The GridGain Systems In-Memory Computing Blog
Focusing on how Apache Ignite handles transactions with third-party persistence, this article is the last part of the Apache Ignite Transactions Architecture series.
In the previous articles in this series, we discussed a range of topics associated with Apache Ignite's transactions handling in its Key-Value API.
In the first article, we briefly reviewed the two-phase commit protocol and…
In this article, we will be discussing transaction handling at the level of Ignite persistence.
In the previous article in this series, we looked at failover and recovery. Here are topics we will cover in the rest of this series:
Transaction handling at the level of Ignite persistence (WAL, checkpointing, and more)
Transaction handling at the level of 3rd party persistence.
Those…
In this article, we will focus on how Apache Ignite handles failover and recovery during transaction execution.
In the previous article in this series, we looked at concurrency modes and isolation levels. Here are topics we will cover in
the rest of this series:
Failover and recovery [this article]
Transaction handling at the level of Ignite persistence (WAL, checkpointing, and more)…
Today, 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. These enhancements make large volumes of enterprise data in data lakes and semi-structured document…
This article on pessimistic and optimistic concurrency is the second in the Apache Ignite Transactions Architecture series.
In the previous article, we looked at the two-phase commit protocol and how it worked with various types of cluster nodes in Apache Ignite. Here are topics we will cover in the rest of this series:
Pessimistic and optimistic concurrency [this article]…
This article on Apache Ignite and the two-phase commit protocol is the first in a series of five posts regarding the Apache Ignite transactions architecture.
Apache Ignite supports a range of different Application Programming Interfaces (APIs). In this multi-part article series, we will take a more detailed look at how Apache Ignite manages transactions in its key-value API and some of the…
Telecommunication companies can transform their operations into data-driven enterprises by utilizing the Digital Integration Hub Architecture, which is built on GridGain's in-memory computing platform. 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…
First, there were DBMSs and data warehouses. Then came data lakes and event stream processing
platforms. Now, the most advanced data solutions are Unified Real-Time Data Platforms. But what are
they?
Unified Real-Time Data Platforms simplify and optimize data architectures by combining
transactional, stream, and analytical processing across data silos into a single “unified” platform. These…
Every industry is experiencing massive increases in the volume of data, the number of queries, and the complexity of requests. At the same time, requirements for low latency are also increasing to keep up with the speed of business. This trend has been apparent in capital markets perhaps longer than in other industries due to intense competition and a willingness to be early adopters of…
GridGain recently published a micro-learning unit on GridGain University that delves into the different data loading strategies for Apache Ignite. These strategies include initial/regular batch load from files, database loading, real-time streaming, and ETL (Extract Transform & Load).
Here is an overview of some of the key strategies. Watch the full 9-minute video here.
Initial /…