#1 most frequent
United States of America
50.0%5 installations of 10
What is MySQL Heatwave?
HeatWave is an in-memory query accelerator developed for Oracle MySQL Database Service. It’s a massively parallel, hybrid, columnar, query-processing engine with algorithms for distributed query processing that provide high performance for queries.
Categories & Use Cases
Videos
Who Buys & Uses MySQL Heatwave
#2 most frequent
Chile
20.0%2 installations of 10
#3 most frequent
India
20.0%2 installations of 10
MySQL Heatwave is the best data handling platform
Use Cases and Deployment Scope
I use MySQL Heatwave in my organization for data mining and data analysis. It provides the facilities for data analysis and free away from the use of other data analysis tool separately. It is high performance and competative tool which uses parallel computing. This is very economical tool in context of price.
Pros
- Data mining
- Data analysis
- Parallel computing
Cons
- This is best tool. There is no as such improvement required at this stage
- Flexibility in pricing
- Cost effective
Most Important Features
- Database access
- Data mining
- Data analysis
Return on Investment
- Cost effective
- More pricing options
- High performance
Other Software Used
MySQL Heatwave, MySQL Heatwave, MySQL Heatwave
Speed and Reliability with MySQL Heatwave
Use Cases and Deployment Scope
For our analytics and Machine learning workloads, we need an extremely fast and reliable Database Management System and the same need is fulfilled by MySQL Heatwave. MySQL Heatwave is so fast that we don't have to move our data from MySQL RDBMS to another data warehouse system such as Databricks, which was an added workload for us. MySQL Heatwave has made our analytics work extremely efficient.
Pros
- Orders of magnitude faster than vanilla MySQL Heatwave
- Analytics and ML Workloads can be directly integrated
- Available as a managed service on Oracle Cloud
- The JDBC interface is consistent with other databases
- On Demand Scalability
- MySQL Autopilot abstracts away most of the configuration with regards to query tuning and optimization
Cons
- Pricing can be a concern if not configured properly
- Not available as a standalone or on premise offering. Only available through OCI
- No Jobs interface like that in Databricks with Spark and Delta Lake
Most Important Features
- MySQL Heatwave Autopilot for automated configuration and performance tuning
- Regular backups
- Speed of query execution
- Auto scaling of underlying infrastructure
Return on Investment
- We no longer have to write data pipelines in Spark anymore for executing ML/Analytics Workloads
- Execution time of the analytics platforms has reduced considerably
- Overall time to market has gone down drastically
Alternatives Considered
Databricks Lakehouse Platform (Unified Analytics Platform) and Cloudera Data Platform
Other Software Used
Oracle Cloud Infrastructure
