Elasticsearch is an enterprise search tool from Elastic in Mountain View, California.
$16
per month
MongoDB
Score 7.9 out of 10
N/A
MongoDB is an open source document-oriented database system. It is part of the NoSQL family of database systems. Instead of storing data in tables as is done in a "classical" relational database, MongoDB stores structured data as JSON-like documents with dynamic schemas (MongoDB calls the format BSON), making the integration of data in certain types of applications easier and faster.
$0.10
million reads
Pricing
Elasticsearch
MongoDB
Editions & Modules
Standard
$16.00
per month
Gold
$19.00
per month
Platinum
$22.00
per month
Enterprise
Contact Sales
Shared
$0
per month
Serverless
$0.10million reads
million reads
Dedicated
$57
per month
Offerings
Pricing Offerings
Elasticsearch
MongoDB
Free Trial
No
Yes
Free/Freemium Version
No
Yes
Premium Consulting/Integration Services
No
No
Entry-level Setup Fee
No setup fee
No setup fee
Additional Details
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Fully managed, global cloud database on AWS, Azure, and GCP
Even when sphinx base code is on c++ and they obtain a great performance from it, even when they have a set of plugins that allow to integrate with common database systems like MySQL, Elasticsearch is on top of license and all their experience on search. It also provides a long …
Other services, such as Alienvault or MongoDB, are not designed to integrate as well with parsing log data. Graphite was much more difficult to work into an usable product as it does not integrate as easily with log parsing plugins. Elasticsearch had the right features to …
When we first evaluated Elasticsearch, we compared it with alternatives like traditional RDBMS products (Postgres, MySQL) as well as other noSQL solutions like Cassandra & MongoDB. For our use case, Elasticsearch delivered on two fronts. First, we got a world-class search …
Elasticsearch is the most well-known and supported free data platform that we identified. We are taking advantage of community knowledge and practices. In terms of flexibility and breadth of use cases no other competitor came close to Elasticsearch. We've tried Solr in the past …
Elasticsearch and Solr are both based on Lucene, but the user community for Elasticsearch is much stronger, and setting up a cluster is easier. Splunk is very well suited for Log indexing and searching but is not nearly as flexible as Elasticsearch. Couchbase is a great NoSQL …
Search and analytics capabilities of Elasticsearch are superior to its competitors. Being open source, it is a cheaper and faster solution than other competitors. Installation is straightforward and it can be potentially deployed anywhere and everywhere! There is no need for …
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 …
Team Lead Xactimate Online Xactware Solutions, Inc
Chose Elasticsearch
The only other competitor we researched was mongo as some of our table information is stored in an XML file, but as we were doing searching we gravitated towards Elasticsearch. We knew mongo had some of the qualifications for what we wanted, but went with Elasticsearch for …
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.
For our application, ElasticSearch fulfilled all the criteria we were looking for. Something that's easy to scale and flexible. I think ElasticSearch works better that Solr with modern real-time search applications. Also, ElasticSearch is easy to integrate with. ElasticSearch …
Your default choice should not be MongoDB in my opinion. Most user-facing systems are relational by nature so a well known and reliable SQL database would be easier to maintain and simpler to develop long term. If you highly value speed of development go with Firebase. If you …
MongoDB and Cassandra are both database system from the NoSQL family. MongoDB can be used in lots of use cases while Cassandra has a specific usage. There are some features that MongoDB provides efficiently while Cassandra doesn't and vice-versa. Like, you can update the data …
The way MongoDB handles the data is unique and the indexing of data is powerful.
Verified User
Professional
Chose MongoDB
Cassandra: may be better for bigger use cases, in PB range, due to our use cases being slightly smaller, we did not need this, but we highly rely on efficient indexing, and low latency, which seemed to be better based on our testing in Mongodb. Couchbase Server: Document …