Data Warehouse

Matching Modern Databases with ML and AI

Introduction Machine Learning (ML) and Artificial Intelligence (AI) have stirred the technology sector into a flurry of activity over the past couple of years. However, it is important to remember that it all comes back to data. As Hilary Mason, a prominent data scientist, noted in Harvard Business Review*, …you can’t do AI without machine learning. You also can’t do machine learning without analytics, and you can’t do analytics without data infrastructure. Over the last year we...


2018 Gartner Magic Quadrant for Data Management Solutions for Analytics

The data management solutions for analytics market is evolving. Disruption is accelerating in this market, with more demand for broad solutions that address multiple data types and offer different delivery models. We are hosting complimentary access to the full Gartner Magic Quadrant for Data Management Solutions for Analytics, so you can learn more about what’s happening in this space. Access Here → MemSQL Positioned as Challenger in Gartner Magic Quadrant MemSQL has been positioned in...


A Brief Introduction to MemSQL

A Brief Introduction to MemSQL

We know choosing or evaluating a new database technology can be challenging due to the variety of choices available. In a recent webcast, we shared various use cases businesses face with traditional database and data warehouse technologies, key differentiators and architectures of MemSQL, sample applications and customer case studies, and a quick demo of MemSQL. MemSQL provides an adaptable database for real-time applications that unite transactions and analytics in a single high-performance...


Using MemSQL within the AWS Ecosystem

The database market is large and filled with many solutions. In this post, we will take a look at what is happening within AWS, the overall data landscape, and how customers can benefit from using MemSQL within the AWS ecosystem. Understanding the AWS Juggernaut At AWS re:Invent in December 2017, AWS CEO Andy Jassy revealed that the business is at a revenue run rate of $18 billion, growing 42 percent per year. Those numbers are staggering and showcase the importance Amazon Web Services now plays...


Data Warehouses and the Flying Car Dilemma

Traditional data warehouses and databases were built for workloads that manifested 20 years ago. They are sufficient for what they were built to do, but these systems are struggling to meet the demands of modern business with the volume, velocity, and user demand of data. IT departments are being challenged from both ends. On one side, companies want to analyze the deluge of data in real time, or near real time. On the other side, on the consumption end, the need to analyze and get value out of...


Why You Need a Real-Time Data Warehouse for IoT Applications

As always-on devices and sensors proliferate, the data emitted from these devices provides meaningful insights to improve customer experiences, optimize costs, and identify new revenue opportunities. In a recent report, Taking the Pulse of Enterprise IoT from McKinsey & Company, 48 percent of respondents cited “managing data” as a critical capability gap related to their IoT initiatives.1 The data infrastructure behind IoT applications requires a high performing and easy-to-access...


design blog

Designing for a Database: What’s Beyond the Query?

Even the most technically-minded companies need to think about design. Working on a database product at a startup is no different. But this comes with challenges, such as figuring out how to implement the human-centered design methodology at a technical company, but also contribute to building a design process that everyone agrees with across the organization. This blog will detail how product design is done at MemSQL as well as highlight how to design enterprise products at a startup.   How do...


Modern Data Warehousing, Meet AI

We are enchanted by the possibility of digital disruption. New computing approaches, from cloud to artificial intelligence and machine learning, promise new business models and untold efficiencies. We are closing the gap between science fiction and business operations. A Quick Look Back Let’s take a quick look back at data processing, and then come back to the industry frontier. It started with data and the place to put it, which became the database. Then came a desire to understand the data...


1.3 Billion NYC Taxi Rows into MemSQL Cloud

Experience teaches us that when loading data into a database, in whatever form ― normalized, denormalized, schema-less, hierarchical, key-value, document, etc ― the devil is always in the data load. For enterprise companies in the real-time economy, every second saved means improved efficiency, productivity, and profitability. Thankfully, MemSQL Cloud makes your enterprise data fast to load and easy to access. You can spin up a cluster in MemSQL Cloud in minutes and load data very quickly...


Key Considerations for a Cloud Data Warehouse

Data growth and diversity has put new pressures on traditional data warehouses, resulting in a slew of new technology evaluations. The data warehouse landscape offers a variety of options, including popular cloud solutions that offer pay-as-you-go pricing in an easy-to-use and scale package. Here are some considerations to help you select the best cloud data warehouse. First, Identify Your Use Case A cloud data warehouse supports numerous use cases for a variety of business needs. Here are some...