Kognitio vs. MySQL Heatwave

What you have are different strategies for data encoding, which makes the process quite flexible, it is perfectly done so that a joint and collaborative work can be carried out, this information analyzed in large quantities, is extremely vital for the company, by giving it the correct and timely reading

Incentivized

If you need a highly performant database, which is much faster than a conventional RDBMS, without worrying about infrastructure scaling, performance tuning, and query optimization, go for MySQL Heatwave. This is the best in the market. It is also very secure and reliable. Regular backups ensure that your data is safe and consistent always.

Incentivized

• Ultra fast query results.
• IN Memory Database.
• Easy integration to reporting services.

Incentivized

• Data mining
• Data analysis
• Parallel computing

Incentivized

• Multiple Query facilitation that can be user friendly.
• Easy workflows to implement.
• Historical query loader.

Incentivized

• 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

Incentivized

The understandable and complete tables and graphs, the cleaning methods and the way of encrypting the data are quite feasible, which does not help to prepare our data, it helps that the data that is thrown as results is separated from each other, the process prior to structuring requires high-level advice and is somewhat time-consuming, there is a risk that they overwrite the data themselves by accident at a later time

Incentivized

We have not used other platforms. So, after a market survey on price, support and facilities, we have decided to go for MySQL Heatwave platform. Which integrates many technologies and provide best support, service and pricing. Also, it provides access to database. The speed of the execution is very high.

Incentivized

• Faster data analysis.
• Analytical reports are now easy to create.
• Company strategy in terms of overall are improved.

Incentivized

• 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

Incentivized