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LaunchDarkly VS Databricks

Compare LaunchDarkly VS Databricks and see what are their differences

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LaunchDarkly logo LaunchDarkly

LaunchDarkly is a powerful development tool which allows software developers to roll out updates and new features.

Databricks logo Databricks

Databricks provides a Unified Analytics Platform that accelerates innovation by unifying data science, engineering and business.‎What is Apache Spark?
  • LaunchDarkly Landing page
    Landing page //
    2023-09-12
  • Databricks Landing page
    Landing page //
    2023-09-14

LaunchDarkly features and specs

  • Comprehensive Feature Flag Management
    LaunchDarkly offers a robust platform for feature flag management, allowing for granular control over which features are enabled for different user segments.
  • Real-time Feature Control
    Changes to feature flags can be made in real-time, reducing the need for redeploys and allowing for instant rollouts and rollbacks.
  • Scalability
    LaunchDarkly is built to handle large-scale deployments and can manage tens of millions of feature flags efficiently.
  • Team Collaboration
    The platform includes features that facilitate team collaboration, such as role-based access control and detailed audit logs.
  • Integration Capabilities
    LaunchDarkly supports integrations with a wide range of DevOps and CI/CD tools, making it easier to incorporate into existing workflows.
  • Advanced Targeting
    The platform allows for sophisticated targeting rules and user segmentation, enabling highly personalized feature rollouts.

Possible disadvantages of LaunchDarkly

  • Cost
    LaunchDarkly can be expensive, especially for smaller organizations or startups with limited budgets.
  • Learning Curve
    The platform can be complex to set up and use effectively, requiring a learning curve for new users.
  • Dependency on Internet Connectivity
    Real-time updates and functionality depend on an internet connection, which may be a limitation for some use cases.
  • Vendor Lock-in
    Once integrated, switching to another feature flag service can be time-consuming and difficult due to the level of integration and customization.
  • Limited Offline Support
    Offline support is not as robust as some other solutions, potentially affecting scenarios where intermittent connectivity is expected.
  • Enterprise Focus
    While powerful, some features and pricing models are more geared towards enterprise users, potentially alienating smaller or non-enterprise customers.

Databricks features and specs

  • Unified Data Analytics Platform
    Databricks integrates various data processing and analytics tools, offering a unified environment for data engineering, machine learning, and business analytics. This integration can streamline workflows and reduce the complexity of data management.
  • Scalability
    Databricks leverages Apache Spark and other scalable technologies to handle large datasets and high computational workloads efficiently. This makes it suitable for enterprises with significant data processing needs.
  • Collaborative Environment
    The platform offers collaborative notebooks that allow data scientists, engineers, and analysts to work together in real-time. This enhances productivity and fosters better communication within teams.
  • Performance Optimization
    Databricks includes various performance optimization features such as caching, indexing, and query optimization, which can significantly speed up data processing tasks.
  • Support for Various Data Formats
    The platform supports a wide range of data formats and sources, including structured, semi-structured, and unstructured data, making it versatile and adaptable to different use cases.
  • Integration with Cloud Providers
    Databricks is designed to work seamlessly with major cloud providers like AWS, Azure, and Google Cloud, allowing users to easily integrate it into their existing cloud infrastructure.

Possible disadvantages of Databricks

  • Cost
    Databricks can be expensive, especially for large-scale deployments or high-frequency usage. It may not be the most cost-effective solution for smaller organizations or projects with limited budgets.
  • Complexity
    While powerful, Databricks can be complex to set up and manage, requiring specialized knowledge in Apache Spark and cloud infrastructure. This might lead to a steeper learning curve for new users.
  • Dependency on Cloud Providers
    Being heavily integrated with cloud providers, Databricks might face issues like vendor lock-in, where switching providers becomes difficult or costly.
  • Limited Offline Capabilities
    Databricks is primarily designed for cloud environments, which means offline or on-premise capabilities are limited, posing challenges for organizations with strict data governance policies.
  • Resource Management
    Efficiently managing and allocating resources can be challenging in Databricks, especially in large multi-user environments. Mismanagement of resources could lead to increased costs and reduced performance.

