Author
Freja Mickos
Freja is a summer marketing intern at SingleStore, and is currently a student at the University of Boston
Data Intensity
In-Memory Database Survey Reveals Top Use Case: Real-Time Analytics
To shed light on the state of the in-memory database market, we conducted a survey on the prevalent use cases for in-memory databases. Respondents included software architects, developers, enterprise executives and data scientists1. The results revealed a high demand for real-time capabilities, such as analytics and data capture, as well as a high level of interest in Spark Streaming.
Real-Time Needs for In-Memory Databases
It is no surprise that our survey results highlight real-time analytics as the top use case for in-memory databases. For years, big data was heralded as the future of technology – today, it is a reality for companies big and small. Going real-time is the next phase for big data, and people seek technologies that address real-time data needs above all else. Those who can successfully converge transactional and analytical data processing, see greater efficiency in data management and have an invaluable advantage over their competitors.
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SingleStore Cited As a Strong Performer by Independent Research Firm
As adoption of in-memory databases grows at a faster and faster pace, IT leaders turn to research firms to find valuable use cases and guidance for purchasing options. We are thrilled to share that SingleStore was among the select companies that Forrester Research invited to participate in its 2015 Forrester Wave™ evaluation. In this evaluation, SingleStore was cited as a strong performer for in-memory database platforms. The report, The Forrester Wave™: In-Memory Database Platforms, Q3 2015, evaluates in-memory databases across three categories: current offering, strategy and market presence.
SingleStore received some of its highest scores in the subcategories of scale-out architecture, performance and scale, and product road map. Much of our company’s recent growth and success can be attributed to our strong leadership team and constant iteration from engineering on the product, as we work closely with our customers to solve their big data and analytics challenges.
Authors of the Forrester Wave™ write, “today’s in-memory database platforms are changing the way we build and deliver systems of engagement and are transforming the practice of analytics, predictive modeling, and business transaction management.” At SingleStore, we have championed in-memory computing since day one. When Eric Frenkiel and Nikita Shamgunov left Facebook to start SingleStore, they knew that a real-time, in-memory approach to data processing and analytics was the answer to closing gaps for enterprises using big data. The major benefit of in-memory platforms is the great performance they provide when working with massive volumes of data. We believe the Forrester Wave™ report validates this approach, stating that “the in-memory database market is new but growing fast as more enterprise architecture professionals see in-memory as a way to address their top data management challenges.”
There’s another reason why in-memory technology is going to become even more critical in the next several years: predictive applications. Consumers desire personalization from every single application they use across numerous devices. Data is at the crux of predictive analytics, which transcends “context-aware” technology by enabling seamless interaction between customer and app. Companies need instantaneous access to hot data to power these kinds of seamless interactions.
Many of our customers are in the throes of building predictive applications, and we get to provide fast, scalable infrastructure to support them. Overall, we are very excited that SingleStore has been recognized by Forrester as a strong performer. The Forrester Wave™ concludes its section on SingleStore with the following line: “customers that are building new transactional and analytical applications that need extreme performance and low-latency access and want a single database platform should look at SingleStore.” We agree.
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Five Data Persistence Dilemmas CIOs Will Face
At SingleStore, we see an in-memory, distributed approach to big data as the path forward to cost-effective deployments. Recently, Gartner released a report titled “Five Data Persistence Dilemmas That Will Keep CIOs Up at Night”, which reinforces this approach to data management.The report outlines three key impacts of utilizing new technologies across HTAP, or Hybrid Transaction/Analytical Processing, for in-memory processing, the compromises of NoSQL DBMSs, and the growing importance of agile cloud computing approaches.Download a complimentary copy of the Gartner Report: Five Data Persistence Dilemmas That Will Keep CIOs Up at NightKey Impacts from the Gartner ReportThe convergence of transaction and analytic database systems in hybrid transaction/analytical processing (HTAP) systems that use in-memory processing reduces the need for separate dedicated environments and shortens the time to value for new data, but it requires IT Leaders to make process compromises and changes to applications to maximize ROI.NoSQL DBMSs compromise a priori data models and strong levels of consistency to offer IT leaders high-throughput operations and scale-out architectures.Agile deployment approaches like cloud computing will present new opportunities that IT leaders and line-of-business heads must seize.The CIO DilemmasThe five dilemmas covered in the report generate a number of questions that CIOs must ask with any new database technology. We receive these questions daily from customers seeking to maximize opportunities with HTAP, scalable SQL databases, and flexible cloud deployments.The Single-Database DilemmaFor decades, data processing has been split into databases for Online Transaction Processing and data warehouses for Online Analytical Processing. HTAP, largely enabled by in-memory computing, collapses the single database model and allows for the definition of new classes of applications, like those that fuse real-time and historical analysis.The HTAP Adoption DilemmaMoving from split OLTP and OLAP to converged HTAP requires thorough cost and capacity planning that does not happen overnight. Fully realizing the benefits of HTAP means transactions and analytics are easily integrated with existing or net new applications. HTAP results in less precomputation and more real-time queries.The Consistency DilemmaNoSQL databases gave up traditional consistency, and abandoned SQL, to achieve scalability. Fortunately, you can have scalability, performance, simplicity and SQL with an in-memory database like SingleStore.The Schema DilemmaYou can define your structure up front, or define it later. However, multi-model databases like SingleStore support structured SQL and semi-structured data types like JSON, so you get the best of both worlds.The Cloud DilemmaWhile some database offerings restrict deployment choice, SingleStore can be deployed on-premises or in the cloud.Try HTAP, Scalable SQL, and Cloud Databases TodayIf you would like a hands-on look at HTAP, scalable SQL, and cloud deployments with in-memory databases, try SingleStore Community Edition, available for free with unlimited capacity and scale. If you would like support or high availability features, try SingleStore Enterprise Edition free for 30 days.
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