Apache Hadoop vs. Elasticsearch

Overview
ProductRatingMost Used ByProduct SummaryStarting Price
Hadoop
Score 7.1 out of 10
N/A
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.N/A
Elasticsearch
Score 8.4 out of 10
N/A
Elasticsearch is an enterprise search tool from Elastic in Mountain View, California.
$16
per month
Pricing
Apache HadoopElasticsearch
Editions & Modules
No answers on this topic
Standard
$16.00
per month
Gold
$19.00
per month
Platinum
$22.00
per month
Enterprise
Contact Sales
Offerings
Pricing Offerings
HadoopElasticsearch
Free Trial
NoNo
Free/Freemium Version
YesNo
Premium Consulting/Integration Services
NoNo
Entry-level Setup FeeNo setup feeNo setup fee
Additional Details
More Pricing Information
Community Pulse
Apache HadoopElasticsearch
Considered Both Products
Hadoop

No answer on this topic

Elasticsearch
Chose Elasticsearch
Elasticsearch is DevOps friendly; it is easy for installation and management of a node/cluster. It is very friendly for developers by providing the REST API out of the box, reducing the development time.
Chose Elasticsearch
We have used Solr. Elastic Search aggregations is what made us move to elastic search initially.
Chose Elasticsearch
Ability to support JSON queries, Percolator, ease to set up and custom routing were some of the reasons why we decided to use Elasticsearch instead of Solr.
Top Pros
Top Cons
Best Alternatives
Apache HadoopElasticsearch
Small Businesses

No answers on this topic

Algolia
Algolia
Score 9.0 out of 10
Medium-sized Companies
Cloudera Manager
Cloudera Manager
Score 9.9 out of 10
Guru
Guru
Score 9.0 out of 10
Enterprises
IBM Analytics Engine
IBM Analytics Engine
Score 8.7 out of 10
Guru
Guru
Score 9.0 out of 10
All AlternativesView all alternativesView all alternatives
User Ratings
Apache HadoopElasticsearch
Likelihood to Recommend
8.9
(36 ratings)
9.0
(47 ratings)
Likelihood to Renew
9.6
(8 ratings)
10.0
(1 ratings)
Usability
8.5
(5 ratings)
10.0
(1 ratings)
Performance
8.0
(1 ratings)
-
(0 ratings)
Support Rating
7.5
(3 ratings)
7.8
(9 ratings)
Online Training
6.1
(2 ratings)
-
(0 ratings)
Implementation Rating
-
(0 ratings)
9.0
(1 ratings)
User Testimonials
Apache HadoopElasticsearch
Likelihood to Recommend
Apache
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.
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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.
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Pros
Apache
  • Handles large amounts of unstructured data well, for business level purposes
  • Is a good catchall because of this design, i.e. what does not fit into our vertical tables fits here.
  • Decent for large ETL pipelines and logging free-for-alls because of this, also.
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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.
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Cons
Apache
  • Less organizational support system. Bugs need to be fixed and outside help take a long time to push updates
  • Not for small data sets
  • Data security needs to be ramped up
  • Failure in NameNode has no replication which takes a lot of time to recover
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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
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Likelihood to Renew
Apache
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
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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.
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Usability
Apache
Great! Hadoop has an easy to use interface that mimics most other data warehouses. You can access your data via SQL and have it display in a terminal before exporting it to your business intelligence platform of choice. Of course, for smaller data sets, you can also export it to Microsoft Excel.
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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.
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Support Rating
Apache
We went with a third party for support, i.e., consultant. Had we gone with Azure or Cloudera, we would have obtained support directly from the vendor. my rating is more on the third party we selected and doesn't reflect the overall support available for Hadoop. I think we could have done better in our selection process, however, we were trying to use an already approved vendor within our organization. There is plenty of self-help available for Hadoop online.
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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.
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Online Training
Apache
Hadoop is a complex topic and best suited for classrom training. Online training are a waste of time and money.
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Elastic
No answers on this topic
Implementation Rating
Apache
No answers on this topic
Elastic
Do not mix data and master roles. Dedicate at least 3 nodes just for Master
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Alternatives Considered
Apache
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.
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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.
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Return on Investment
Apache
  • 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.
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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.
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