Presto vs. TimeXtender

Presto is for interactive simple queries, where Hive is for reliable processing. If you have a fact-dim join, presto is great..however for fact-fact joins presto is not the solution.. Presto is a great replacement for proprietary technology like Vertica

Incentivized

TimeXtender has worked really well with our customers who have different data sources using complex data types in large quantities requiring a DW-like solution that can consolidate all data sources at one-HUB. TimeXtender does this well, and provides automation capabilities, the ability to easily handle slowly changing dimensions, handing data lineage and data security very well. TimeXtender has the ability to be very customizable, allowing the HUB to grow as your business does. TimeXtender's customer support team is super helpful and will work with you throughout your implementation to make sure you reach success with the product. The ROI for timeXtender versus competing products (there aren't many that do what timeXtender does) shows the investment to be worthwhile for the majority of organizations in today's data-rich corporate world.

Incentivized

• Linking, embedding links and adding images is easy enough.
• Once you have become familiar with the interface, Presto becomes very quick & easy to use (but, you have to practice & repeat to know what you are doing - it is not as intuitive as one would hope).
• Organizing & design is fairly simple with click & drag parameters.

Incentivized

• It has the ability to create one dynamic 'DW' or source of truth, consolidating all data sources in one HUB.
• Ease of use, with a great UI that is easy to learn and adapt to.
• Ease/speed of complex implementation.

Incentivized

• Presto was not designed for large fact fact joins. This is by design as presto does not leverage disk and used memory for processing which in turn makes it fast.. However, this is a tradeoff..in an ideal world, people would like to use one system for all their use cases, and presto should get exhaustive by solving this problem.
• Resource allocation is not similar to YARN and presto has a priority queue based query resource allocation..so a query that takes long takes longer...this might be alleviated by giving some more control back to the user to define priority/override.
• UDF Support is not available in presto. You will have to write your own functions..while this is good for performance, it comes at a huge overhead of building exclusively for presto and not being interoperable with other systems like Hive, SparkSQL etc.

Incentivized

• Product Marketing: As implementers and resellers of this technology, we loved it. But, convincing clients who had not previously heard of TX/Discovery Hub was more difficult than it could have been if the company had a larger marketing force behind it.
• Relatively New to Market: it creates a learning curve for early implementers.
• More information should be published on timeXtender's website about product lines, including testimonials.

Incentivized

Presto is good for a templated design appeal. You cannot be too creative via this interface - but, the layout and options make the finalized visual product appealing to customers. The other design products I use are for different purposes and not really comparable to Presto.

Incentivized

For our clients, timeXtender was a much better solution. It offered a more cost-effective solution, easier integration, and better customer support for our complex client needs. The timeXtender team worked with us throughout the process to make sure we could create a success story that was repeatable for our clients, and they proved great partners.

Incentivized

• Presto has helped scale Uber's interactive data needs. We have migrated a lot out of proprietary tech like Vertica.
• Presto has helped build data driven applications on its stack than maintain a separate online/offline stack.
• Presto has helped us build data exploration tools by leveraging it's power of interactive and is immensely valuable for data scientists.

Incentivized