Apache Solr vs. Presto

Overview
ProductRatingMost Used ByProduct SummaryStarting Price
Apache Solr
Score 6.7 out of 10
N/A
Apache Solr is an open-source enterprise search server.N/A
Presto
Score 3.0 out of 10
N/A
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.N/A
Pricing
Apache SolrPresto
Editions & Modules
No answers on this topic
No answers on this topic
Offerings
Pricing Offerings
Apache SolrPresto
Free Trial
NoNo
Free/Freemium Version
NoNo
Premium Consulting/Integration Services
NoNo
Entry-level Setup FeeNo setup feeNo setup fee
Additional Details
More Pricing Information
Best Alternatives
Apache SolrPresto
Small Businesses
Algolia
Algolia
Score 8.8 out of 10
SingleStore
SingleStore
Score 9.7 out of 10
Medium-sized Companies
Guru
Guru
Score 9.0 out of 10
SingleStore
SingleStore
Score 9.7 out of 10
Enterprises
Guru
Guru
Score 9.0 out of 10
SingleStore
SingleStore
Score 9.7 out of 10
All AlternativesView all alternativesView all alternatives
User Ratings
Apache SolrPresto
Likelihood to Recommend
9.0
(10 ratings)
7.8
(2 ratings)
User Testimonials
Apache SolrPresto
Likelihood to Recommend
Apache
Solr spins up nicely and works effectively for small enterprise environments providing helpful mechanisms for fuzzy searches and facetted searching. For larger enterprises with complex business solutions you'll find the need to hire an expert Solr engineer to optimize the powerful platform to your needs. Internationalization is tricky with Solr and many hosting solutions may limit you to a latin character set.
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Open Source
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
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Pros
Apache
  • Easy to get started with Apache Solr. Whether it is tackling a setup issue or trying to learn some of the more advanced features, there are plenty of resources to help you out and get you going.
  • Performance. Apache Solr allows for a lot of custom tuning (if needed) and provides great out of the box performance for searching on large data sets.
  • Maintenance. After setting up Solr in a production environment there are plenty of tools provided to help you maintain and update your application. Apache Solr comes with great fault tolerance built in and has proven to be very reliable.
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Open Source
  • 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.
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Cons
Apache
  • These examples are due to the way we use Apache Solr. I think we have had the same problems with other NoSQL databases (but perhaps not the same solution). High data volumes of data and a lot of users were the causes.
  • We have lot of classifications and lot of data for each classification. This gave us several problems:
  • First: We couldn't keep all our data in Solr. Then we have all data in our MySQL DB and searching data in Solr. So we need to be sure to update and match the 2 databases in the same time.
  • Second: We needed several load balanced Solr databases.
  • Third: We needed to update all the databases and keep old data status.
  • If I don't speak about problems due to our lack of experience, the main Solr problem came from frequency of updates vs validation of several database. We encountered several locks due to this (our ops team didn't want to use real clustering, so all DB weren't updated). Problem messages were not always clear and we several days to understand the problems.
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Open Source
  • 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.
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Alternatives Considered
Apache
Apache Solr is a ready-to-use product addressing specific use cases such as keyword searches from a huge set of data documents.
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Open Source
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.
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Return on Investment
Apache
  • Improved response time in e-commerce websites.
  • Developer's job is easier with Apache Solr in use.
  • Customization in filtering and sorting is possible.
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Open Source
  • 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.
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