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Coveo Relevance Cloud vs. Elasticsearch vs. Redis Software

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    Overview
    ProductRatingMost Used ByProduct SummaryStarting Price

    Coveo Relevance Cloud

    Score7 out of 10
    N/ACoveo is an enterprise search technology which can index data on disparate cloud systems making it easier to retrieve. It has integrated plug-ins for Salesforce.com, Sitecore CEP, and Microsoft Outlook and SharePoint.

    $600

    per month

    Elasticsearch

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

    $16

    per month

    Redis Software

    Score8.8 out of 10
    N/ARedis is an open source in-memory data structure server and NoSQL database.N/A
    Pricing
    Coveo Relevance CloudElasticsearchRedis Software
    Editions & Modules
    Base
    $600
    per month
    Pro
    $1,320
    per month
    Standard
    $16.00
    per month
    Gold
    $19.00
    per month
    Platinum
    $22.00
    per month
    Enterprise
    Contact Sales
    No answers on this topic
    Offerings
    Pricing Offerings
    Coveo Relevance CloudElasticsearchRedis Software
    Free Trial
    YesNoYes
    Free/Freemium Version
    NoNoYes
    Premium Consulting/Integration Services
    YesNoYes
    Entry-level Setup FeeOptionalNo setup feeOptional
    Additional Details
    More Pricing Information
    Community Pulse
    Coveo Relevance CloudElasticsearchRedis Software
    Considered Multiple Products
    Coveo
    No answer on this topic
    Elastic
    Chose Elasticsearch
    Elasticsearch has a steep learning curve, but it is the best in terms of customization and use cases it can cover most of the business needs. The other tools might be easier to integrate with and start seeing results, but you will end up having issues when you need customized …
    Incentivized
    Chose Elasticsearch
    All database systems have things they are good at, and things they aren't as good at. Riak/SOLR is great as a K/V store, but SOLR cannot handle requests as fast as ElasticSearch. In fact, SOLR is the reason we had to migrate to ElasticSearch.
    Redis is great at SET operations …
    Incentivized
    Chose Elasticsearch
    ES does not compete with the above packages but compliments them. By automating and mining logs, you are able to get a sense of the business process, marketing data or whatever else you need to capture and mine. The potential energy stored within Elasticsearch makes it a great …
    Incentivized
    Chose Elasticsearch
    Power and simplicity along with performance.
    Incentivized
    Chose Elasticsearch
    We found Elasticsearch to be the fastest in querying text based data, allowing us to significantly speed up our APIs.
    Incentivized
    Chose Elasticsearch
    We first started out experimenting with PostgreSQL's fulltext searching capabilities for our project. As our dataset grew, PostgreSQL began to slow down too much for our purposes. The simple fact that Elasticsearch has built-in clustering and replication was enough for us to …
    Incentivized
    Redis
    Chose Redis Software
    We divide projects between Redis and Elasticsearch Service. In some parts or modules one of these two databases fit better than the other.
    Incentivized
    Chose Redis Software
    Redis is great at set operations and is very fast. Riak is a fast long-term data store, but it is expensive to run. MongoDB is good for small, quick projects. Elasticsearch is great at indexing and searching. Choose the right tool for the job, and don't be afraid to …
    Incentivized
    Chose Redis Software
    I can't evaluate. I didn't use them personally.
    Incentivized
    Chose Redis Software
    We have also done lot of research over NoSQL databases to find what is a good fit for our application. We finally decided to use Redis because:
    1. It requires very minimal hardware to set up.
    2. Supports key-value structure.
    Incentivized
    Chose Redis Software
    We chose Redis over Memcached and Couchbase for its performance, cost, support, and ease of use. Couchbase probably would have worked as well, but it seemed a bit overkill for our use cases.
    Incentivized
    Chose Redis Software
    Memcached is a much more simple caching layer than Redis. Some features that make Redis come out above memcached include:
    • Data structures. Redis offers plenty of useful data structures (lists, hashmaps, sets, etc) where memcached is basically just strings.
    • Data persistence. Redis …
    Incentivized
    Key User Insights
    Would buy again
    No answers on this topic
    82%
    Would buy again
    14 Answers
    100%
    Would buy again
    6 Answers
    Delivers good value for the price
