Data Lake Market Size, Share, Growth Analysis, By Deployment (On-premises, Cloud), By Vertical (IT, Retail), By Type (Solution, Services), By Region -Industry Forecast 2025-2032

Global Data Lake Market size was valued at USD 13.62 billion in 2023 and is poised to grow from USD 16.86 billion in 2024 to USD 93.04 billion by 2032, growing at a CAGR of 23.8% in the forecast period (2025-2032).

The rise of big data and the need for advanced analytics solutions fueled the demand for data lakes. Organizations wanted to store and process vast amounts of diverse data types efficiently. The proliferation of data due to adopting the Internet of Things (IoT) has been a significant driver of the data lakes market. IoT devices generate an enormous volume of data, often in real time. Data lakes can handle this massive influx of data without compromising performance.The growing importance of AI and machine learning in data analytics has led to a surge in the adoption of data lakes. Data lakes provide the necessary infrastructure to store and process the vast amounts of data required for advanced analytics and machine learning models. Organizations are leveraging data lakes to ingest, store, and prepare data for training these models, leading to more accurate predictions, personalized recommendations, and enhanced decision-making. As AI and machine learning technologies continue to evolve, the demand for data lakes capable of supporting these capabilities will only increase. The demand for real-time insights has led to the integration of real-time data processing and streaming capabilities in data lakes. Organizations are leveraging technologies like Apache Kafka, Apache Spark Streaming, and Amazon Kinesis to ingest, process, and analyze data in near real-time. This enables them to make timely, data-driven decisions and respond quickly to changing market conditions or customer needs.

The rise in the number of digital payments is increasing the amount of transactional data in banks across the globe. Several banks are investing in developing data lakes to improve their analytical abilities to provide on-the-go solutions to their customers. Banks, including Australia and New Zealand Banking Group and State Bank of India, have already started developing data lakes to integrate data across domains and create a central database. Thus, data lakes allow banks to aggregate data from all the data ponds across the domains into a central database that can be accessed by any individual in real time.