Oracle is set to cut storage pricing and add major updates to its cloud data warehouse service, Oracle Autonomous Data Warehouse, in an effort to take on competing services from rivals including Amazon Web Services (AWS), Microsoft, Google and Snowflake.
The updates to Oracle Autonomous Data Warehouse, announced Wednesday, will be available from the Oracle public cloud and on-premises via Oracle Cloud@Customer. They include a 75% reduction in storage pricing, adoption of new data file formats such as Apache Iceberg, a new low-code Data Studio, and the adoption of Databricks’ open source Delta Sharing protocol.
The updates, which will be provided to Oracle Autonomous Data Warehouse customers at no additional cost, are expected to be made generally available by the end of the third quarter, said Patrick Wheeler, vice president of product management at Oracle’s database division.
“We’re reducing the cost of native autonomous data warehouse storage, that is Exadata storage. We’re going down from $118 per terabyte per month to $25 per terabyte per month. That is the same price as object storage,” Wheeler said.
Storage price cut lowers barriers to adoption
By lowering the cost of storage in its data warehouse, Oracle is removing one advantage that date lakes usually have over data warehouses, said Constellation Research’s principal analyst Holger Mueller.
But enterprises are not likely to completely move their data from lakes to data warehouses completely, said dbInsights principal analyst Tony Baer. Instead, the pricing change “will stretch the lifecycle for Autonomous Data Warehouse customers to keep their data local for longer time periods,” Baer said.
The pricing change also challenges rival hyperscalers such as AWS, Microsoft and Google Cloud.
“It basically takes direct aim at Oracle’s hyperscale cloud rivals, literally removing cost as a barrier to entry for Autonomous Data Warehouse or exit from a competing solution such as AWS RedShift,” said Omdia chief analyst Bradley Shimmin.
“The reduced pricing coupled with the company’s purported 20% speed-up on Exadata hardware supports Oracle’s broader goal of delivering a highly differentiated level of performance, coupled with lower operating costs through both speed and automation,” Shimmin added.
Optimizing cloud costs
Oracle’s price cut also could be a reaction to efforts by companies to optimize cloud costs, according to Doug Henschen, principal analyst at Constellation Research.
“Oracle is trying to win over more customers, simple as that. The more data that accumulates on a cloud, the more costly storage becomes,” said Henschen
The current financial environment, according to Amalgam Insights’ chief analyst Hyoun Park, will likely compel CFOs to justify “any technical investment that can result in a million-dollar savings opportunity while retaining core functional capability.”
“Data warehouse vendors cutting costs are pushing against Snowflake’s relatively high-priced model, both in light of the concerns around cost management as well as to make the case for enterprises to find migration from high-priced services compelling,” Park said.
Adoption of Delta Sharing protocol takes aim at Snowflake
Oracle’s adoption of Databricks’ Delta Sharing protocol is a major part of the updates to its Autonomous Data Warehouse. The protocol was adopted, according to Oracle’s Wheeler, to avoid vendor lock-ins for data sharing and sort out issues such as security, version control and access management of data sets.
“With this open approach, customers can now securely share data with anyone using any application or service that supports the protocol,” the company said in a statement.
Oracle’s decision to adopt the protocol could be primarily due to its popularity and to counter Snowflake’s product offerings, analysts said.
“Though not yet a standard protocol, Databricks’ Delta Share is building significant momentum across data and analytics players as a means of securely exchanging data between applications housed on disparate cloud platforms without having to do any sort of replication,” said Omnia’s Shimmin.
The protocol could also serve as a counter to Snowflake’s inter-Snowflake sharing capabilities, which are restricted to a closed protocol that only includes other Snowflake data sources.
“With Snowflake’s success based on its ease of use and cloud-native build, other notable data vendors are attempting to become less expensive, more versatile, and more valuable,” said Amalgam Insights’ Park.
Oracle has been consistent in adopting the protocol across its offerings, dbInsights’ Baer said, citing the previously announced support for Delta Sharing in MySQL HeatWave.
Oracle Autonomous Data Warehouse gets low-code Data Studio
The addition of Oracle’s Data Studio inside the Autonomous Data Warehouse will help enterprise data scientists, analysts and business users to load, transform and analyze data, said Wheeler, adding that it uses a drag-and-drop interface typical of low-code platforms.
Oracle’s Data Studio inside Autonomous Data Warehouse, according to analysts, competes with the likes of Amazon DataZone and Google Dataplex, as vendors cater to enterprise demand for self-service analytics.
“Oracle has more than 100 connectors prebuilt into Data Studio that can help analyze, prepare, and integrate data into the data warehouse without having to rely on IT teams. This is a big deal, particularly for data scientists, who waste far too much time gaining access to and massaging disparate data sources. Anything that speeds these tasks would be greatly appreciated by these enterprise users,” Shimmin said.
A Google Sheets add-on is also now part of Oracle Autonomous Data Warehouse in addition to the already available Microsoft Excel add-in, the company said.
Oracle updates include multicloud features
Other updates to Oracle’s Autonomous Data Warehouse — including the addition of data sources, data file formats, notification access for Microsoft Teams, data catalog sources, and direct query access to Google BigQuery — serve to add multicloud functionality to the system, Wheeler said.
Oracle’s choice to allow the data warehouse to query Apache Iceberg tables is due to the rising popularity of the data file format, analysts said.
“Iceberg is an open standard table format that organizations are demanding because it ensures that their data will be accessible to them over the long haul in a standards-based way, rather than locked up in a proprietary database format,” Henschen said, adding that enterprises want their cloud-based, analytical data platform to also be a “lakehouse” that is able to store and support the reuse of semistructured and unstructured data.
The addition of Apache Iceberg support also targets AWS, said Shimmin, adding that “AWS users are flocking to Iceberg as a means of lowering their data storage costs.”
In addition, Oracle has integrated its data warehouse with AWS Glue to allows users to retrieve data lake schema and metadata automatically.
Oracle collaboration with AWS
While the integration could be necessary to attract Glue users, Shimmin believes that the integration is another step toward Oracle’s collaboration with AWS.
“The Glue integration is Oracle’s long-term plan to create a cloud interconnect service just as it has done with Microsoft. This would enable AWS users to stand up and manage Autonomous Data Warehouse from within AWS using a single pane of glass, for example,” Shimmin said.
The combination of the new updates to the data warehouse, according to analysts, will help Oracle to take on the likes of Snowflake, its biggest rival, and Google BigQuery.
“With this new update, Oracle has come up with its answer to Google BigQuery Omni, which lets you query data on AWS or Azure and bring the results back to the BigQuery data warehouse on Google. The core Autonomous Data Warehouse service runs exclusively on Oracle Cloud Infrastructure (OCI), but they’re moving to enable querying of data on AWS, Azure and elsewhere,” Henschen said.
Other data warehouse rivals include Snowflake, Microsoft Synapse and Amazon Redshift.
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