LaunchDarkly videos

+ Add

How LaunchDarkly Enables Product Managers to Test in Production

More videos:

  • Review - Getting Started with Feature Flags - #1 LaunchDarkly Feature Flags
  • Review - Show & Tell with LaunchDarkly's Edith Harbaugh: Mobile Feature Flags

Databricks videos

+ Add

Introduction to Databricks

More videos:

  • Tutorial - Azure Databricks Tutorial | Data transformations at scale
  • Review - Databricks - Data Movement and Query

Category Popularity

0-100% (relative to LaunchDarkly and Databricks)

LaunchDarkly

Databricks

Developer Tools
100 100%
Developer Tools
0% 0
Data Dashboard
0 0%
Data Dashboard
100% 100
Feature Flags
100 100%
Feature Flags
0% 0
Big Data Analytics
0 0%
Big Data Analytics
100% 100

User comments

Share your experience with using LaunchDarkly and Databricks. For example, how are they different and which one is better?
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Reviews

These are some of the external sources and on-site user reviews we've used to compare LaunchDarkly and Databricks

LaunchDarkly Reviews

Top Mobile Feature Flag Tools
LaunchDarkly is another dedicated feature flag management tool that offers extensive features. They support a variety of platforms and languages and boast clients like Microsoft, Atlassian, and Invision. Like Rollout, LaunchDarkly offers all the features of an enterprise-grade tool but, unlike Rollout, reserves the security features for the “Enterprise” plan. Out of the box,...
Source: instabug.com
Feature Toggling Tools for $100 or less
A differentiating factor is the functionality to schedule releases through the console, LaunchDarkly and FeatureFlow have incorporated this into their front end. Another front-end feature of interest is user segmentation management, which is available with LaunchDarkly, Rollout, and Bullet train subscriptions.
Source: medium.com

Databricks Reviews

Jupyter Notebook & 10 Alternatives: Data Notebook Review [2023]
Databricks notebooks are a popular tool for developing code and presenting findings in data science and machine learning. Databricks Notebooks support real-time multilingual coauthoring, automatic versioning, and built-in data visualizations.
Source: lakefs.io
7 best Colab alternatives in 2023
Databricks is a platform built around Apache Spark, an open-source, distributed computing system. The Databricks Community Edition offers a collaborative workspace where users can create Jupyter notebooks. Although it doesn't offer free GPU resources, it's an excellent tool for distributed data processing and big data analytics.
Source: deepnote.com
Top 5 Cloud Data Warehouses in 2023
Jan 11, 2023 The 5 best cloud data warehouse solutions in 2023Google BigQuerySource: https://cloud.google.com/bigqueryBest for:Top features:Pros:Cons:Pricing:SnowflakeBest for:Top features:Pros:Cons:Pricing:Amazon RedshiftSource: https://aws.amazon.com/redshift/Best for:Top features:Pros:Cons:Pricing:FireboltSource: https://www.firebolt.io/Best for:Top...
Source: www.shipyardapp.com
Top 10 AWS ETL Tools and How to Choose the Best One | Visual Flow
Databricks is a simple, fast, and collaborative analytics platform based on Apache Spark with ETL capabilities. It accelerates innovation by bringing together data science and data science businesses. It is a fully managed open-source version of Apache Spark analytics with optimized connectors to storage platforms for the fastest data access.
Source: visual-flow.com
Top Big Data Tools For 2021
Now Azure Databricks achieves 50 times better performance thanks to a highly optimized version of Spark. Databricks also enables real-time co-authoring and automates versioning. Besides, it features runtimes optimized for machine learning that include many popular libraries, such as PyTorch, TensorFlow, Keras, etc.
Source: blog.bismart.com

Social recommendations and mentions

Based on our record, LaunchDarkly should be more popular than Databricks. It has been mentiond 37 times since March 2021. We are tracking product recommendations and mentions on various public social media platforms and blogs. They can help you identify which product is more popular and what people think of it.

