Table of Contents
- Executive Summary
- Overview
- Considerations for Adoption
- GigaOm Sonar
- Solution Insights
- Editor’s Note
- Near-Term Roadmap
- Analyst’s Outlook
- Report Methodology
- About Andrew Brust
- About GigaOm
- Copyright
1. Executive Summary
The key focus of real-time analytics is to power analysis that can deliver results and insights as events happen in the real world. To help achieve this instant analysis, a new category of databases—real-time analytical databases—has emerged. Real-time analytical databases work to ensure the data used in analysis is as up to date as possible. These databases have their roots in traditional online analytical processing (OLAP) databases; however, they surpass these predecessors by providing the ability to connect to and ingest extremely large (up to petabyte-scale) volumes of data, often from streaming data sources and batch or change data capture (CDC) sources. In doing so, they offer functionality found in both specialized business intelligence (BI) platforms and streaming data platforms and combine it with the core capabilities found in operational databases and data warehouses.
To facilitate analytics over large volumes of data with minimal latency, the databases in this category make use of structural and architectural optimizations. Examples include columnar orientation, various types of indexing, partitioning, and segmentation, precomputations of aggregations to accelerate queries, and vector processing. Scalability—the resilience of the system under the demands of increasing workloads—and high availability are also important in this category because of the time-critical nature of the analysis.
Real-time analytical databases allow organizations to see an up-to-the-minute view of the state of their data. This enables decisions to be made as events occur or as conditions change in the real world. This technology benefits any organization or user that needs data to be current and accurate. Use cases can take many practical forms, spanning different industries and target audiences. These can include healthcare, emergency response, cybersecurity, fraud detection, shipment and inventory tracking, personalized advertising, financial trading, and apps for food delivery or ridesharing. The time-sensitive criticality of some of these use cases is a primary factor driving the impact and urgency of adoption for these databases. The simple decreasing tolerance for latency among the modern everyday end users of an app, regardless of its intended function, drives urgency as well.
In terms of maturity, real-time analytical database technology is uniquely divergent. The online analytical processing (OLAP) methodology on which a number of these platforms are based (even if they use relational, rather than multidimensional, storage) represents a longstanding one. On the other hand, the workloads and use cases powered by real-time analytical databases are fresh and cutting-edge. The vendor landscape consists largely of newer, up-and-coming commercial offerings, often built upon open source databases.
This is the first year that GigaOm has reported on the real-time analytical database space in the context of our Sonar reports. This GigaOm Sonar provides an overview of vendors of real-time analytical databases and their available offerings, outlines the key characteristics that prospective buyers should consider when evaluating the solutions, and equips IT decision-makers with the information they need to select the best one for their business and use case requirements.
ABOUT THE GIGAOM SONAR REPORT
This GigaOm report focuses on emerging technologies and market segments. It helps organizations of all sizes to understand a new technology, its strengths and its weaknesses, and how it can fit into the overall IT strategy. The report is organized into five sections:
- Overview: An overview of the technology, its major benefits, and possible use cases, as well as an exploration of product implementations already available in the market.
- Considerations for Adoption: An analysis of the potential risks and benefits of introducing products based on this technology in an enterprise IT scenario. We look at table stakes and key differentiating features, as well as considerations for how to integrate the new product into the existing environment.
- GigaOm Sonar Chart: A graphical representation of the market and its most important players, focused on their value proposition and their roadmap for the future.
- Vendor Insights: A breakdown of each vendor’s offering in the sector, scored across key characteristics for enterprise adoption.
- Near-Term Roadmap: 12- to 18-month forecast of the future development of the technology, its ecosystem, and major players in this market segment.