Tobiko Data Announces General Availability of Enterprise-Grade Solution

Tobiko Data launches Tobiko Cloud, the enterprise-ready SQLMesh with advanced automation, security, and impressive performance gains.

Tobiko Data, the creator of leading open-source data transformation tool SQLMesh, today announced the general availability of its enterprise-ready flagship solution Tobiko Cloud, featuring built-in scheduling with integrated observability features, advanced change categorization, and enterprise-grade security with single-sign-on (SSO) and role-based access controls.

SQLMesh gained popularity in the data community because its architecture allowed data engineers to run data transformation tasks at a fraction of the time and cost of other platforms, With semantic understanding of SQL and unique mechanisms for copying and promoting production data in virtual environments isolated from physical production tables, SQLMesh ensures companies don’t waste unnecessary and costly compute cycles on repeating their work or running data processes with preventable errors, which for enterprise companies can take hours and in some cases cost millions.

A benchmark study Tobiko conducted in partnership with Databricks found that in comparison to dbt’s open source Core™ product, SQLMesh is 9 times faster and cheaper in routine data transformation tasks, and can save the average data team 11 engineering hours a month.

Tobiko Cloud, the new enterprise-ready version of SQLMesh, performed even better. It is adapted to the needs of large enterprises with stricter data governance requirements and more complex projects and dependencies, including:

• Scheduler, a built-in scheduling tool that delivers configuration simplicity with secure data-encryption and support for isolated Python environments.
• Observability features including trigger-based configurable runtime alerts, a cost tracker that tracks compute costs for BigQuery and Snowflake as transformation tasks are run, and a debugger view with logs and traceability for users to know when and why models fail.
• Concurrency and pause model runs that enable data teams to run multiple models and tasks simultaneously without bottlenecks, and to pause individual instances of production without impacting others.
• Advanced change categorization that categorizes whether your change is breaking or non-breaking, and any potential downstream impact.
• Cross-database diffing that leverages a hashing algorithm to perform comparisons across multiple warehouses, eliminating the need for expensive full joins.
• SSO, role-based access controls, and hybrid deployments so enterprises can enjoy maximum security and data protection.

"Inefficient data processing translates to wasted time and massive costs,” said Tyson Mao, CEO and co-founder. “Our latest release ensures that large organizations can process their data faster, more securely, and without the unnecessary inefficiencies of legacy systems.”

Biosensing platform Strella Biotechnology has dramatically improved its data operations with Tobiko Cloud. “SQLMesh and Tobiko Cloud have been instrumental in helping our team flesh out our data organization and the analytics data warehouse,” says Naoya Kanai, Machine Learning Engineer at Strella, “Before we were operating solely on read replicas of prod Postgres databases, and we had no concept of building transformations for analytical purposes. Now we're able to build downstream analytics, assemble clean training sets for ML experiments, and iterate quickly in a collaborative fashion for anything data-related.”

Users of Tobiko’s open-source framework also state that they are finding greater value after upgrading to Tobiko Cloud, praising the solution’s ability to automate monitoring and upgrades and boost development velocity.

"Our data engineering team at Pipe transformed our SQLMesh operations by adopting Tobiko Cloud," said Tim Chan, Staff Data Engineer. "While the phrase ‘single pane of glass’ feels overused, it perfectly captures how Tobiko Cloud centralized our pipeline monitoring. We troubleshoot user plans in real-time during development cycles and track every run’s behavior – no more guesswork. The Tobiko Cloud CLI tool eliminated our upgrade headaches by automatically syncing SQLMesh and state store versions. No more manual patching or version conflicts. Combined with Tobiko’s managed infrastructure, we ditched our unscalable BigQuery state store and reclaimed engineering time. The Tobiko Cloud CLI tool silently handles upgrades while we focus on building – not babysitting infrastructure. What began as a scalability fix is now core to our data reliability.”

Data and engineering teams interested in learning more about Tobiko Cloud can visit them at Snowflake Summit June 2-5, or visit https://tobikodata.com/ to learn more and schedule a demo.

About Tobiko Data

Tobiko Data is the creator of popular open source projects SQLGlot and SQLMesh, which reduce the manual work that comes with wrangling data and increase efficiency in warehouse cost by avoiding needless table rebuilds. Tobiko’s data transformation platform, built around SQLMesh, automates away the toil of building data pipelines, enabling professionals to spend more resources on the business and less on infrastructure. Tobiko also offers an enterprise-ready version of SQLMesh, featuring advanced automation and enterprise-grade security. Tobiko has raised $21.8 million from Unusual Ventures, Theory Ventures, Fivetran CEO George Fraser, Census CEO Boris Jabes, and MotherDuck CEO Jordan Tigani. For more information, visit https://tobikodata.com/.

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