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Databricks VS graphql.js

Compare Databricks VS graphql.js and see what are their differences

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Databricks logo Databricks

Databricks provides a Unified Analytics Platform that accelerates innovation by unifying data science, engineering and business.‎What is Apache Spark?

graphql.js logo graphql.js

A reference implementation of GraphQL for JavaScript - graphql/graphql-js
  • Databricks Landing page
    Landing page //
    2023-09-14
  • graphql.js Landing page
    Landing page //
    2023-08-27

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.

graphql.js features and specs

  • Strongly Typed
    GraphQL.js allows for strongly typed schemas, making it easier to perform validation and introspection on your data, ensuring that queries conform to a specific structure before execution.
  • Efficient Data Fetching
    GraphQL.js enables clients to request exactly the data they need which can reduce over-fetching and under-fetching compared to REST APIs.
  • Rich Developer Tooling
    The introspection capabilities in GraphQL.js allow for rich tooling, enabling better development workflows including robust IDE support and tools like GraphiQL.
  • Evolving APIs
    GraphQL.js facilitates evolving APIs without the need for versioning, providing backward compatibility by introducing non-breaking changes.
  • Community Support
    GraphQL.js has a large and active community, providing numerous resources, plugins, and tools that support smooth development processes.

Possible disadvantages of graphql.js

  • Complexity
    Implementing GraphQL.js can add complexity to projects as developers may need to learn new concepts such as schemas, resolvers, and query languages.
  • Overhead
    The flexibility of GraphQL.js can introduce performance overhead, as the server may need to parse and execute more complex and dynamic queries.
  • Cache Invalidation
    Caching strategies for GraphQL.js can be more complex compared to REST, as caching needs to account for the structure and specifics of the queries requested.
  • Over-fetching Risks
    While GraphQL.js mitigates data over-fetching, it can also expose sensitive data if developers are not meticulous in specifying and controlling the schema and access permissions.
  • Debugging Complexity
    Debugging runtime errors in GraphQL.js can sometimes be more difficult, especially with deeply nested queries and complex resolvers.

Databricks videos

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Introduction to Databricks

More videos:

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

graphql.js videos

No graphql.js videos yet. You could help us improve this page by suggesting one.

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Category Popularity

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Data Dashboard
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Project Management
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Big Data Analytics
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User comments

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Reviews

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

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

graphql.js Reviews

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Social recommendations and mentions

Based on our record, Databricks should be more popular than graphql.js. It has been mentiond 18 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.

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 / 9 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 / almost 3 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 / about 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

graphql.js mentions (8)

  • Diving into Open-Source Development
    To begin, I'm going to start with GraphQL. This repo is a JS-specific implementation for GraphQL, for which projects written in JS/TS can utilize to build an API for their web app. The reason why I chose this project is because I've always been intrigued by how GraphQl challenges the standard way of building an API, a.k.a REST APIs. I have very little knowledge about this project since I've never used it before at... - Source: dev.to / almost 2 years ago
  • How to define schema once and have server code and client code typed? [Typescript]
    When I asked this in StackOverflow over a year ago I reached the solution of using graphql + graphql-zeus. Source: almost 2 years ago
  • Apollo federated graph is not presenting its schema to graphiql with fields sorted lexicographically
    GraphiQL (and many other tools) relies on introspection query which AFAIK is not guaranteed to have any specific order (and many libs don't support it). Apollo Server is built on top of graphql-js and it relies on it for this functionality. Source: over 2 years ago
  • How (Not) To Build Your Own GraphQL Server
    Defining your schema and the resolvers simultaneously led to some issues for developers, as it was hard to decouple the schema from the (business) logic in your resolvers. The SDL-first approach introduced this separation of concerns by defining the complete schema before connecting them to the resolvers and making this schema executable. A version of the SDL-first approach was introduced together with GraphQL... - Source: dev.to / over 3 years ago
  • three ways to deploy a serverless graphQL API
    Graphql-yoga is built on other packages that provide functionality required for building a GraphQL server such as web server frameworks like express and apollo-server, GraphQL subscriptions with graphql-subscriptions and subscriptions-transport-ws, GraphQL engine & schema helpers including graphql.js and graphql-tools, and an interactive GraphQL IDE with graphql-playground. - Source: dev.to / over 3 years ago
View more

What are some alternatives?

When comparing Databricks and graphql.js, you can also consider the following products

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

JsonAPI - Application and Data, Languages & Frameworks, and Query Languages

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.

Apollo - Apollo is a full project management and contact tracking application.

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.

Graphene - Query Languages

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