20 Hot New Data Tools and their Early Go-to-Market Strategies

As enterprise tech investors at Work-Bench, we’ve seen firsthand how hard it is for early stage startups to close early customers and build a repeatable sales process. That’s why we’re all about helping our founders successfully launch and scale their enterprise go-to-market efforts through making customer introductions, navigating complex accounts and back-channeling, and helping them build out their sales team.

Recently, Amplify Partners, Data Council, and Great Expectations published a comprehensive post, “25 Hot New Data Tools and What They DON’T Do,” highlighting the top 25 data tools in the market today. Given the sheer number of data tools that have emerged over the past few years, it’s become harder to figure out who does what, which companies actually compete against one another, and who will break out to become standalone companies.

As a follow-up to their analysis, I decided to put a Work-Bench spin on the post. I was curious to understand how these startups were going to market with customers, and what trends could be identified from their sales motions.

A few notes:

While I know a handful of the companies listed, I formed my analysis by collecting data pertaining to the companies’ business models, pricing strategies and customers as follows: I checked each company’s website for pricing information, open source product offerings, sales demos, customer case studies and customer logos. Then, I went on each company’s LinkedIn profile and checked for the different roles and titles they had on the sales team. Based on this information, I came up with some interesting conclusions.

Five of the 25 companies listed in the original post, namely Select Star, Hex, Bayes, Watchful and Monte Carlo, are still in stealth, so I excluded them from this post since there is no public data to analyze.

The Takeaways

1. Enterprise GTM motion is changing

Traditionally, it used to be all about having a heavy direct sales team for data companies to go-to-market. Today, we see a variety of approaches including bottoms-up and open source usage. This leads to a new set of challenges because in a world where there is more competition for eyeballs, it will be interesting to see how these companies break out a crowded market and differentiate.

• 13 out of the 20 tools use open source communities to drive customer adoption: Great Expectations/Superconductive, DataHub/LinkedIn, Flyte/Lyft, Kedro/Quantum Black, Mara/Project A, dbt/Fishtown Analytics, Databand, Dolt/Liquidata, Dataform, Materialized, Prefect, Preset, and Dagster/Elementl are powered by open source technology that leverages the developer community as key contributors to the software base.
• 6 out of the 20 companies are driven from the bottom-up and operate under a self-serve, freemium business model under which users have access to a free version of the software with basic functionalities for an unlimited period. Users can upgrade to a paid plan to enjoy exclusive functionalities. These companies include DoltHub/Liquidata, Dataform, Materialized, Prefect, dbt, and Preset.
• 7 out of the 20 companies utilize a direct sales strategy: Companies including Sisu Data, Ascend, Snorkel, DataKitchen, Materialize, Prefect, dbt, Toro Data, Tecton have made some early sales hires to actively help land early paid customers at the departmental level and expand across the enterprise.
• Open Core / Cloud service hybrid business: Under this hybrid model, companies like Prefect and Materialized offer their products as a managed service to generate different pathways to monetization.

2. Pricing varies big time in early stage startups

Pricing can be particularly difficult for an early GTM company to nail down and we see a variety of pricing models across the companies we analyzed.

We wonder which model will work best to motivate increased adoption with customers (without breaking the bank), while also balancing the need for the startup to properly monetize its product.

• 6 companies offer a free plan from the onset: Dataform, DoltHub/Liquidata, Prefect, Materialized, operate under a freemium pricing tier, Ascend.io operates under a trial pricing tier, dbt operates under a free trial / freemium hybrid approach while Toro Data doesn’t offer any free plan.
• 4 companies, namely dbt, Dataform, Prefect and Ascend have adopted a tiered pricing model that offers a range of packages with different combinations of features at different price points, giving users the flexibility to upgrade to a more expensive plan as they outgrow their current package.

Other B2B pricing models include:

• Flat monthly rate — DoltHub / Liquidata
• Per user / seat monthly fee — dbt, Dataform, Prefect
• Per VM instances/hour — Ascend
• Per-node monthly fee — Materialize.io
• High volume pricing — Toro Data

3. Early customer selection is critical

If you have a lightweight product, a thriving community, and it is easy for a customer to install your software and get going, then perhaps SMBs make sense for high velocity deal closing. On the other hand, if you’ve invested from the get-go to build an enterprise grade product that meets security and scalability requirements of the Fortune 500, and you align with a timely pain point of theirs, getting even a few of these logos can be monumental in positively impacting your company trajectory and enabling you to begin building a competitive moat.

By analyzing the publicly available customer logos and case studies highlighting key clients, we found a healthy split in early customers in the group:

• 6 out of the 20 companies highlight enterprise clients: Sisu Data, Snorkel, Prefect, dbt, DataHub and DataKitchen
• 8 out of the 20 companies highlight SMBs: Databand, Sisu Data, Prefect, dbt, DataHub, DataKitchen, Dataform, and Ascend
• 3 out of the 20 companies highlight big tech companies: Preset, dbt and Snorkel
• The remaining companies don’t have any logos listed.

4. There is a growing impact of community

Community engagement across open source and Slack channels is a key strategy for data tools to unlock user adoption and drive sales and marketing.

• 10 of the companies that have an open source offering maintain an active community Slack: Prefect, Great Expectations, Databand, Dataform, DataHub, Flyte, Dbt, Preset, Dagster, Materialized
• 3 of the companies that have an open source offering don’t maintain an active community Slack: Dolt/DoltHub, Mara, Kedro

We are excited by all the innovation in the data ecosystem and continue to track this space for new investment opportunities. Also, check out my previous blog posts covering the modern data engineering as well as the challenges around data catalogs and discovery. If you’re a startup building in this space and figuring out your early go-to-market motion, I’d love to connect and share some perspective.