[email protected] Blogs : www.dasini.net/blog/en : www.dasini.net/blog/fr Linkedin: www.linkedin.com/in/olivier-dasini Harmonisez vos charges de travail transactionnelles et analytiques avec MySQL HeatWave Big Data & AI Paris - September 2023
4 … the MySQL Cloud services made by the MySQL Team The MySQL HeatWave “Family” “MySQL HeatWave” MySQL HeatWave for OLTP a.k.a MDS: (OLTP) General Purpose Optimized for OLTP MySQL HeatWave Lakehouse (Lakehouse) MySQL HeatWave (Analytics / ML) OLTP + Analytics (OLAP) + Machine Learning InnoDB Lakehouse InnoDB RAPID InnoDB RAPID
6 *Benchmark queries are derived from the TPC-H benchmark, but results are not comparable to published TPC-H benchmark results since they do not comply with the TPC-H specification 400G, 64 cores MySQL HeatWave dramatically speeds up analytic queries
7 See documented performance comparisons that show how HeatWave is 6.5X faster than Amazon Redshift at half the cost, 1400X faster than Amazon Aurora at half the cost, and 5400X faster than Amazon RDS for MySQL at two-thirds the cost 30TB TPCH, MySQL HeatWave is faster, cheaper & easier to use than all the competitive database services MySQL HeatWave performance and price comparison www.oracle.com/mysql/heatwave/performance
10 Machine learning in action with MySQL HeatWave OLTP Applications Social ECommerce FinTech SaaS Analytics Tools Real-time ML recommendations Real-time analytics on trends
salle 5 De la requête élémentaire à l'analytique avancée et l'apprentissage automatique: La Révolution MySQL HeatWave Lakehouse Mardi 26 septembre • 11h00 - 11h15 / Stand ORACLE A28 Découvrez MySQL HeatWave AutoML: l'apprentissage automatique pour tous • 16h00 - 16h15 / Stand ORACLE A28 Déverrouillez le pouvoir de l'analyse Big Data avec MySQL HeatWave Lakehouse !
15 MySQL HeatWave can process data from multiple data sources e.g. Oracle Golden Gate, ... OCI Object Storage AWS Aurora AWS Redshift Data can be in a file or other databases → No requirement to have data in MySQL https://www.mysql.com/products/mysqlheatwave/lakehouse
16 HeatWave Lakehouse Query data in object storage • Querying in HeatWave • Scale to 512 nodes, 512 TB • CSV, Parquet, Aurora & Redshift exports • Fastest load, Best price-performance Use standard MySQL syntax Combine OLTP data with object store data • 100% compatible with MySQL syntax • Use MySQL Autopilot to auto-infer schema, estimate capacity, load times, and generate load scripts • Treat data lake data as tables • Use select, join, aggregations, filters, etc… to combine data in OLTP tables with data lake tables Main benefits 1 2 3
17 Provides flexibility to develop applications on object store without any performance, cost impact Same price-performance when data inside MySQL or in object store HeatWave HeatWave Lakehouse Snowflake Redshift Google Big Query Databricks 0 10 20 30 40 50 60 70 80 90 100 1.5 1.5 41.9 20.2 41.4 92.5 10TB TPC-H Price-Performance Price-Performance (cents) • 10 HeatWave Nodes, X-Large cluster for Snowflake; 10 nodes of ra3.4xlarge for Redshift; 800 slots for Google BigQuery; Large cluster for Databricks • Standard edition price for Snowflake; 3 yr upfront price for Redshift; 1 year reserved price for Google BigQuery and Databricks https://www.oracle.com/mysql/heatwave/performance/#heatwave-lakehouse
salle 5 De la requête élémentaire à l'analytique avancée et l'apprentissage automatique: La Révolution MySQL HeatWave Lakehouse Mardi 26 septembre • 11h00 - 11h15 / Stand ORACLE A28 Découvrez MySQL HeatWave AutoML: l'apprentissage automatique pour tous • 16h00 - 16h15 / Stand ORACLE A28 Déverrouillez le pouvoir de l'analyse Big Data avec MySQL HeatWave Lakehouse !
23 Why MySQL HeatWave for new and existing applications? Unmatched price performance Integrated in-memory query accelerator 6.5X faster than Redshift at half the cost 7X faster than Snowflake at 20% the cost 1,400X faster than Aurora at half the cost MySQL Autopilot: automation to achieve high query performance at scale, higher OLTP throughput, and get the best price performance Ready for the distributed cloud Deploy on OCI, AWS, Azure Replicate data from OLTP on- premises apps to MySQL HeatWave on OCI or AWS Deploy in your data center with Oracle Dedicated Region Simplicity of transactions, real-time analytics, and ML in one managed service Eliminate the cost and complexity of separate analytics database, ML, and ETL services Avoid the latency and security risks of data movement between data stores MySQL and Amazon Aurora- based applications work without changes
24 • Modernize transactional applications using Amazon Aurora, RDS for MySQL, Azure Database for MySQL, Google’s Cloud SQL for MySQL with supporting analytical workloads from Amazon Redshift, Snowflake, Azure Synapse, and Google BigQuery • Modernize mixed workload applications using Amazon Aurora, RDS for MySQL, Azure Database for MySQL, GCP Cloud SQL for MySQL (initially without separate analytics database) • Modernize mixed workload applications using MySQL either on-premises or in the cloud • Rely on MySQL HeatWave for in-database machine learning to avoid using a separate machine learning service with data coming from MySQL, MySQL-based services, or analytics databases Modernizing applications with MySQL HeatWave Key use cases
29 “Oracle announced MySQL HeatWave with Autopilot last August, which may very well have been the single greatest innovation in open source cloud databases in the last 20 years to that point. Now Oracle has gone beyond its original unifying of OLTP and OLAP in HeatWave, with MySQL HeatWave ML. Oracle is bringing all of the machine learning processing and models inside the database, so that customers not only avoid managing ML databases apart from the core database, but also eliminate the hassles of ETL, gaining speed, accuracy, and cost-effectiveness in the bargain.” “This latest announcement from Oracle is the third major release of MySQL HeatWave in just over 12 months. Oracle has delivered more cloud database innovations during that timeframe than most cloud database vendors have delivered in the last decade. Not only does the in-database HeatWave ML make Redshift ML look like yesterday’s tech in terms of engineering, performance and cost, but the latest MySQL HeatWave TPC-DS benchmarks demonstrate that Amazon Redshift, Snowflake, Azure Synapse and Google BigQuery are all slower and more expensive. It’s rather clear who’s innovating in cloud databases and who’s being complacent.” Feedback from analysts
30 • The best MySQL releases ever, as widely acknowledged by the MySQL Community • Commitment to open source, with continued code contributions (as opposed to AWS, who forked MySQL to create the closed source Aurora) • A constant stream of innovation, with new products and services—including MySQL HeatWave—helping users and customers tackle the new challenges that they are facing • Unparalleled MySQL Database expertise from Oracle, the leading database company Oracle is committed to MySQL’s success