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    Overview
    ProductRatingMost Used ByProduct SummaryStarting Price

    Elasticsearch

    Score8.5 out of 10
    N/AElasticsearch is an enterprise search tool from Elastic in Mountain View, California.

    $16

    per month

    Pinecone

    Score8.9 out of 10
    N/APinecone is a fully managed vector database that makes it easy to add vector search to production applications. It combines state-of-the-art vector search libraries, advanced features such as filtering, and distributed infrastructure to provide high performance and reliability at any scale.

    $0.07

    per hour

    Pricing
    ElasticsearchPinecone
    Editions & Modules
    Standard
    $16.00
    per month
    Gold
    $19.00
    per month
    Platinum
    $22.00
    per month
    Enterprise
    Contact Sales
    Enterprise
    $0.01
    per hour
    Offerings
    Pricing Offerings
    ElasticsearchPinecone
    Free Trial
    NoNo
    Free/Freemium Version
    NoYes
    Premium Consulting/Integration Services
    NoNo
    Entry-level Setup FeeNo setup feeNo setup fee
    Additional Details——
    More Pricing Information
    Community Pulse
    ElasticsearchPinecone
    Considered Both Products
    Elastic
    No answer on this topic
    Pinecone
    No answer on this topic
    Key User Insights
    Would buy again
    82%
    Would buy again
    14 Answers
    No answers on this topic
    Delivers good value for the price
    100%
    Delivers good value for the price
    16 Answers
    No answers on this topic
    Happy with the feature set
    100%
    Happy with the feature set
    17 Answers
    No answers on this topic
    Lived up to sales and marketing promises
    100%
    Lived up to sales and marketing promises
    13 Answers
    No answers on this topic
    Implementation went as expected
    87%
    Implementation went as expected
    13 Answers
    No answers on this topic
    Features
    ElasticsearchPinecone
    Vector Database
    Comparison of Vector Database features of Elasticsearch and Pinecone
    Feature
    Elasticsearch
    -
    Ratings
    Pinecone
    7.5
    1 Ratings
    5% below category average
    Vector Data Connection00 Ratings10.01 Ratings
    Attribute Management00 Ratings10.01 Ratings
    Data Import/Export00 Ratings5.01 Ratings
    Data Sharing and Collaboration00 Ratings5.01 Ratings
    Best Alternatives
    ElasticsearchPinecone
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    Apache Solr
    Score7.9 out of 10
    Astra DB, now part of IBM watsonx.data
    Score8.8 out of 10
    Medium-sized Companies
    IBM Watson Discovery
    Score9 out of 10
    Astra DB, now part of IBM watsonx.data
    Score8.8 out of 10
    Enterprises
    Amazon CloudSearch
    Score8.5 out of 10
    No answers on this topic
    All AlternativesView all alternativesView all alternatives
    User Ratings
    ElasticsearchPinecone
    Likelihood to Recommend
    9.0
    (48 ratings)
    10.0
    (1 ratings)
    Likelihood to Renew
    10.0
    (1 ratings)
    -
    (0 ratings)
    Usability
    10.0
    (1 ratings)
    9.0
    (1 ratings)
    Support Rating
    7.8
    (9 ratings)
    -
    (0 ratings)
    Implementation Rating
    9.0
    (1 ratings)
    -
    (0 ratings)
    User Testimonials
    ElasticsearchPinecone
    Likelihood to Recommend
    Elastic
    Elasticsearch is a really scalable solution that can fit a lot of needs, but the bigger and/or those needs become, the more understanding & infrastructure you will need for your instance to be running correctly. Elasticsearch is not problem-free - you can get yourself in a lot of trouble if you are not following good practices and/or if are not managing the cluster correctly. Licensing is a big decision point here as Elasticsearch is a middleware component - be sure to read the licensing agreement of the version you want to try before you commit to it. Same goes for long-term support - be sure to keep yourself in the know for this aspect you may end up stuck with an unpatched version for years.
    Incentivized
    Read full review
    Pinecone
    Similarity search and ranking are fundamental capabilities, and Pinecone just has this nailed. Almost every application, especially those that talk to LLMs, can use this feature, and there is no reason to reinvent it or use anything more complicated or "full stack" than Pinecone. Pinecone is a powerful tool in this space.
    Incentivized
    Read full review
    Pros
    Elastic
    • As I mentioned before, Elasticsearch's flexible data model is unparalleled. You can nest fields as deeply as you want, have as many fields as you want, but whatever you want in those fields (as long as it stays the same type), and all of it will be searchable and you don't need to even declare a schema beforehand!
    • Elastic, the company behind Elasticsearch, is super strong financially and they have a great team of devs and product managers working on Elasticsearch. When I first started using ES 3 years ago, I was 90% impressed and knew it would be a good fit. 3 years later, I am 200% impressed and blown away by how far it has come and gotten even better. If there are features that are missing or you don't think it's fast enough right now, I bet it'll be suitable next year because the team behind it is so dang fast!
