Tuesday, January 12, 2021

Is GraphQL Worth It?

In the development world, GraphQL is becoming an increasingly common topic of conversation. But what is GraphQL and should you be using it? In this blog, we’ll talk about what hosted GraphQL is and why you might choose to use it in your business.

What is GraphQL?

GraphQL is a query language. It’s used for APIs and defines the data that you get when you make a query. This makes defining and returning data much easier for frontend developers and it makes less work for backend developers, So, why might you use a hosted GraphQL server?

Why Might You Choose Hosted GraphQL?

Here are some of the biggest benefits of hosted GraphQL and why someone might choose it for their business.

Connect Your Applications to an API

If you have applications or websites that you need to connect to a database, it’s hard to beat GraphQL as a solution. You can easily define the data you want to return to the client app and only utilize the data you’re needing.

You Need an Alternative or Replacement for a REST API

REST APIs can be useful in several scenarios, but GraphQL is superior in a lot of ways. For instance, with GraphQL, you won’t have to worry about over and under fetching, dependent requests, and multiple requests. With GraphQL, you can make a complex query and expect it to return the exact data you need, without having to take multiple round trips and bring you data you’re not looking for.

If you’re looking to replace a REST API because you’re needing something a little more complex, then GraphQL will be a great choice.

Data Normalization

If you’re needing to structure your data and get rid of any superfluous redundancies, then GraphQL can help. GraphQL creates relationships between your data points and ensures your data is normalized, making it easy to get your data organized and return exact data without multiple queries.

In short, GraphQL, like most query languages, isn’t perfect, but it can be a great solution for many situations. In the end, whether or not you use GraphQL is up to you, but the above scenarios are good situations where GraphQL might be best for your needs.

Read a similar article about graph database here at this page.

Servo browser engine adopted by Linux Foundation

Servo, an open source browser engine originally developed at Mozilla, has moved over to the Linux Foundation. A modular, embeddable web engine written in Mozilla’s Rust language, Servo shares code with the Firefox browser and is intended to enable delivery of content and applications via web standards. Created in 2012, Servo incubated technologies later incorporated into Firefox such as the WebRender GPU-based rendering system read more

Saturday, October 10, 2020

What is Ristretto Golang cache?

An efficient cache library is an important aspect of any implementation. If your cache library isn’t great, it can slow an application down dramatically. The Ristretto Golang cache is a memory-bound, concurrent Go cache that is contention resistant. Learn more about it in this blog.

What Ristretto Golang Cache is Meant to Do?

The three primary functions of the Ristretto Golang Cache are as follows:

  • Fast Accesses
  • High Concurrency and Contention Resistance
  • Memory Bounding

But what does that mean and how does it help the Go cache library to function better. Let’s talk about what each of these mean in a little more detail.

Fast Access

Ristretto Golang cache takes a shard-based approach to optimize performance. This is achieved using sharded mutex-wrapped GO maps.

High Concurrency Contention Resistance

Ristretto Golang cache is made to have high levels of contention resistance. This is achieved through batching. Batching is when instead of acquiring a mutex lock for every metadata mutation, a ring buffer fills up before acquiring a mutex and processing the mutations. This can dramatically lower contention.

Memory Bounding

Since a cache must be bounded in size, Ristretto Golang cache taking memory cost into consideration when bounding. A cost is attached to every key-value. This lets the cache adjust for different workloads and continue operating efficiently, even when at capacity. For instance, less valuable items might be replaced by more valuable items when operating at capacity. This makes the cache library highly efficient at all times.

Is Ristretto Golang Cache Right for My Application and Should I Implement It?

If you’re wondering if you should implement the Ristretto Golang cache library into your GO application, just consider the benefits we’ve outlined in this blog. Ristretto has the ability to make your cache library much more reliable and efficient. Through fast access, contention resistance, and memory bounding, your cache library in Go will operate exactly how you need it to. Since Ristretto is new, it’s still evolving and will only get better over time. It’s adaptive and scalable, so it can really make a difference in the way you run GO.

Read a similar article about cloud-based graph database here at this page.

Pubmatic Has Announced Openwrap OTT

Digital technology company PubMatic announced the launch of OpenWrap OTT, a header bidding solution that centralizes 100% of direct and programmatic demand while preserving a seamless TV-like viewer experience. PubMatic has delivered more than 8 years of header bidding technology, and Prebid Server-based OpenWrap OTT helps both publishers and advertisers realize the full economic potential of programmatic by optimizing monetization and viewer experience across the entire ad pod read more

Tuesday, September 8, 2020

What is a Graph Database?

Graphs and data modeling have become essential components of data analytics. One common way to model data is through a graph database. In this blog, we’ll explain in basic terms what a graph database is and how you can use them to get insightful analytics.

What is a Graph Database?

A graph database is commonly depicted as a network of nodes. Each node is meant to represent an entity, like a person or a place. These nodes are connected and each connection represents a relationship between nodes. Each relationship contains a quantitative piece of data that shows how or why the nodes are connected. For instance, a very simple example of this would be the two nodes, Paul and Dan. The relationship “is the son of” might connect the two. So in the graph you would see these two separate nodes, Paul and Dan, and through the connection you could see that Dan is the son of Paul.

Once a database is created, it’s simple for a user to enter a query and find the relationship between nodes.

These network of nodes are unique in the fact that they’re specifically centered around relationships and connections, rather than data about specific individuals.

What Can Graph Databases Do?

So we have a little bit better of an understanding of what a graph database is and what kind of data it has, but how do we use this data? There are plenty of use cases.

It turns out that they're used in more places than you might think. They’re commonly utilized by major companies for their recommendation engines, to improve their artificial intelligence, to detect fraud, and much more.

For instance, you can utilize graph databases to improve your AI chat messenger. They will help the AI learn what common queries are and make those connections to help your customers get the right answer. That’s just the beginning of what these databases can offer. As the technology improves and they become more widely utilized, they will continue to change and shape the way business is done and how we collect data. 

For more information about hosted graphQL backend, check out this site.

Is GraphQL Worth It?

In the development world, GraphQL is becoming an increasingly common topic of conversation. But what is GraphQL and should you be using it...