    No answers on this topic
    100%
    Delivers good value for the price
    16 Answers
    100%
    Delivers good value for the price
    6 Answers
    Happy with the feature set
    No answers on this topic
    100%
    Happy with the feature set
    17 Answers
    100%
    Happy with the feature set
    6 Answers
    Lived up to sales and marketing promises
    No answers on this topic
    100%
    Lived up to sales and marketing promises
    13 Answers
    100%
    Lived up to sales and marketing promises
    6 Answers
    Implementation went as expected
    No answers on this topic
    87%
    Implementation went as expected
    13 Answers
    100%
    Implementation went as expected
    6 Answers
    Best Alternatives
    Coveo Relevance CloudElasticsearchRedis Software
    Small Businesses
    Elasticsearch
    Score8.5 out of 10
    Apache Solr
    Score7.9 out of 10
    No answers on this topic
    Medium-sized Companies
    Elasticsearch
    Score8.5 out of 10
    IBM Watson Discovery
    Score9 out of 10
    No answers on this topic
    Enterprises
    Amazon CloudSearch
    Score8.5 out of 10
    Amazon CloudSearch
    Score8.5 out of 10
    No answers on this topic
    All AlternativesView all alternativesView all alternativesView all alternatives
    User Ratings
    Coveo Relevance CloudElasticsearchRedis Software
    Likelihood to Recommend
    10.0
    (4 ratings)
    9.0
    (48 ratings)
    8.0
    (76 ratings)
    Likelihood to Renew
    6.6
    (2 ratings)
    10.0
    (1 ratings)
    8.7
    (12 ratings)
    Usability
    -
    (0 ratings)
    10.0
    (1 ratings)
    9.0
    (6 ratings)
    Support Rating
    -
    (0 ratings)
    7.8
    (9 ratings)
    8.7
    (5 ratings)
    Implementation Rating
    -
    (0 ratings)
    9.0
    (1 ratings)
    7.3
    (1 ratings)
    User Testimonials
    Coveo Relevance CloudElasticsearchRedis Software
    Likelihood to Recommend
    Coveo
    Coveo Relevance Cloud is a great solution to implement into Salesforce to provide Knowledge-Centered Support, Enhancements to a Customer Community, to provide sales aids, or to complement your customized app in Salesforce.
    Incentivized
    Read full review
    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
    Redis
    Redis has been a great investment for our organization as we needed a solution for high speed data caching. The ramp up and integration was quite easy. Redis handles automatic failover internally, so no crashes provides high availability. On the fly scaling scale to more/less cores and memory as and when needed.
    Incentivized
    Read full review
    Pros
    Coveo
    • Coveo is fast, search results come up quick (though it's not always great).
    • Not much complexity to run.
    • Coveo is implemented within our portal and doesn't require extra steps to use it.
    Incentivized
    Read full review
    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
    Redis
    • Easy for developers to understand. Unlike Riak, which I've used in the past, it's fast without having to worry about eventual consistency.
    • Reliable. With a proper multi-node configuration, it can handle failover instantly.
    • Configurable. We primarily still use Memcache for caching but one of the teams uses Redis for both long-term storage and temporary expiry keys without taking on another external dependency.
    • Fast. We process tens of thousands of RPS and it doesn't skip a beat.
    Incentivized
    Read full review
    Cons
    Coveo
    • It would be great if Coveo 6 allowed you to rebuild indexes from a certain subtree instead of needing to rebuild the entire tree to see changes. This functionality was added in Coveo 7 and is very useful.
    • In Coveo 6, integration with Sitecore is more difficult than one would expect. This integration is much improved in Coveo 7.
    • I have seen cases where an exception thrown when crawling a specific document will cause the indexing to stop completely. I believe this only happens in implementations using custom faceting but it could be handled more efficiently if the trouble document was skipped and the indexing could continue.
    • Relevancy ranking editor is good but not as powerful as GSA. GSA offers a self-learning scorer which automatically analyzes user behavior and the specific links that users click on for specific queries to fine tune relevance and scoring.
    • We've ran into issues on multiple clients with Sitecore items being indexed multiple times in Sitecore 7 and Coveo 7. The fix Coveo suggested was to upgrade our Sitecore version and Coveo but unfortunately this didn't resolve our issue. After months of testing we were finally able to resolve this by implementing our own CoveoItemCrawler to get around the issue (based on https://developers.coveo.com/display/public/SC201404/Items+in+the+Same+Language+Gets+Indexed+Multiple+Times;jsessionid=3C1A2AE33540E0A0B8BB52BA3A64AF70).
