Based on our record, Hasura should be more popular than Hadoop. It has been mentiond 117 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.
> 2. ORMs do not hide SQL nastiness. This is certainly true! I mean: ORMs are now well known to "make the easy queries slightly more easy, while making intermediate queries really hard and complex queries impossible". I think the are of ORMs is over. It simply did not deliver. If a book on SQL is --say-- 100 pages, a book on Hibernate is 400 pages. So much to learn just to make the easy queries slightly easier to... - Source: Hacker News / about 1 month ago
Another strategy is to model access control declaratively and enforce it in the application layer. ZenStack (built above Prisma ORM) and Hasura are good examples of this approach. The following code shows how access policies are defined with ZenStack and how a secured CRUD API can be derived automatically. - Source: dev.to / about 2 months ago
Today, this ecosystem is going strong with new providers like Hasura, AppWrite and Supabase powering millions of projects. There are a few reasons people choose this style of hosting, especially if they are more comfortable with frontend development. BaaS lets them set up a database in a secure way, expose some business logic on top of the data, and connect via a dev-friendly SDK from their app or website code to... - Source: dev.to / 3 months ago
Hi! If you’ve ever thought about something like using GraphQL for something like this.. You might like Hasura. (Obligatory I work for Hasura) We’ve got an OpenAPI import and you can setup cron-jobs or one-off jobs and do things like load in headers from the environment variables to pass through. There isn’t currently an easy journey for chaining multiple calls together without writing any code at all, but you can... - Source: Hacker News / 3 months ago
Hasura.io — Hasura extends your existing databases wherever it is hosted and provides an instant GraphQL API that can be securely accessed for web, mobile, and data integration workloads. Free for 1GB/month of data pass-through. - Source: dev.to / 4 months ago
Did you check out tools like https://hadoop.apache.org/ ? Source: about 1 year ago
There are different ways to implement parallel dataflows, such as using parallel data processing frameworks like Apache Hadoop, Apache Spark, and Apache Flink, or using cloud-based services like Amazon EMR and Google Cloud Dataflow. It is also possible to use parallel dataflow frameworks to handle big data and distributed computing, like Apache Nifi and Apache Kafka. Source: about 1 year ago
There are several frameworks available for batch processing, such as Hadoop, Apache Storm, and DataTorrent RTS. - Source: dev.to / over 1 year ago
A copy of Hadoop installed on each of these machines. You can download Hadoop from the Apache website, or you can use a distribution like Cloudera or Hortonworks. - Source: dev.to / over 1 year ago
The Apache™ Hadoop™ project develops open-source software for reliable, scalable, distributed computing. - Source: dev.to / over 1 year ago
Supabase - An open source Firebase alternative
Apache Spark - Apache Spark is an engine for big data processing, with built-in modules for streaming, SQL, machine learning and graph processing.
GraphQL Playground - GraphQL IDE for better development workflows
PostgreSQL - PostgreSQL is a powerful, open source object-relational database system.
GraphQl Editor - Editor for GraphQL that lets you draw GraphQL schemas using visual nodes
Apache Flink - Flink is a streaming dataflow engine that provides data distribution, communication, and fault tolerance for distributed computations.