Vector Database Global Market Report 2024 - by Growth, Share, Trends, Demand, Forecast To 2033

The vector database market size has grown exponentially in recent years. It will grow from $1.98 billion in 2023 to $2.46 billion in 2024 at a compound annual growth rate (CAGR) of 24.3%. The growth in the historic period can be attributed to geospatial data explosion, rise of location-based services (lbs), growing applications in smart cities, emergence of 5g network, demand for real-time spatial analytics.

The vector database market size is expected to see exponential growth in the next few years. It will grow to $5.76 billion in 2028 at a compound annual growth rate (CAGR) of 23.7%. The growth in the forecast period can be attributed to rise of digital mapping, telecommunication network planning, gps and satellite technology, environmental and natural resource management, transportation and logistics planning. Major trends in the forecast period include spatial analytics and business intelligence, integration with cloud services, real-time geospatial applications, smart infrastructure development, cross-industry collaboration.

Market Overview -
A vector database is an assortment of data kept in mathematical form. Vector databases make it simpler for machine learning models to recall prior inputs, allowing them to be utilized in search, suggestion, and text generation applications. Vector databases are designed to manage vector embeddings and provide a comprehensive solution for the administration of semi-structured and unstructured information.

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Cloud-Driven Surge Accelerating Growth In The Vector Database Market
The increasing use of cloud platforms is expected to propel the growth of the vector database market in the coming years. A cloud platform is the computer's operating system and components of a server in an Internet-connected data center. It enables hardware and software products to coexist independently and at scale. Vector databases on cloud platforms provide for effective retrieval and storage of high-dimensional data, enabling real-time analytics, deep learning, and tailored content suggestions while using scalable and adaptable infrastructure. For instance, in December 2023, according to Eurostat, a Europe-based intergovernmental organization, 42.5% of EU enterprises used cloud computing in 2023, primarily for hosting their e-mail systems and storing files in electronic form, an increase of 4.2% compared to 2021. Therefore. Therefore, the increasing use of cloud platforms is driving the vector database market.

Competitive Landscape -
Major companies operating in the vector database market report are Google LLC (Alphabet Inc.), Microsoft Corporation, Amazon Web Services Inc., Alibaba Cloud, Elastic N.V., MongoDB Inc., FD Technologies PLC, DataStax Inc., Redis Ltd., Vector AI, GSI Technology Inc., Chroma DB, Vald, SingleStore, OpenSearch, Rockset Inc., PlanetScale, Kinetica DB Inc., Qdrant, ClickHouse Inc., Clarifai Inc., Pinecone Systems Inc., Vespa ai, Marqo AI, Activeloop, Zilliz, Milvus, S2Search Australia Pty Ltd, Weaviate

Transformative Use Of Vector Databases For Generative AI And Enhanced Developer Productivity
Major companies operating in the vector database market are focusing on the integration of vector databases with technologies such as AI vector similarity search to enhance generative AI and substantially boost developer productivity. AI vector similarity search is a technique that involves using artificial intelligence (AI) algorithms to compare and find similarities between vectors in a dataset. For instance, in September 2023, Oracle Corporation, a US-based computer technology company, announced the inclusion of semantic search capabilities employing AI vectors into Oracle Database 23c. The AI Vector Search feature set includes an innovative vector data type, vector indexes, and vector search SQL operators that allow the Oracle Database to store semantic information of pictures, documents, and other unstructured information as vectors and employ these to run fast resemblance queries. AI vector similarity search in Oracle Database 23c provides the integration of search on semantic and business data, resulting in highly accurate responses rapidly and securely. These new capabilities also allow Retrieval Augmented Generation (RAG), a ground-breaking generative AI approach that uses large language models (LLMs) and private corporate data to respond to natural language inquiries.

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Key Segments -
The vector database market covered in this report is segmented -
1) By Database Type: Relational Vector Databases, NoSQL Vector Databases, NewSQL Vector Databases
2) By Offering: Solutions, Services
3) By Deployment Mode: On-Premises, Cloud-Based
4) By Industry: Financial Services, Healthcare And Life Sciences, Retail And E-Commerce, Manufacturing, Telecommunications, Government And Public Sector, Energy And Utilities, Transportation And Logistics, Media And Entertainment, Other Industries

Key highlights covered in the report -
1. Detailed market size forecast and historical data analysis
2. Key drivers influencing market growth
3. Identification of upcoming trends and potential opportunities in the market
4. Analysis of major players strategies, to understand competitive dynamics and market positioning
5. Evaluation of regional dynamics

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