GridGain Blog
The scope of relevant information for today’s data-driven enterprises extends beyond the boundaries of their firewalls. This has created complex problems, including the multidimensional nature of the data to be processed, the enormous scale of data and the tremendous speed at which the data must be processed.
The two largest sources of latency in any distributed system are network latency and disk access. In traditional client server applications, data is constantly moved over the network, and it's usually accessed from disk. To reduce latency, Apache Ignite allows distributed in-memory data and computation as well as a transactional SQL environment – including the ability to control the location of…
GridGain now offers advanced JSON query capabilities that not only empower technical teams but also provide tangible business benefits. By seamlessly integrating technical features with compelling business advantages, GridGain helps enterprises derive valuable insights from their data as soon as it’s generated.
In the second part of this blog series, we'll explore how to overcome the limitations of standard query processing by writing some code. As a result, you will likely only use this technique in those instances where you know you are experiencing the set of limitations and need to get the most optimal result times.
In this two-part blog post, we will first explore and understand the major steps that are executed by GridGain’s SQL query processing engine. More importantly, we will share how data is exchanged in the above process and learn about certain limitations that exist within this process.
After learning the basics in part one, we will then explore how to overcome those limitations in part two by…
In this 10-minute training course, we take you through writing your first queries using the three techniques of standard SQL, SQL via Java APIs, and Ignite’s KeyValue pair API.
This six-minute Micro Learning Unit explores how distributed data is implemented in Apache Ignite and identifies solutions to three key data challenges: hardware capacity, hardware reliability, and performance issues.
We are thrilled to announce the release of GridGain Platform v8.9, adding new and enhanced integrations with popular data formats – including Apache Parquet, Apache Iceberg, CSV, and JSON – in order to enable more complete real-time analysis of your increasingly complex enterprise data.
In this blog post, we will explore how the Digital Integration Hub architecture can assist telecommunication companies in enhancing customer insights, creating additional revenue streams, and preparing for the 5G revolution.
Explore how Unified Real-Time Data Platforms power real-time analytics, fraud detection, and AI by unifying streaming and stored data at scale.