TigerGraph Reviews

After conducting extensive evaluations of numerous graph databases available on the market, TigerGraph has emerged as the only solution that truly scales to meet our ever-growing needs. Its exceptional performance and scalability have solidified its position as our top choice for a graph database.

A key factor that influenced our decision to choose TigerGraph is its SQL-like, feature-rich language. This intuitive language not only supports our production graph use cases but also enables our data scientists and analysts to perform in-depth graph analytics and uncover valuable insights. With its powerful Accumulator functions, TigerGraph has allowed us to harness the true potential of graph analytics like never before, enabling us to tackle complex data challenges that would have been impossible with other technologies.

TigerGraph's unparalleled scalability and comprehensive language capabilities have opened up new possibilities for our team, revolutionizing the way we approach data analysis and decision-making. By leveraging the power of graph analytics with TigerGraph, we are now able to uncover insights and drive data-driven decisions more effectively than ever before.

One aspect that could be considered a minor drawback in TigerGraph is the initial learning curve associated with its unique query language, GSQL. However, this concern is effectively mitigated by the fact that GSQL is designed to be similar to SQL, making it easier for users with SQL experience to quickly adapt and become proficient in using it. Furthermore, TigerGraph offers extensive documentation and support resources, which greatly facilitate the learning process and help users overcome this initial challenge. With the advent of GPT-4, most queries can now be AI-generated, effectively resolving this barrier.

In the grand scheme of things, the benefits of TigerGraph's powerful features, scalability, and performance far outweigh this minor inconvenience, making it an excellent choice for organizations seeking a robust graph database solution.

Graph Analytics, Friend recommendations, Item recommendations, Community/Influencer detection and Fraud detection.

TigerGraph Cloud is a very powerful platform that gives newcomers into the graph world a lot of ability to deliver right off the bat with its GraphStudio UI.

No downside. Just a bit of learning curve in general to adopted to the graph database world.

Complex manufacturing analytics and internal process improvement efforts.

Completely new platform and new language GSQL is growing very fast and most important, It's a future.

With Azure the trial version is not free.

I am learning to solve the Covid problem on the platform and the GUI makes it easy to learn the platform

One of the most beneficial aspects of TigerGraph is its powerful graph database technology. We like its Fast query performance, Flexibility and Advanced analytics.

Cost: It is costly, and not all companies can afford it. Additionally, it can be quite complex for beginners. Documentation and community support are not good.

We use it for Real-time insights, enabling data connectivity, Developer productivity using GSQL query language, and API data over APIs. Overall business performance has increased

Tigergraph was extremely useful for connecting data through machine learning. It help drive our data points to make better business decisions.

At times it does freeze while using bur very rarely and it could quite possibly be our servers.

Trying to integrate the use of data sets through financial services go further make business and trading decisions

We use Tigergraph to trace customer footprint in our website. Like how customers relate with our products, their purchases etc. And with Tigergraph it's really easy to understand user behaviour analysis data and take action accordingly.

Nothing as of now and with Graph 3.0 it's really cool.

We have find out the reason of decrease of customers in our website and with Tigergraph it's more easy to understand customer behaviour and using the data we are working on coustomer retention rate and it's growing rapidly. Thanks to Tigergraph Analytics.

Being able to expand nodes and edges, perform traversals, and the range of built-in functions/accumulators.

The limited UI search features. It's unbelievable that a querying tool this powerful, with its own unique GSQL language, doesn't have partial search options. Even part of a vertex's id is NOT searchable from the UI, exact matches only.

Highly scalable, the framework of TG is made for handling very large datasets. We load tens of thousands of vertices at a time & it is still comparably small to the telecom datasets that this tool is most used for.

Robust optimizations are possible with Tigergraph, no matter how complex the network. Secondly, the latest update allows for longer traversals which leads to better queries. Tigergraph's built-in REST API integrates everything easily with Frontend and Middleware code parts.

Connecting data through Artificial Intelligence for analytics purpose

Some times it becomes bit slow at times.

Must have software

analytics solution for a finance survey

GSQL is designed to resemble SQL. It makes it difficult for SQL users to adapt quickly. The extensive documentation and support provided by TigerGraph also make the learning process arduous.

TigerGraph provides features for data analysis Im not a fan of the user interface and documentation. It is difficult for technical users to navigate and learn the platform.

TigerGraph solves the problems of data analytics through its graph database and analytics platform. We encounter glitches at a time. Improvements are needed in management.

There is a learning curve at the beginning for those who are new to graph databases GSQL has been designed to resemble SQL making it difficult for individuals with SQL experience.

The platform lacks a user experience, which makes navigation and learning difficult. The limited functionality of the graphical user interface (GUI) hampers problem-solving.

TigerGraph does not solve data analysis and management problems. The documentation and support resources provided by TigerGraph do not overcome the initial problems. It also slowed down the learning process.