Oracle MySQL&#8217;s Unyielding Success
Oracle, a major player in the cloud and relational database management systems domain, firmly believes in its approach to make this sector intriguing and user-friendly by introducing products that simplify data querying, making it both efficient and cost-effective for enterprises. Oracle recently announced general availability of MySQL HeatWave Lakehouse which enables customers to query data in object storage as fast as querying data inside the database. In an exclusive interview with AIM, Oracle India’s technology head Saravanan P, said that the most common problem that the enterprise customers face is creating consolidated reports as there are multiple copies of databases. “We brought the MySQL Heatwave to address these multiple data source challenges, specifically, here is a database which can run both OLTP and OLAP on a single database”. Saravanan further added HeatWave Lakehouse enables customers to process and query hundreds up to hundreds of terabytes, stored in object stores like CSV and Parquet formats, as well as Amazon’s Aurora and Amazon Redshift backups. “Majority of customers of MySQL are digital native companies which heavily rely on clouds to manage their data,” he added. The aim of MySQL HeatWave Lake House is to enable  customers to easily obtain valuable real-time insights by combining data from object storage with database data. MySQL Heatwave Lakehoue  delivers significantly improved query performance and faster data loading, all at a lower cost. Currently MySQL HeatWave Lakehouse can load data from object storage that amounts to 400 terabytes, and it does this 8 times faster than Redshift and 2.7 times faster than Snowflake. As demonstrated by a 500 TB TPC-H* benchmark, its query performance is 9 times faster than Amazon Redshift, 17 times faster than Databricks, 17 times faster than Snowflake, and 36 times faster than Google BigQuery. (see below) Reason: MySQL HeatWave uses MySQL Autopilot. It is a unique feature of MySQL HeatWave that uses machine learning to automate and improve query execution. It learns from past queries and optimises the execution plan for future ones. This innovation is exclusive to MySQL HeatWave users and not found anywhere else. In addition, files in the object store are queried directly by HeatWave without copying the data into the MySQL database. As a result, MySQL HeatWave Lakehouse sets new standards for scalability and performance of query processing, speed of loading data, cluster provisioning time, and automation to query data in object storage. MySQL HeatWaveLakehouse provides customers the ability to query data in the object store in a variety of file formats and optionally combine it with data in the MySQL database. In addition, files in the object store are queried directly by HeatWave without copying the data into the MySQL database. This explains why Oracle MySQL is the first name that comes to the forefront. Currently, MySQL holds a relative market share of 44.04% in the realm of database management tools. Within this market, it claims 31.39% in the U.S., 8.19% in India, and 6.75% in the U.K. As an open-source software, MySQL takes the lead among other relational databases in the market. MySQL vs the World Today, MySQL is not alone, there are multiple players including SingleStoreDB (SQL), alongside database companies such as Redis (Real-time), MongoDB (NoSQL), Neo4j (Graph) and others are offering more or less similar services to its customers, and the competition is only getting bigger. “It’s like horses for courses,” said Sarvanan. He believes that each kind of database has its own use case. He said that Oracle’s moat is managing multiple data sources. Customers do not need to store data on one cloud and at one location. They should have the option to store data at different sources. “If you asked me today, customers are more about user databases distributed,” he added, saying that MySQL’s perfectly fits in this equation. Multi-Cloud Approach At the same time, MySQL faces heat from hyperscalers such as Google Cloud SQL, AWS SQL Server Databases, and Micrsoft Azure SQL Database, who are providing, similar platforms and services for its internal cloud customers. But, Oracle seems to be in the long game. Saravanan said that Oracle believes in multi cloud approach. “We don’t want to be homogeneous, we wanted customers to use this feature functionality, even if they’re on Azure or AWS,” he added. In other words, even if you are running your workload on AWS or Azure, you can take advantage of Oracle MySQL to query your data. “They get similar performance by using the MySQL Heatwave so that they can make use of it without migrating the data out of the cloud, and changing the application code” he added. Enterprise Data Security Speaking on data security for enterprises, Saravanan told AIM that security is in the DNA of Oracle and it takes center stage at the company and OCI (Oracle Cloud Infrastructure) is a highly secured cloud. “Any data that moves within OCI is encrypted,” explained Sarvanan. Further, he said it takes the core security of OCI to MySQL as well. He emphasised  that  MySQL gives role based data access which means that you cannot get access to the data even though you are admin. Citing RBI and MeitY, he said OCI complies with regulatory requirements in the country, and strictly follows the law of the land across geographies. En route: Generative AI Last month, Oracle partnered with Cohere, where it looks to develop powerful, generative AI services for organizations globally. The duo plans to automate end-to-end business processes, improving the decision making, alongside enhancing customer experiences. What’s next? In the coming months, Oracle is planning to announce more such products and tools to unleash their generative AI strategy for enterprise , alongside a few announcements around its expansion into vector databases and more.
MySQL Heatwave Lakehoue  delivers significantly improved query performance and faster data loading, all at a lower cost
Oracle recently announced general availability of MySQL HeatWave Lakehouse which enables customers to query data in object storage as fast as querying data inside the database. 
["MySQL", "Oracle", "Oracle SQL"]
["Oracle SQL", "machine learning", "AWS", "AI", "ML", "Oracle", "RAG", "vector databases", "Aim", "generative AI", "MySQL", "Azure", "Redis"]
["AI", "machine learning", "ML", "generative AI", "Aim", "RAG", "vector databases", "AWS", "Azure", "Redis"]
Siddharth is a media graduate who loves to explore tech through journalism and putting forward ideas worth pondering about in the era of artificial intelligence.