    • Elasticsearch is really, really stable. It takes a lot to bring down a cluster. It's self-balancing algorithms, leader-election system, self-healing properties are state of the art. We've never seen network failures or hard-drive corruption or CPU bugs bring down an ES cluster.
    Incentivized
    Read full review
    Pinecone
    • Adding a vector (of course) and we are able to add arbitrary metadata with it.
    • Similarity search, ranking and metadata retrieval.
    • The webui/console tools are nice when debugging/confirming something. Above-average tooling in this regard.
    Incentivized
    Read full review
    Cons
    Elastic
    • Joining data requires duplicate de-normalized documents that make parent child relationships. It is hard and requires a lot of synchronizations
    • Tracking errors in the data in the logs can be hard, and sometimes recurring errors blow up the error logs
    • Schema changes require complete reindexing of an index
    Incentivized
    Read full review
    Pinecone
    • Pinecone has come a long way (we have been using it for years). While the tooling used to have some rough edges, I can't really complain these days.
    • Migrating an entire database from one AWS zone to another basically required a full data dump and reload. That could be improved. I have not tried AWS=>GCP=>Azure replications/migrations, but suspect they are not yet well supported, and that would be helpful.
    Incentivized
    Read full review
    Likelihood to Renew
    Elastic
    We're pretty heavily invested in ElasticSearch at this point, and there aren't any obvious negatives that would make us reconsider this decision.
    Incentivized
    Read full review
    Pinecone
    No answers on this topic
    Usability
    Elastic
    To get started with Elasticsearch, you don't have to get very involved in configuring what really is an incredibly complex system under the hood. You simply install the package, run the service, and you're immediately able to begin using it. You don't need to learn any sort of query language to add data to Elasticsearch or perform some basic searching. If you're used to any sort of RESTful API, getting started with Elasticsearch is a breeze. If you've never interacted with a RESTful API directly, the journey may be a little more bumpy. Overall, though, it's incredibly simple to use for what it's doing under the covers.
    Incentivized
    Read full review
    Pinecone
    It is lean and covers all the bases. I am sure there are one or two things that could be better, so 9 instead of 10.
    Incentivized
    Read full review
    Support Rating
    Elastic
    We've only used it as an opensource tooling. We did not purchase any additional support to roll out the elasticsearch software. When rolling out the application on our platform we've used the documentation which was available online. During our test phases we did not experience any bugs or issues so we did not rely on support at all.
    Incentivized
    Read full review
    Pinecone
    No answers on this topic
    Implementation Rating
    Elastic
    Do not mix data and master roles. Dedicate at least 3 nodes just for Master
    Incentivized
    Read full review
    Pinecone
    No answers on this topic
    Alternatives Considered
    Elastic
    As far as we are concerned, Elasticsearch is the gold standard and we have barely evaluated any alternatives. You could consider it an alternative to a relational or NoSQL database, so in cases where those suffice, you don't need Elasticsearch. But if you want powerful text-based search capabilities across large data sets, Elasticsearch is the way to go.
    Incentivized
    Read full review
    Pinecone
    We selected Pinecone because they had much more startup-friendly pricing.
    Incentivized
    Read full review
    Return on Investment
    Elastic
    • We have had great luck with implementing Elasticsearch for our search and analytics use cases.
    • While the operational burden is not minimal, operating a cluster of servers, using a custom query language, writing Elasticsearch-specific bulk insert code, the performance and the relative operational ease of Elasticsearch are unparalleled.
    • We've easily saved hundreds of thousands of dollars implementing Elasticsearch vs. RDBMS vs. other no-SQL solutions for our specific set of problems.
    Incentivized
    Read full review
    Pinecone
    • When our product had a primitive search, we were lambasted by users, and we embraced Pinecone to fill an urgent need for something better. Over the years, it has become a wired-in foundation for more than a few product features.
    • The money we didn't spend creating and maintaining something "like" Pinecone has been one of our best investments.
    Incentivized
    Read full review
    ScreenShots

    Pinecone Screenshots

    Screenshot of Pinecone App