MigratoryData just released the integration of MigratoryData with Apache Kafka. This is a significant step forward both for Kafka users and MigratoryData users. On one hand, MigratoryData is going to provide to Kafka a scalable extension for Kafka data pipelines across the Web while preserving its key feature like real-time messaging, high availability, guaranteed delivery, message ordering. On the other hand, Kafka is going to provide to MigratoryData a reliable layer for message storage and integration with Kafka data pipelines like stream processing, databases, microservices. In this blog post, we outline the compatibility and complementarity of MigratoryData and Apache Kafka.
Read more
In this paper we present a fault-tolerant mechanism for sending notifications to offline users, to complement MigratoryData’s realtime messaging to online users. Hence, MigratoryData’s unified client API can be used to achieve both realtime messaging to online users and notifications – such as Push Notifications, Email, SMS, and more – to offline users. We exemplify the new mechanism with a chat mobile app for Android and iOS.
Read more
MigratoryData 6 adds support for the MQTT protocol - the de facto messaging standard for the Internet of Things.
Read more
In this blog post, we show how to use popular open-source big data platform Elastic Stack for searching, analyzing, and visualizing data produced by MigratoryData.
Read more
Using the RESTful HTTP request-response approach can become very inefficient for websites requiring real-time communication. We propose a new approach and exemplify it with a well-known feature that requires real-time communication, and which is included by most websites: search box autocomplete.
Read more
In our previous world-record-setting C10M benchmark, we showed that MigratoryData Server can achieve extreme high-scalability by delivering real-time messaging to 10 million concurrent users on a single 1U machine. Here, we show that MigratoryData Server can achieve simultaneously both extreme high-scalability and consistent low latency.
Read more
The C10M problem relates to the classic C10K Internet scalability problem, which originally occurred in the context of Web servers. The C10K problem consists of successfully supporting 10,000 concurrent connections on a single machine. While the C10K problem is currently solved by certain Web servers, the C10M problem, which consists in supporting 10 million concurrent connections on a single machine, remains a challenging problem not only for Web servers, but for any Internet server in general. In this article, we demonstrate that MigratoryData Server is able to handle 10 million concurrent connections on a single commodity machine. Moreover, it is able to push almost 1 Gbps live data to these 10 million users (each user receiving a 512-byte message per minute) with an average latency of under 100 milliseconds.
Read more
Massive scalability is the biggest challenge we undertake at MigratoryData, a provider of an enterprise publish-subscribe messaging system for building very scalable real-time web and mobile applications. We recently published a blog post demonstrating 12 million concurrent connections with MigratoryData WebSocket Server running on a single 1U server. We are going to share some lessons learned while pushing the boundaries of scalability with MigratoryData WebSocket Server.
Read more
We have recently completed a new performance benchmark which demonstrates that MigratoryData is able to handle 12 million concurrent users from a single server Dell PowerEdge R610 while pushing a substantial amount of live data (1.015 gigabit per second).
Read more
This benchmark shows that MigratoryData achieves 8X higher scalability than the record obtained by the competition in the same benchmark category; reaffirming it is the most scalable WebSocket server. This benchmark result also demonstrates that, using MigratoryData WebSocket Server, it is feasible and affordable to build real-time web applications delivering high volumes of real-time information to a high number of concurrent users.
Read more