LaunchDarkly mentions (37)

  • How to Add Paid Features to Your SaaS Apps
    This kind of goes without saying since it's the opposite of the first don't I listed, but it's worth restating and giving some examples. Using tools from third parties means taking advantage of what they have done so you don't have to do that work. This means you are free to build things that make your app special. I like to use feature flag tools for this. Some examples are LaunchDarkly, Split, and AWS App... - Source: dev.to / about 1 year ago
  • Pivoting a million dollar DevTool startup
    Taplytics is a broad A/B testing platform for marketing teams. While DevCycle is a feature flagging tool built for developers. Taplytics actually has feature flagging, but DevCycle is much more focused and plans to compete directly with incumbents like LaunchDarkly by building a better developer experience (more on how later). But with Taplytics they built so many features and every customer was using them in a... - Source: dev.to / over 1 year ago
  • Arc Update - 1.20.1 (43987)
    I had a custom rule added to Little Snitch that blocked the following domains: launchdarkly.com, clientstream.launchdarkly.com, mobile.launchdarkly.com. Source: over 1 year ago
  • Feature flags implementation in Nest.js 😻
    There are however Saas to implement directly a feature management system. Several solutions exist like LaunchDarkly, Flagsmith or Unleash.io. Using a SaaS (Software as a Service) feature flagging solution offers the advantage of a faster and more straightforward implementation process. These services are readily available and can be quickly integrated into your project. - Source: dev.to / over 1 year ago
  • Boost DX, Enhance UX, and Skyrocket Profits! Dive into a sub-50ms world with Edge Feature Flags 🚀
    Currently, there are numerous feature flag systems available. Options include our own company's open-source system, "Bucketeer", and the renowned SaaS "LaunchDarkly" among others. When comparing these, the following considerations might come into play:. - Source: dev.to / over 1 year ago
View more

Databricks mentions (18)

  • Platform Engineering Abstraction: How to Scale IaC for Enterprise
    Vendors like Confluent, Snowflake, Databricks, and dbt are improving the developer experience with more automation and integrations, but they often operate independently. This fragmentation makes standardizing multi-directional integrations across identity and access management, data governance, security, and cost control even more challenging. Developing a standardized, secure, and scalable solution for... - Source: dev.to / 8 months ago
  • dolly-v2-12b
    Dolly-v2-12bis a 12 billion parameter causal language model created by Databricks that is derived from EleutherAI’s Pythia-12b and fine-tuned on a ~15K record instruction corpus generated by Databricks employees and released under a permissive license (CC-BY-SA). Source: about 2 years ago
  • Clickstream data analysis with Databricks and Redpanda
    Global organizations need a way to process the massive amounts of data they produce for real-time decision making. They often utilize event-streaming tools like Redpanda with stream-processing tools like Databricks for this purpose. - Source: dev.to / over 2 years ago
  • DeWitt Clause, or Can You Benchmark %DATABASE% and Get Away With It
    Databricks, a data lakehouse company founded by the creators of Apache Spark, published a blog post claiming that it set a new data warehousing performance record in 100 TB TPC-DS benchmark. It was also mentioned that Databricks was 2.7x faster and 12x better in terms of price performance compared to Snowflake. - Source: dev.to / almost 3 years ago
  • A Quick Start to Databricks on AWS
    Go to Databricks and click the Try Databricks button. Fill in the form and Select AWS as your desired platform afterward. - Source: dev.to / about 3 years ago
View more

What are some alternatives?

When comparing LaunchDarkly and Databricks, you can also consider the following products

Flagsmith - Flagsmith lets you manage feature flags and remote config across web, mobile and server side applications. Deliver true Continuous Integration. Get builds out faster. Control who has access to new features. We're Open Source.

Google BigQuery - A fully managed data warehouse for large-scale data analytics.

ConfigCat - ConfigCat is a developer-centric feature flag service with unlimited team size, awesome support, and a reasonable price tag.

Looker - Looker makes it easy for analysts to create and curate custom data experiences—so everyone in the business can explore the data that matters to them, in the context that makes it truly meaningful.

Unleash - Unleash is an open-source feature management platform. We are private, secure, and ready for the most complex setups out of the box.

Jupyter - Project Jupyter exists to develop open-source software, open-standards, and services for interactive computing across dozens of programming languages. Ready to get started? Try it in your browser Install the Notebook.

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