PUBLISHER: KBV Research | PRODUCT CODE: 1373729
PUBLISHER: KBV Research | PRODUCT CODE: 1373729
The Global Data Lake Market size is expected to reach $51.3 billion by 2030, rising at a market growth of 19.8% CAGR during the forecast period.
Cloud-based data lakes integrate seamlessly with various data sources and cloud services, facilitating data ingestion, transformation, and integration. Consequently, the Cloud segment would capture around 45% share of the market by 2030. Cloud data lakes offer robust security features, encryption, access control, and compliance with industry-specific regulations, easing organizations' data governance and compliance efforts. Cloud-based data lakes are well-suited for running advanced analytics workloads, including machine learning and AI. Organizations can leverage cloud-based analytics services and tools to gain deeper insights from their data.
The major strategies followed by the market participants are Product Launches as the key developmental strategy to keep pace with the changing demands of end users. For instance, In July, 2023, Oracle Corporation unveiled MySQL HeatWave Lakehouse, allowing customers to query object storage data as quickly as database data. Additionally, In September, 2023, Dremio Corporation announced the next-generation Reflections for sub-second analytics, spanning the entire data ecosystem, regardless of data location. The new product redefines data access, enabling swift insights at 1/3 the cost of a cloud data warehouse.
Based on the Analysis presented in the KBV Cardinal matrix; Microsoft Corporation is the forerunners in the Market. In May, 2023, Microsoft Corporation unveiled Microsoft Fabric, a comprehensive unified analytics platform that consolidates essential data and analytics tools. The platform combines Azure Data Factory, to unleash the power of their data and prepare for the AI era. Companies such as Oracle Corporation, Amazon Web Services, Inc., Snowflake, Inc. are some of the key innovators in the Market.
Market Growth Factors
Increasing need to extract insights from vast volumes of data
Organizations are generating more data than ever, owing to digital transformation, IoT devices, social media, and other data sources. This explosion of data has created a demand for storage solutions that can endure massive amounts of structured and unstructured data. Data lakes can store various data types, including text, images, videos, log files, and sensor data. The growing need to extract insights from large volumes of data has driven organizations to invest in data lakes as a foundational data management and analytics solution. These platforms provide the agility, scalability, and flexibility needed to unlock the full potential of data and stay competitive in today's data-driven world. Hence, these factors will aid in the expansion of the market.
Rapid growth of advanced analytics technologies
The rapid growth of advanced analytics technologies has been a significant driver of the development of the market. Advanced analytics encompasses a range of sophisticated techniques and tools, including machine learning, artificial intelligence, predictive analytics, and data mining, which require extensive and diverse datasets for meaningful insights. Advanced analytics requires access to large volumes of historical and real-time data. Data lakes provide a cost-effective and scalable solution for storing massive datasets, making them readily available for analysis. Data lakes facilitate data preparation by providing a central location for raw data, enabling data engineers and scientists to access and shape data as needed. As organizations increasingly acknowledge the value of data-driven insights, data lakes play a vital role in enabling advanced analytics capabilities and driving innovation across various industries. Thus, the rapid growth of technologies will augment the expansion of the market.
Market Restraining Factors
Regulatory compliance-related data usage complexities
Regulatory bodies, such as the Health Insurance Portability and Accountability Act (HIPAA) in the United States and the General Data Protection Regulation (GDPR) in Europe, impose stringent data security and privacy requirements. Organizations using data lakes must implement strong safety measures to protect sensitive data and secure compliance with these regulations. Many regulations mandate specific data retention and deletion policies. Organizations must configure data lakes to adhere to these requirements, which can be complex when dealing with vast datasets. Beyond regulatory compliance, organizations must also consider legal and ethical aspects when managing data within data lakes. This includes addressing potential legal liabilities and ethical concerns associated with data use. The regulatory compliance challenges can pose obstacles for the market.
Component Outlook
On the basis of component, the market is segmented into solution and services. The services segment acquired a substantial revenue share in the market in 2022. Service providers offer ongoing support and maintenance to ensure the continued dependability and availability of the data lake environment. This includes monitoring, troubleshooting, and applying updates and patches. These services assist in ingesting data from various sources into the data lake. Service providers can help with data extraction, transformation, and loading (ETL) processes, ensuring that data is appropriately formatted and cleansed before storage.
