InterSystems IRIS vs. Presto

Intersystems IRIS is a really great tool for Interoperability. It has so many capabilities out of the box and then such a great developer community on top of that, that there are really no limits to what you can do in terms of data manipulation and translation. Personally I find it to be a great tool if you are looking for Interoperability software.

Incentivized

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

• Connecting with mutliple vendor platforms and systems allowing us to consume and provide data as needed.
• Allowed us to implement our own RESTful api engine to server data to our internal applications.
• Setting up their recommendations for high availability allow us to perform server maintenance with minimal down time to our users.

• 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

• Enhanced documentation, more comprehensive and user-friendly documentation, including detailed tutorials and examples
• Improving compatibility and integrations with others programming languages
• Introducing tools and techniques to optimize the performance of ObjectScript applications, such as profiling tools, performance monitoring utilities, and code optimization guidelines
• A better compatibility with Python libraries

• 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

It could do with some additional support for languages and frameworks that are widely used by developers today. For example, it could also integrate the use of AI Coding agents or AI tools to speed up application development processes. It could also include better SSH support to allow developers to remotely edit and maintain applications.

The support team is the best in the world. All you need they can help you. The documentation is very good, but the support team can help you in less than 24h (some hours if it's very urgent).

Also, there is a great developers team in a good community that can help you in several languages (English, Spanish, Japanese, Portuguese, etc.).

Will done based on a proper planning, so this will makes execution more easier and better.

We are using InterSystems IRIS [especially] for database operations as the query performance is really good for [a large] amount of customer data. You can easily integrate for any application like web, desktop, and many more. It also provides BI functionality which is also very easy to implement using InterSystems IRIS[.]

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

• Very Fast and scalable software to deal with big data flow, safe and robust.
• The studio IDE is quite old fashion and lacks a few facilities
• amazing for complex data consumption, its milyi-model capability wich allows multiple different models for a single set of codes.

• 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