KX parlays existing database engine to deliver a new pure-play vector database
James Curtis is a senior research analyst at S&P Global Market Intelligence, leading the database and data platforms vertical within the Data, AI & Analytics channel. Previously, he covered business intelligence, analytics and reporting, along with machine learning and data science. James’ current areas of concentration include database and related technology analysis, real-time analytics, cloud computing and cloud-native technologies for database as a service, database optimization tooling, generative AI and retrieval augment generation (RAG) environments, including vector stores and semantic search. James arrived at S&P Global Market Intelligence through its 2019 acquisition of 451 Research, which he joined in 2015. Prior to 451 Research, he held several senior roles in technology, marketing and communications. He served as VP of a large BPO firm where he oversaw marketing for analytic solutions. He held senior technical marketing roles at Netezza and later at IBM with responsibility for data warehousing, analytics and big-data products. He has managed global programs at HPE and worked as a case editor at Harvard Business School. James holds a bachelor's degree in English from Utah State University, a master's degree in writing from Northeastern University in Boston and an MBA from Texas A&M University.
Having built its data lakehouse offering that enables a "single point of access," Starburst is expanding its platform further by adding capabilities enabling enterprises to deploy applications with significant data requirements; specifically, interactive applications with near real-time needs.
The processing of streams of data in motion is an important component of the data streaming architectures organizations are developing to reduce latency in decision-making, and improve the reactivity of software applications. The addition of stream processing to MongoDB's platform aims to harmonize developer interactions with streaming and at-rest data.
The company considers generative AI a transformative technology. One expectation is that customers will want to interact with their data, using natural language to "talk to the data." While this full vision is not yet manifest, the announcement of Amazon Q is an initial building block for this AI-based strategy.
The startup has built a cloud database platform service on the open-source ClickHouse database, which can deliver analytics in real time. Traditional data warehouses may be the workhorse database for analytics, but these systems may not deliver results fast enough. ClickHouse is looking to target specific OLAP-type workloads that require real-time results.
This report highlights some of the key topics we expect to be prominent in 2024 in the data, AI and analytics sectors. Generative AI obviously takes the headlines, but for the technology to succeed, preexisting issues around data management, data operationalization (DataOps), machine learning operationalization (MLOps) and other infrastructure-related tasks need to be solved.
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