Enterprise Size Outlook
By enterprise size, the market is bifurcated into large enterprises and small & medium enterprises. The large enterprises segment acquired the highest revenue share in the market in 2022. Data lakes are highly scalable, allowing organizations to store and manage petabytes of data or more as their data volume grows. This scalability accommodates the increasing data needs of large enterprises. Data lakes often use cost-effective storage solutions, such as cloud storage or Hadoop Distributed File System (HDFS), which can significantly reduce storage costs compared to traditional data warehousing.
Deployment Type Outlook
Based on deployment type, the market is fragmented into on-premise and cloud. The cloud segment garnered a significant revenue share in the market in 2022. Significant data lake parasol vendors provide cloud-based solutions that automate equipment maintenance processes and increase profits. In addition, the adoption of cloud data lakes is anticipated to increase due to their adaptability, scalability, flexibility, and cost-effectiveness. Companies favor cloud-based solutions, which facilitate cross-regional, cross-regional, and cross-national information storage and recovery strategies.
Vertical Outlook
By vertical, the market is classified into IT, BFSI, retail & Ecommerce, healthcare, media & entertainment, manufacturing, and others. The retail and Ecommerce segment recorded a remarkable revenue share in the market in 2022. Data lakes could play a crucial role in retail marketing, as they would facilitate rapid classification of potential customers. Data lakes would provide an in-depth understanding of buyers, their purchasing motivations, and their requirements by analyzing information gathered from various sources, such as call logs, surveys, and social media platforms. Retailers can analyze customer purchase patterns and discover associations between products frequently purchased together.
Regional Outlook
Region-wise, the market is analysed across North America, Europe, Asia Pacific, and LAMEA. In 2022, the North America region witnessed the largest revenue share in the market. The rapid pace of growth in North America can be attributed to the increasing use of big data technology, the rising volume of data across industry verticals, and the rising investment in data lake solutions by businesses. In the United States, associations have begun utilizing data lake solutions to generate actionable insights from structured and unstructured data to remain competitive. Growing the generation of data, such as clickstream data, server logs, customer data, customer relationship management (CRM), and Enterprise Resource Planning (ERP), causes vendors to launch multiple data lake services and products to cater to various demands of the organizations and their customers.
The market research report covers the analysis of key stake holders of the market. Key companies profiled in the report include Amazon Web Services, Inc., Cloudera, Inc., Dremio Corporation, Informatica Inc., Microsoft Corporation, Oracle Corporation, SAS Institute Inc., Snowflake Inc., Teradata Corporation and Zaloni, Inc.
Recent Strategies Developed in Data Lake Market
Partnerships, Collaborations, and Agreements:
Sep-2023: Cloudera, Inc. collaborated with Amazon Web Services, Inc., a subsidiary of Amazon that provides on-demand cloud computing platforms. This collaboration reinforces Cloudera's bond with AWS, pledging to advance cloud-native data management and analytics. It utilizes AWS services to provide ongoing innovation and cost savings for customers, supporting Cloudera's open data lakehouse on AWS for reliable enterprise generative AI.
Sep-2022: Snowflake Inc. strengthened its partnership with Endava, one of the world's leading providers of digital transformation consulting and agile software development services, to assist joint customers in their digital transformation. This collaboration aimed to enable data-driven strategies, enhance data governance and security, centralize cloud-based data, and democratize analytics across various business domains.
May-2022: Informatica Inc. partnered with Oracle, an American multinational computer technology company, to integrate Informatica's data integration and governance products, specifically the Intelligent Data Management Cloud (IDMC), with Oracle Cloud Infrastructure (OCI), including Oracle Exadata Database Service, Oracle Autonomous Database, Oracle Object Storage, and Oracle Exadata Cloud@Customer.
Apr-2022: Informatica inc. expanded its partnership with Snowflake, the Data Cloud Company. This partnership aimed to enhance integration between the Data Cloud and Informatica's Intelligent Data Management Cloud (IDMC), facilitating an expedited transition to the cloud for customers by offering extended data management and governance capabilities.
