We're happy to announce that the MongoDB Atlas app is now available in the Sumo Logic app catalog. MongoDB Atlas is a globally distributed cloud database service and the easiest way to run MongoDB in the cloud. Atlas offers best-in-class automation, built-in security controls, and proven best practices to protect your data and scale your applications.

We all expect our phones to make and take calls and our credit cards to process payments whether day or night. Business transactions are expected to always be completed on time, with no margin for downtime. With this, software has become the lifeblood of many, if not most, enterprises and public services.

Being able to execute a SQL performance tuning is a vital skill for software teams that rely on relational databases. Vital isn’t the only adjective that we can apply to it, though. Rare also comes to mind, unfortunately. Many software professionals think that they can just leave all the RDBMS settings as they came by default. They’re wrong. Often, the default settings your RDBMS comes configured with are far from being the optimal ones.

Analyst firm Gartner recently predicted that “75% of all databases will be deployed or migrated to a cloud platform by 2022, with only 5% ever considered for repatriation to on-premises.” Enterprise architects are deploying analytics, artificial intelligence, and machine learning workloads on cloud database platforms for greater scalability and lower operational overhead.

As discussed in multi-data source Flux, Flux can now get data out of RDBMs with SQL.from() and use it to perform deeper analysis. In many cases, results from crunching data lend themselves naturally to time series storage. In others, the results are more appropriately leveraged on different data stores. In order to fulfill Flux’s general-purpose analysis engine vision, data must flow both into and out of InfluxDB.

For any given task, there are many tools you can use. But few are the right tools. If you’re in IT, you’ve probably heard the saying “Use the right tool for the job.” In architects’ meetings, this sentence echoes from one corner to the other. In my career, I’ve heard it more times than I can count. And the wisdom behind it has stood the test of time. That’s because when it comes to how data is stored, it’s not one-tool-fits-all for every type of data.

Maintaining the health and performance of your IT infrastructure can be one of the biggest headaches you face in your time as an IT professional. With so many moving parts it can be nearly impossible to keep track of them all and how they interact with each other making it quite difficult to efficiently and successfully monitor MongoDB. One day you may log into your MongoDB environment and it’s not returning your queries, or you’re not getting the results you expected.

Relational databases have commonly been an essential component of every application. Cloud vendors like GCP have a service for relational databases. GCP’s relational database offering is GCP Cloud SQL, which is a managed service for relational databases similar to RDS from AWS.

The world is becoming increasingly aware of the massive amounts of data floating around the internet. Not surprisingly, many people have concerns about this. These concerns have led to a lot of legislation around data privacy, of which GDPR is just one of many. On top of all of this, there’s been the exposure of thousands of MongoDB databases on the internet.

Our databases are the ones that keep the Internet alive. There has even been talk for some years about the development of operating systems with which users do not have direct contact with the files, but their personal files are stored in a local DB. In fact, we already see how there are online services that do this for us, such as Google Drive or Nextcloud, the latter written under free license Affero.