With MongoDB as one of the most popular NoSQL databases, we are excited to announce the release of our MongoDB Connector v4.2.0. This version includes improvements in connector configuration and support for batch/bulk operations. Let’s walk through an example of using the bulk operation (Bulk.insert()) using the MongoDB Connector v4.2.0.
Since v2.6, MongoDB has supported bulk operations.
REmote DIctionary Server (REDIS) is an open source, in-memory data structure store which was created by Salvatore Sanfilippo in 2009 for real-time web analytics. This open source project had been sponsored by VMware and Pivotal Software, and since June 2015, has been sponsored by Redis Labs. According to Redis Day TLV 2016, Redis has gained lots of adoption in thousands of companies including American Express, Atlassian, Ariba,
Let’s imagine you’ve been working as an architect in a large company for several years and are very proud of the now mature Supplier Relationship Management (SRM) application you specified, formed, and delivered to the business, as it continues to provide value.
Functionally, the SRM is a web application that allows for managing relationships of suppliers and materials, maintaining hierarchical structures, uncovering unwanted dependencies and helping your clients significantly reduce supplier costs.
In the past few months, you may have noticed that we have regularly announced the release of new Mule connectors for NoSQL data-stores. Two main forces are at play behind the need for these types of data-stores:
Big Data – The need to deal in realtime or near-realtime with the vast amounts of data “web-scale” applications can generate,
BASE vs ACID – The need to scale reliably in the unreliable environment that is the cloud leading to the relaxation of RDBM’s ACID properties (Atomicity,
The recently upgraded Redis connector for Mule allows you to interact with this NoSQL data-store in a convenient manner. This blog is a tutorial that you can follow in order to get your feet wet with Redis, if you don’t know it already, or Mule, if you have Redis experience and want to see how they both can work together.
In this tutorial, we will build a very simple back-end that captures page visit count for identified users via a web bug.
In the new enterprise, the “one big database” paradigm is being progressively eroded as it becomes more apparent that the ACID qualities of traditional SQL databases are not always needed, and can actually get in the way of massive scalability. In order to respond to the imperative of cloud deployments, new data stores have emerged.
One of them is Riak, a highly-available, fault-tolerant and scalable distributed key-value store built by Basho Technologies,
Mule has a very extensive support for NoSQL data stores, which covers pretty much the whole spectrum of what’s available out there, from key/value stores to document-oriented databases. The only piece that was missing in the puzzle was connectivity to a graph database: with the introduction of the Neo4j connector, the gap is now closed.
Popularized by the advent of social media, the need for efficiently storing,
Apache Cassandra is a column-based, distributed NoSQL database. Until recently the only way to interact with Cassandra databases from Mule was to reuse one of the existing Java clients, like Hector or Astyanax, in a component. Mule’s Cassandra DB Module now provides message processors to insert, update, query and delete data in Cassandra.
To show off some of the features of the Cassandra module I’ll show how to implement a simple account management API.
Picture an architecture where production data gets painstakingly replicated to a very expensive secondary database, where, eventually, yesterday’s information gets analyzed. What’s the name for this “pattern”? If you answered “Traditional Business Intelligence (BI)”, you’ve won a rubber Mule and a warm handshake at the next Mule Summit!
As the volume of data to analyze kept increasing and the need to react in real-time became more pressing, new approaches to BI came to life: the so-called Big Data problem was recognized and a range of tools to deal with it started to emerge.
MuleSoft provides the most widely used integration platform for connecting any application, data source or API, whether in the cloud or on-premises. With Anypoint Platform®, MuleSoft delivers a complete integration experience built on proven open source technology, eliminating the pain and cost of point-to-point integration. Anypoint Platform includes CloudHub™ iPaaS, Mule ESB™, and a unified solution for API management™, design and publishing.