What users are saying about
170 Ratings
23 Ratings
170 Ratings
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Score 8.4 out of 100
23 Ratings
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Score 7.8 out of 100

Attribute Ratings

  • Logstash is rated higher in 1 area: Likelihood to Recommend

Likelihood to Recommend

9.8

Datadog

98%
19 Ratings
10.0

Logstash

100%
3 Ratings

Usability

10.0

Datadog

100%
1 Rating

Logstash

N/A
0 Ratings

Support Rating

8.9

Datadog

89%
10 Ratings

Logstash

N/A
0 Ratings

Likelihood to Recommend

Datadog

Datadog is a no-brainer for any environment that relies on multiple servers. Even for one server, it's so much better to use for monitoring and alert capability than anything else I remember looking at before we started using Datadog. Teams can even use it to track their progress of investigating an alert so multiple people aren't unknowingly looking into the same exact issue unnecessarily.
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Elastic

Perfect for projects where Elasticsearch makes sense: if you decide to employ ES in a project, then you will almost inevitably use LogStash, and you should anyways. Such projects would include: 1. Data Science (reading, recording or measure web-based Analytics, Metrics) 2. Web Scraping (which was one of our earlier projects involving LogStash) 3. Syslog-ng Management: While I did point out that it can be a bit of an electric boo-ga-loo in finding an errant configuration item, it is still worth it to implement Syslog-ng management via LogStash: being able to fine-tune your log messages and then pipe them to other sources, depending on the data being read in, is incredibly powerful, and I would say is exemplar of what modern Computer Science looks like: Less Specialization in mathematics, and more specialization in storing and recording data (i.e. Less Engineering, and more Design).
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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
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Elastic

  • Logstash design is definitely perfect for the use case of ELK. Logstash has "drivers" using which it can inject from virtually any source. This takes the headache from source to implement those "drivers" to store data to ES.
  • Logstash is fast, very fast. As per my observance, you don't need more than 1 or 2 servers for even big size projects.
  • Data in different shape, size, and formats? No worries, Logstash can handle it. It lets you write simple rules to programmatically take decisions real-time on data.
  • You can change your data on the fly! This is the CORE power of Logstash. The concept is similar to Kafka streams, the difference being the source and destination are application and ES respectively.
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Cons

Datadog

  • User interface could be improved in some areas, looking for host information and the agent install link takes a bit of time.
  • Configuration of the agent is generally done via a config file which is a pro and a con. It would be nice to have some UI to configure various agent options.
  • Billing isn't entirely straightforward, they could use more reports to figure out the source of your monthly costs.
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Elastic

  • Since it's a Java product, JVM tuning must be done for handling high-load.
  • The persistent queue feature is nice, but I feel like most companies would want to use Kafka as a general storage location for persistent messages for all consumers to use. Using some pipeline of "Kafka input -> filter plugins -> Kafka output" seems like a good solution for data enrichment without needing to maintain a custom Kafka consumer to accomplish a similar feature.
  • I would like to see more documentation around creating a distributed Logstash cluster because I imagine for high ingestion use cases, that would be necessary.
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Pricing Details

Datadog

Starting Price

$0 Up to 5 hosts

Editions & Modules

Datadog editions and modules pricing
EditionModules
Free$01
Standard$15/host2
EnterpriseCustom3
Infrastructure$15.004
Log Management$1.275
APM$31.006

Footnotes

  1. Up to 5 hosts
  2. Up to 500 hosts
  3. 500+ hosts
  4. Per Host Per Month
  5. Per Million Log Events
  6. Per Host Per Month

Offerings

Free Trial
Free/Freemium Version
Premium Consulting/Integration Services

Entry-level set up fee?

Optional

Additional Details

Logstash

Starting Price

Editions & Modules

Logstash editions and modules pricing
EditionModules

Footnotes

    Offerings

    Free Trial
    Free/Freemium Version
    Premium Consulting/Integration Services

    Entry-level set up fee?

    No setup fee

    Additional Details

    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.
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    Elastic

    No answers on this topic

    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

    No answers on this topic

    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

    MongoDB and Azure SQL Database are just that: Databases, and they allow you to pipe data into a database, which means that alot of the log filtering becomes a simple exercise of querying information from a DBMS. However, LogStash was chosen for it's ease of integration into our choice of using ELK Elasticsearch is an obvious inclusion: Using Logstash with it's native DevOps stack its really rational
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    Return on Investment

    Datadog

    • One of our critical production databases went down a couple of weeks back. Just because we had the Datadog monitoring enabled for that database, Datadog sent the alerts to PagerDuty and we were instantly notified via pager and email alert. We could act right away and bring up the database within a few mins.
    • Ability to create custom screenboards have allowed us to track the critical and warning alerts in front of our eyes all the time
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    Elastic

    • Positive: Learning curve was relatively easy for our team. We were up and running within a sprint.
    • Positive: Managing Logstash has generally been easy. We configure it, and usually, don't have to worry about misbehavior.
    • Negative: Updating/Rehydrating Logstash servers have been little challenging. We sometimes even loose data while Logstash is down. It requires more in-depth research and experiments to figure the fine-grained details.
    • Negative: This is now one more application/skill/server to manage. Like any other servers, it requires proper grooming or else you will get in trouble. This is also a single point of failure which can have the ability to make other servers useless if it is not running.
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    Screenshots

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