Bucket vs. LaunchDarkly

Overview
ProductRatingMost Used ByProduct SummaryStarting Price
Bucket
Score 0.0 out of 10
Mid-Size Companies (51-1,000 employees)
Bucket collects and combines feature engagement metrics and qualitative feedback in one place. It goes beyond feature adoption tracking by helping users to look at long-term retention and user satisfaction for every part of an application. Bucket is designed to solve the problem at the heart of SaaS products that disconnects the power of incentives and leaves developers at the mercy of their roadmap. Built for B2B SaaS, Bucket utilizes the STARS framework to…
$249
per month
LaunchDarkly
Score 7.9 out of 10
N/A
LaunchDarkly provides a feature management platform that enables DevOps and Product teams to use feature flags at scale. This allows for greater collaboration among team members, and increased usability testing before full-scale feature deployment.
$12
per month
Pricing
BucketLaunchDarkly
Editions & Modules
Pro
$249
per month
Business
$749
per month
Enterprise
custom
per month
Foundation
$12
per month per Service Connection per month, or $10 per 1k client-side MAU per mo
Enterprise
Custom
Guardian
Custom
Offerings
Pricing Offerings
BucketLaunchDarkly
Free Trial
YesYes
Free/Freemium Version
NoNo
Premium Consulting/Integration Services
NoYes
Entry-level Setup FeeNo setup feeOptional
Additional DetailsDiscount available on the Foundation plan for annual pricing.
More Pricing Information
Community Pulse
BucketLaunchDarkly
Best Alternatives
BucketLaunchDarkly
Small Businesses
GitLab
GitLab
Score 8.6 out of 10
GitLab
GitLab
Score 8.6 out of 10
Medium-sized Companies
GitLab
GitLab
Score 8.6 out of 10
GitLab
GitLab
Score 8.6 out of 10
Enterprises
GitLab
GitLab
Score 8.6 out of 10
GitLab
GitLab
Score 8.6 out of 10
All AlternativesView all alternativesView all alternatives
User Ratings
BucketLaunchDarkly
Likelihood to Recommend
-
(0 ratings)
10.0
(28 ratings)
Likelihood to Renew
-
(0 ratings)
7.0
(1 ratings)
Usability
-
(0 ratings)
7.4
(26 ratings)
Availability
-
(0 ratings)
10.0
(1 ratings)
Performance
-
(0 ratings)
8.1
(26 ratings)
Support Rating
-
(0 ratings)
10.0
(1 ratings)
Implementation Rating
-
(0 ratings)
9.0
(1 ratings)
Configurability
-
(0 ratings)
8.0
(1 ratings)
Ease of integration
-
(0 ratings)
8.0
(1 ratings)
Product Scalability
-
(0 ratings)
10.0
(1 ratings)
Vendor post-sale
-
(0 ratings)
8.0
(1 ratings)
Vendor pre-sale
-
(0 ratings)
10.0
(1 ratings)
User Testimonials
BucketLaunchDarkly
Likelihood to Recommend
Bucket
No answers on this topic
LaunchDarkly
If a new feature should be added but unsure of how it will actually work or how users will accept the new enhancement or change, this tool allows you test and measure initial results. This saves so much time and energy knowing the results before it is deployed and might have low user adoption or acceptance.
Read full review
Pros
Bucket
No answers on this topic
LaunchDarkly
  • A/B or Multi Variant Testing as a methodology to gather insight from customer usage. Experimentation as a feature within LaunchDarkly offers information around the success of one variant over another and whether the experiment has reached statistical significance.
  • Being able to decouple deployment of code from the release of a feature is hugely valuable.
  • Development teams are empowered to manage features within their production applications for reliability or testing purposes.
Read full review
Cons
Bucket
No answers on this topic
LaunchDarkly
  • Limited number of users on cheaper plans that is limiting our ability to audit log who is making changes.
  • Some of our engineers are confused between flags and segments and have set up items incorrectly.
  • Better documented support for React with Typescript.
Read full review
Likelihood to Renew
Bucket
No answers on this topic
LaunchDarkly
It fits out business case
Read full review
Usability
Bucket
No answers on this topic
LaunchDarkly
It's very easy to create new feature flags and set them properly. It is more difficult to get LaunchDarkly integrated within a distributed system so that flags can be used. Especially on stateless servers where gating features by user is not easy. Overall though, it is very easy to get started and I like how simple it is to use.
Read full review
Reliability and Availability
Bucket
No answers on this topic
LaunchDarkly
No issue with availability at all
Read full review
Performance
Bucket
No answers on this topic
LaunchDarkly
From what I have seen, LaunchDarkly integrates well with your code and also services you might have in your tech ecosystem. We use Jenkins for automation and we were able to use it to build pipelines to automate the control of LaunchDarkly toggles in our code.
Read full review
Support Rating
Bucket
No answers on this topic
LaunchDarkly
The overall support is very responsive
Read full review
Implementation Rating
Bucket
No answers on this topic
LaunchDarkly
Yes I do.
Read full review
Alternatives Considered
Bucket
No answers on this topic
LaunchDarkly
LaunchDarkly stood out to us because it put control of the application within the hands of our engineers. We didn't want to allow business users to manipulate the production site via a third-party tool. Instead, our focus was on delivering faster as an engineering team.
Read full review
Scalability
Bucket
No answers on this topic
LaunchDarkly
The platform didn't go down since we implemented it
Read full review
Return on Investment
Bucket
No answers on this topic
LaunchDarkly
  • Improved developer experience with some teams moving to Trunk-based Development.
  • Increased deployment frequency due to smaller code releases.
  • Validation of the technical and business value of work is achieved more quickly through smaller pieces of work and through experimenting with a small group of users before a feature gets to 100% of customers.
Read full review
ScreenShots

Bucket Screenshots

Screenshot of Screenshot of Screenshot of Screenshot of Screenshot of

LaunchDarkly Screenshots

Screenshot of regression detection and automated incident response at the feature level. This connects critical metrics to the release process so that every change is monitored - even the smallest releases, where issues would previously have been obscured by noise in the wider system metrics.Screenshot of where track the progression of a feature flag across a series of phases, where each phase consists of one or more environments.Screenshot of how to target groups of contexts individually or by attribute. Contexts are people, services, machines, or other resources that encounter feature flags in a product.Screenshot of where to design experiments that measure business-critical user flows and provide results specific to those product funnels, and measure multi-step user journeys. This is used to determine whether conversions are succeeding, with all metrics visible in one place.