    • Integration with RabbitMQ in Coveo 7 seems error prone. We often see the error "The AMQP operation was interrupted" and on occasion, need to restart the Coveo service to get this operating again. In some extreme cases, we have also had to restart the server because of issues when attempting to restart the Coveo service.
    Incentivized
    Read full review
    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
    Redis
    • We had some difficulty scaling Redis without it becoming prohibitively expensive.
    • Redis has very simple search capabilities, which means its not suitable for all use cases.
    • Redis doesn't have good native support for storing data in object form and many libraries built over it return data as a string, meaning you need build your own serialization layer over it.
    Incentivized
    Read full review
    Likelihood to Renew
    Coveo
    This question is not applicable to me
    Incentivized
    Read full review
    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
    Redis
    We will definitely continue using Redis because: 1. It is free and open source. 2. We already use it in so many applications, it will be hard for us to let go. 3. There isn't another competitive product that we know of that gives a better performance. 4. We never had any major issues with Redis, so no point turning our backs.
    Incentivized
    Read full review
    Usability
    Coveo
    No answers on this topic
    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
    Redis
    It is quite simple to set up for the purpose of managing user sessions in the backend. It can be easily integrated with other products or technologies, such as Spring in Java. If you need to actually display the data stored in Redis in your application this is a bit difficult to understand initially but is possible.
    Incentivized
    Read full review
    Support Rating
    Coveo
    No answers on this topic
    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
    Redis
    The support team has always been excellent in handling our mostly questions, rarely problems. They are responsive, find the solution and get us moving forward again. I have never had to escalate a case with them. They have always solved our problems in a very timely manner. I highly commend the support team.
    Incentivized
    Read full review
    Implementation Rating
    Coveo
    No answers on this topic
    Elastic
    Do not mix data and master roles. Dedicate at least 3 nodes just for Master
    Incentivized
    Read full review
    Redis
    Whitelisting of the AWS lambda functions.
    Incentivized
    Read full review
    Alternatives Considered
    Coveo
    No answers on this topic
    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
    Redis
    We are big users of MySQL and PostgreSQL. We were looking at replacing our aging web page caching technology and found that we could do it in SQL, but there was a NoSQL movement happening at the time. We dabbled a bit in the NoSQL scene just to get an idea of what it was about and whether it was for us. We tried a bunch, but I can only seem to remember Mongo and Couch. Mongo had big issues early on that drove us to Redis and we couldn't quite figure out how to deploy couch.
    Incentivized
    Read full review
    Return on Investment
    Coveo
    • Quick to find things in a massive database when needed.
    • Results need to be more concise - sometimes we spend more time looking for the right file than if we were to just search amongst our own networks instead.
    • Coveo is not always the most useful but does its job when general information is needed.
    Incentivized
    Read full review
    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
    Redis
    • Redis has helped us increase our throughput and server data to a growing amount of traffic while keeping our app fast. We couldn't have grown without the ability to easily cache data that Redis provides.
    • Redis has helped us decrease the load on our database. By being able to scale up and cache important data, we reduce the load on our database reducing costs and infra issues.
    • Running a Redis node on something like AWS can be costly, but it is often a requirement for scaling a company. If you need data quickly and your business is already a positive ROI, Redis is worth the investment.
    Incentivized
    Read full review
    ScreenShots

    Redis Software Screenshots

    Screenshot of Database configurationScreenshot of Database metricsScreenshot of DatabasesScreenshot of NodesScreenshot of Alerts