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Databricks acquisition of BladeBridge boosts data migration
The data and AI vendor's latest purchase adds AI-powered ETL capabilities aimed at making it easier for new customers to transport data from competing data storage platforms.
Databricks continued its acquisition spree, purchasing BladeBridge to add AI-powered data migration capabilities.
Financial terms of the transaction, unveiled on Feb. 4, were not disclosed.
Once a data lakehouse specialist, San Francisco-based Databricks has aggressively built an environment for AI development with a series of acquisitions over the past two years. Given its transition from data management to AI development underpinned by data management, Databricks has attracted the investment community's attention. Investors recently rewarded the vendor with $10 billion in equity funding plus another $5.25 billion in credit financing.
The acquisition of BladeBridge, a data migration specialist founded in 2006 whose AI-powered capabilities help users to move data from one system to another, now contributes to Databricks' evolution by better enabling new customers to transport data into Databricks SQL, the vendor's serverless data warehouse.
As a result, the move is significant, according to Doug Henschen, an analyst at Constellation Research.
"This will make it easier for customers to move from other platforms to Databricks," he said. "It's something they could have done and that many database and data platforms are doing organically, but this will … ease migrations from other platforms."
In addition to acquiring BladeBridge's technology, the vendor's staff, including co-founder and executive vice president Simon Eligulashvili, will join Databricks.
Adding through acquisition
Databricks' acquisition of BladeBridge adds capabilities designed to better enable existing customers to move data into Databricks, where it can be used to inform AI and analytics tools. In addition, adding BladeBridge's tools is geared at simplifying the data migration process for new customers transferring data out of data warehouses and other storage formats.
Using LLM-powered AI, BladeBridge's tools automate code analysis and conversion across over 20 data warehouses and extract, transform and load platforms. The result is reduced manual labor, faster data migration, and code validation.
Even before the acquisition, hundreds of current Databricks SQL customers used BladeBridge to migrate their data, according to Databricks. As a result, the acquisition makes sense for Databricks, according to Kevin Petrie, an analyst at BARC U.S.
However, beyond merely making it easier for customers to get started with Databricks, the purchase demonstrates the evolution that Databricks, which did not support SQL tables until recently, has made to support one of the favored programming languages.
"This is a good move for Databricks," Petrie said. "Just a few years ago Databricks was a newcomer to SQL tables and data warehousing. Now, they have the confidence to … put new dollars to work on a strategic acquisition that helps lure enterprises away from competitors."
In addition, the acquisition potentially strengthens Databricks' foundation for AI and machine learning development, given that structured tables remain the most popular input for such models, he continued. That said, there's a growing repatriation trend with many enterprises moving data out of the cloud and back on premises, which could affect the potential impact of acquiring BladeBridge, according to Petrie.
"Like other cloud platforms, Databricks faces a challenging macro trend: enterprises still favor on-premises infrastructure for some analytics projects," Petrie said, noting that a 2024 survey from Barclays found that 83% of CIOs plan to repatriate at least some data back on premises or to a private cloud.
Meanwhile, however significant the acquisition turns out, it remains to be seen exactly how Databricks plans to integrate BladeBridge's capabilities with existing Databricks data migration tools, according to Donald Farmer, founder and principal of TreeHive Strategy.
It's possible they'll be combined or packaged with existing Databricks capabilities, or Databricks could use BladeBridge as the foundation for a new service, much the way it used MosaicML as the foundation for its AI development suite.
"Let's see what they develop here and -- importantly -- if Databricks will charge for the use of these migration tools," Farmer said.
Regarding Databricks' acquisition strategy, although the vendor has made a flurry of purchases over the past two years, it has been strategic, according to Henschen.
Databricks paid $1 billion or more for MosaicML and Tabular. But rather than acquiring large companies that are difficult to integrate, it has mostly targeted small vendors whose staff and technology can easily fold into Databricks.
"I like that they have acquired mostly small niche players that logically fit into the company's existing market space," Henschen said. "It's a bad sign when companies go after more mature companies and adjacent markets just to boost revenue and keep growth going."
Increasing competition
Flush with cash, Databricks' acquisition of BladeBridge perhaps signals that it is more aggressively targeting customers of rival vendors.
By making it easier to move data, Databricks is removing some of the burden of leaving one vendor for another. In addition, Databricks, perhaps tellingly, directly named rivals Snowflake, AWS and Teradata in the news release revealing its latest acquisition.
However, though Databricks mentioned helping enterprises migrate away from rivals when unveiling the acquisition, BladeBridge was mainly used to migrate data from outdated platforms, according to Henschen.
"The dominant scenarios that BladeBridge supported were from truly legacy data integration platforms and database platforms to modern alternatives," he said.
For example, BladeBridge customers were leaving tools such as IBM DataStage, IBM Db2, Informatica Power Center and Microsoft SQL Server in favor of modern data integration and data storage platforms, Henschen continued.
"I doubt many customers were going from Snowflake to Databricks," he said. "For Databricks, though, it's a good tech and personnel pickup that will accelerate migrations."
Farmer likewise downplayed the potential to use BladeBridge's technology to make it easier to poach customers from rivals, noting that BladeBridge supports conversions from over 20 platforms and not just Amazon Redshift, Snowflake and Teradata.
In addition, it was previously possible to use BladeBridge to migrate from Databricks to another platform, so it remains to be seen whether Databricks plans to remove or limit certain functionality, Farmer continued.
"The clear emphasis on the commercial goal of migrating Snowflake, Redshift and Teradata to Databricks does leave some unanswered questions," he said.
Eric Avidon is a senior news writer for Informa TechTarget and a journalist with more than 25 years of experience. He covers analytics and data management.
