MongoDB vs DynamoDB: How do you choose between them? Whether you are a two-man team bootstrapping a proof of concept or an established one battling with high throughput and heavy load; this post can serve as a guidepost in your decision process. Before going into the details, a brief history lesson on how these technologies emerged is pertinent; you must understand the optimal conditions for running these systems and how they operate in the wild before making an informed choice.

According to Gartner, leading organizations in every industry are wielding data and analytics as competitive weapons. Companies that leverage data as a competitive differentiator will stand the best chance of acting faster on opportunities and responding to threats in a competitive marketplace. The problem is that most companies aren’t aware of the value of their data. As a result, they aren’t leveraging the full potential of their data to make informed decisions.

Sometime in 2019, Netflix cracked a conundrum that stumped them for years. The company had so much data about its content and subscribers, it had to sync multiple heterogeneous data stores like MySQL and Elasticsearch continuously, which brought seriously stressful challenges like dual writes and distributed transactions. So Netflix created its own CDC tool that processes captured log events in sequence and takes dumps for specific tables and primary keys of tables. Problem sorted. Case closed.

Imagine this: less than half an organization’s structured data is used in decision-making. Think of the missed opportunities for customer acquisition and revenue by not taking advantage of that information. According to an IBM study, 87 percent of CEOs regard data as a strategic asset. So why then are companies not harnessing the power of this information?

Reverse ETL is a data integration technology that offers a wonderful way to enable solutions for making various stored data more actionable and usable. This process is especially helpful for enterprise business operation tools that help teams execute processes and meet goals more effectively. The idea is to use clean and accurate data to enhance various SaaS platforms and business management tools to enhance processes.

Intercom bills itself as a “conversational relationship platform,” helping businesses connect with their audiences primarily through live chat, as well as email and chatbots. The Intercom platform offers functionality including engagement and onboarding for new customers, support for existing customers, and marketing for potential customers on the fence.

REST API provides a solution for communicating easily with various apps, platforms, and web services. This tool allows the user to communicate and execute actions universally with various languages and more. Companies implementing REST API stand to gain a better experience and create more flexibility when using ERPs, CRMs, and more like Salesforce. When users connect to Salesforce with a REST API, they get more flexibility and options that make the process more actionable and streamlined.

Change data capture is one of the fundamental underpinnings of modern data management. Without knowing when their enterprise data has changed or refreshed with new information, businesses wouldn’t be able to access up-to-the-minute insights that help them stay competitive in a constantly shifting landscape. In change data capture (CDC), users are promptly notified (either in real-time or near real-time) when changes have been made to a source table or source database.

In this guide, we'll discuss what a database schema is, six database schema designs, and how and why they are used. We know a lot of thought goes into database construction. Before creating any database, developers plan what it should include and how the different aspects work together. This planning ensures a database has the necessary design for its intended use. Coders then use the schema to implement the database’s design.