Hadoop is an open source software from Apache, supporting distributed processing and data storage. Hadoop is popular for its scalability, reliability, and functionality available across commoditized hardware.
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Presto
Score 10.0 out of 10
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Presto is an open source SQL query engine designed to run queries on data stored in Hadoop or in traditional databases.
Teradata supported development of Presto followed the acquisition of Hadapt and Revelytix.
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Pricing
Apache Hadoop
Presto
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Pricing Offerings
Hadoop
Presto
Free Trial
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No
Free/Freemium Version
Yes
No
Premium Consulting/Integration Services
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No
Entry-level Setup Fee
No setup fee
No setup fee
Additional Details
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Community Pulse
Apache Hadoop
Presto
Considered Both Products
Hadoop
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Chose Apache Hadoop
Spark is a good alternative to Hadoop that can have faster querying and processing performance and can offer more flexibility in terms of applications that it can support.
Google BigQuery has also been a great alternative and is especially great in terms of ease of use. The …
Altogether, I want to say that Apache Hadoop is well-suited to a larger and unstructured data flow like an aggregation of web traffic or even advertising. I think Apache Hadoop is great when you literally have petabytes of data that need to be stored and processed on an ongoing basis. Also, I would recommend that the software should be supplemented with a faster and interactive database for a better querying service. Lastly, it's very cost-effective so it is good to give it a shot before coming to any conclusion.
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
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.
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.
Hadoop is organization-independent and can be used for various purposes ranging from archiving to reporting and can make use of economic, commodity hardware. There is also a lot of saving in terms of licensing costs - since most of the Hadoop ecosystem is available as open-source and is free
As Hadoop enterprise licensed version is quite fine tuned and easy to use makes it good choice for Hadoop administrators. It’s scalability and integration with Kerberos is good option for authentication and authorisation. installation can be improved. logging can be improved so that it become easier for debugging purposes. parallel processing of data is achieved easily.
It's a great value for what you pay, and most Data Base Administrators (DBAs) can walk in and use it without substantial training. I tend to dabble on the analyst side, so querying the data I need feels like it can take forever, especially on higher traffic days like Monday.
Not used any other product than Hadoop and I don't think our company will switch to any other product, as Hadoop is providing excellent results. Our company is growing rapidly, Hadoop helps to keep up our performance and meet customer expectations. We also use HDFS which provides very high bandwidth to support MapReduce workloads.
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.
There are many advantages of Hadoop as first it has made the management and processing of extremely colossal data very easy and has simplified the lives of so many people including me.
Hadoop is quite interesting due to its new and improved features plus innovative functions.