"There is a clash of these two technologies. Databricks has coined its lakehouse concept, offering SQL and BI-like queries on its platform, while Snowflake, for example, has started to support unstructured data. Over the past couple of years, boundaries have merged between data lakes and data warehouse. Tabular launches with the promise of a 'headless' data warehouseīut Snowflake is making progress at looking like a data lake, which was promising for the vendor and the customers who favor the platform, he added.Aerospike targets Java Spring devs with support for the popular framework.Trino and dbt open source data tools snuggle closer with integrated SaaS.Databricks snaps up MosaicML to build private, custom machine models.
#TABULAR DATA FORMAT FULL#
"I don't think it's convincing because this whole notion of apps that are just kind of focused on data is so incredibly lightweight and trivial, compared to full application solutions that enterprises need." Mike Gualtieri, Forrester principal analyst, was unimpressed with Snowflake's move in third-party apps. "Snowflake's valuation and the expectations put upon it by shareholders' force, mean it is trying be all things data, whether it be an application development platform or machine learning platform, or anything in between," Park said. Meanwhile, it was expectations from investors that is pushing Snowflake to branch out as much as anything else. Park reckons Iceberg is technically winning in terms of adoption, but faces challenges in terms of performance. "It's a smart way to be able to be the intelligence above all of the data lake formats that are out there," he said. However, Databricks' move to support all three would allow it to offer services to Iceberg customers, including those using Snowflake or Cloudera. "A lot of third parties are working with Iceberg, feeling that it is the easiest data format to work with and because they are frankly afraid of empowering Databricks," he told The Register. Hyoun Park, CEO and chief analyst with Amalgam Insights, said there was a battle in the data lake world between the Iceberg, Hudi and Delta formats. More than 25 apps were already available, it said. The idea is developers can build and test Snowflake Native Apps, to exploit data in its marketplace. Snowflake also announced its Native App Framework in public preview on AWS. It said organizations could work with data in their own storage in the Apache Iceberg format, whether or not the storage was managed by Snowflake, but use the vendor's performance management and governance tools.
The cloud data warehouse and platform company - once valued at a staggering $120 billion - has announced a private preview of its Iceberg Tables, which also promises to reach across silos – although without supporting Hudi and Delta. In some sort of enterprise data analytics grudge match, Snowflake decided to hold its annual get together in the same week as Databricks. The backer of Iceberg, meanwhile, has not stood still. This year, SAP and Microsoft have announced support for Delta, but both have said they could address data in Iceberg and Hudi in time. In fact, Databricks CEO and co-founder Ali Ghodsi told The Register last year that the three table formats – Iceberg, Hudi and Delta – were similar, and all were likely to be adopted across the board by the majority of vendors. More specialist players are also in on the act, including Dremio, Starburst, and Tabular, which was founded by the team behind the Iceberg project when it was developed at Netflix. It has spent the last couple of years gathering momentum, after Snowflake, Google, and Cloudera announced their support last year. Apache Iceberg is an open table format designed for large-scale analytical workloads while supporting query engines including Spark, Trino, Flink, Presto, Hive and Impala.
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