labs. A former neurobiologist, he earned a Ph.D. from the University of Pittsburgh and studied at Carnegie Mellon before turning to data infrastructure.