Datadog vs. Elasticsearch

Overview
ProductRatingMost Used ByProduct SummaryStarting Price
Datadog
Score 8.4 out of 10
N/A
Datadog is a monitoring service for IT, Dev and Ops teams who write and run applications at scale, and want to turn the massive amounts of data produced by their apps, tools and services into actionable insight.
$0
Up to 5 hosts
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
DatadogElasticsearch
Editions & Modules
Free
$0
Up to 5 hosts
Log Management
$1.27
Per Million Log Events
Standard
$15/host
Up to 500 hosts
Infrastructure
$15.00
Per Host Per Month
APM
$31.00
Per Host Per Month
Enterprise
Custom
500+ hosts
Standard
$16.00
per month
Gold
$19.00
per month
Platinum
$22.00
per month
Enterprise
Contact Sales
Offerings
Pricing Offerings
DatadogElasticsearch
Free Trial
YesNo
Free/Freemium Version
NoNo
Premium Consulting/Integration Services
NoNo
Entry-level Setup FeeOptionalNo setup fee
Additional Details
More Pricing Information
Community Pulse
DatadogElasticsearch
Considered Both Products
Datadog

No answer on this topic

Elasticsearch
Chose Elasticsearch
From my perspective, there is nothing currently on the marker better than Datadog, but unfortunately, that's a pricey product, Elasticsearch deliver us part of Datadog functionalities being cheaper. Fluentd as a service (provided by the company behind Fluentd) looks like a …
Chose Elasticsearch
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 …
Chose Elasticsearch
I think Elasticseach works less great compared to Splunk. Mainly the way the Splunk search head works is vastly superior to the way the Elasticsearch query language works. Furthermore, the Splunk architecture is in my opinion easier to roll out and scale-up. Splunk also has a …
Top Pros
Top Cons
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DatadogElasticsearch
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User Ratings
DatadogElasticsearch
Likelihood to Recommend
9.1
(22 ratings)
9.0
(47 ratings)
Likelihood to Renew
-
(0 ratings)
10.0
(1 ratings)
Usability
10.0
(1 ratings)
10.0
(1 ratings)
Support Rating
8.9
(6 ratings)
7.8
(9 ratings)
Implementation Rating
-
(0 ratings)
9.0
(1 ratings)
User Testimonials
DatadogElasticsearch
Likelihood to Recommend
Datadog
DataDog Is well suited to all of the Infrastructure Monitoring Solutions, DB monitoring, and other Network monitoring also. It's not well suited because it cannot give perfect Infrastructure recommendations for our use case but also For example: If we are using AWS DB to monitor performance insights then Datadog is less effective there because AWS gives very niche recommendations.
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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
Datadog
  • APIs, the ability to interact with the data we pull into data dog is key. We port the information over to Servicenow, so the ability to pull everything into DataDog, then Servicenow, is a key component of our success here at Wayfair.
  • Simple Interface - clean, useful, effective. Allows users to use DataDog for one reason, get work done.
  • Lightweight agent on hosts
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.
Read full review
Cons
Datadog
  • We had a couple "integrations" that had some issues during setup, but Support addressed them very quickly
  • Unnecessary alerts about DataDog components...by the time I see them, they're almost always also fixed
  • I wish there was a DataDog mobile app that would have dedicated alerts (configurable per alert to override Do Not Disturb setting) instead of relying on emails notifications that could be overlooked in the midst of many incoming emails around the same time.
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
Read full review
Likelihood to Renew
Datadog
No answers on this topic
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.
Read full review
Usability
Datadog
The user interface is quite intuitive with the exception of the network map. As a deployer of software, it is trivial to setup.
Read full review
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
Datadog
The support team usually gets it right. We did have a rather complicate issue setting up monitoring on a domain controller. However, they are usually responsive and helpful over chat. The downside would be I don’t think they have any phone support. If that is important to you this might not be a good fit.
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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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Implementation Rating
Datadog
No answers on this topic
Elastic
Do not mix data and master roles. Dedicate at least 3 nodes just for Master
Read full review
Alternatives Considered
Datadog
We are still trying other products, but people still like Datadog. After setting up a dashboard, it's great for monitoring instances on Datadog. Also, the DevOps team had a good time setting up Datadog. It means Datadog was way easier to set up compared to those others.
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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
Datadog
  • Visibility into website issues and performance problems has improved our company communication.
  • Handling and detecting site issues faster has improved customer satisfaction and retention.
  • Configuration of the Datadog site can take a bit of time and we lost a bit of developer time during that process.
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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.
Read full review
ScreenShots

Datadog Screenshots

Screenshot of Out-of-the-box and easily customizable monitoring dashboards.Screenshot of Datadog is built to give visibility across teams. You can discuss issues in-context with production data, annotate changes and notify your team, see who responded to that alert before, and remember what was done to fix it.Screenshot of Datadog seamlessly unifies traces, metrics, and logs—the three pillars of observability.Screenshot of Collect monitoring data from across your entire stack with Datadog's 400+ built-in integrations.Screenshot of Datadog's Service Map decomposes your application into all its component services and draws the observed dependencies between these services in real timeScreenshot of Centralize log data from any source.