Oct-2021: Dremio Corporation partnered with InterWork, a global IT consulting & services company offering innovative and cutting-edge solutions. Under this partnership, InterWorks leveraged Dremio's capabilities for optimizing data lake investments, enhancing BI dashboards, and enabling interactive analytics, particularly with Tableau Software integration.
Product Launches and Product Expansions:
Sep-2023: Dremio Corporation announced the next-generation Reflections for sub-second analytics, spanning the entire data ecosystem, regardless of data location. The new product redefines data access, enabling swift insights at 1/3 the cost of a cloud data warehouse.
Jul-2023: Oracle Corporation unveiled MySQL HeatWave Lakehouse, allowing customers to query object storage data as quickly as database data. The lakehouse supports various object store file formats (CSV, Parquet, etc.) and can seamlessly merge object storage and MySQL database data in a single query.
Jul-2023: Teradata Corporation launched VantageCloud Lake analytics platform to Microsoft Azure, a cloud computing platform run by Microsoft. This version includes ClearScape Analytics, offering advanced analytics features, and utilizes Azure Data Lake Storage, a specialized Azure Blob Storage for enhanced capabilities.
Jun-2023: Snowflake, Inc. introduced a government and education data cloud, catering to public-sector agencies and educational institutions. This fully managed package simplifies data integration and application development, allowing organizations to harness their data for vertical-specific needs, from predictive capabilities to historical trend analysis.
May-2023: Amazon Web Services, Inc. launched Amazon Security Lake, a service that centralizes security data from various sources into a dedicated data lake. Amazon Security Lake standardizes incoming security data to the Open Cybersecurity Schema Framework (OCSF), streamlining its automatic collection, integration, and analysis from over 80 sources, encompassing AWS, security partners, and analytics providers.
May-2023: Informatica Inc. enhanced Intelligent Data Management Cloud (IDMC) with expanded data engineering services, including replication, ingestion, ELT, and data quality observability. These improvements offering advanced intelligence, automation, and a wider range of cloud data management services.
May-2023: Microsoft Corporation unveiled Microsoft Fabric, a comprehensive unified analytics platform that consolidates essential data and analytics tools. The platform combines Azure Data Factory, Azure Synapse Analytics, and Power BI into a single product, enabling data and business professionals to unleash the power of their data and prepare for the AI era.
May-2023: Oracle Corporation unveiled new innovations to its Autonomous Data Warehouse, the first autonomous database for analytics workloads. These innovations promote multicloud compatibility, open standard-based data sharing, and simplified data integration and analysis through a low-code tool, departing from the closed nature of traditional data warehouses and lakes.
Mar-2023: Amazon Web Services, Inc. added new features to Amazon S3, a service offered by Amazon Web Services that provides object storage through a web service interface. The new features allow third-party data sales without duplicating data to another S3 bucket and introduce Mountpoint for Amazon S3, an open-source file client. This accelerates and reduces the cost of building data lakes for customers.
Aug-2022: Cloudera, Inc. introduced CDP One, a single software-as-a-service (SaaS) solution for data lakehouses, facilitating self-service analytics and data science on diverse data types. CDP One boasted built-in enterprise security and machine learning, reducing costs and risk without needing extra staff. It enhanced productivity for data experts and developers, enabling quicker business insights and fostering innovation.
Aug-2022: Teradata Corporation unveiled VantageCloud Lake, a cloud-native product built on a new architecture. It combines Teradata Vantage's capabilities with cloud elasticity, cost-efficiency, and scalability, named VantageCloud Enterprise, designed for ease of use and flexibility.
Mar-2022: Snowflake, Inc. introduced the Data Cloud for Retail, following the recent launch of the Healthcare and Life Sciences Data Cloud. The cloud provides a dedicated platform to tackle data challenges in the retail industry for stakeholders like retailers, manufacturers, distributors, and CPG vendors.
Jul-2021: Dremio Corporation unveiled Dremio Cloud, a cloud service that streamlines data lake creation and management, allowing for in-memory SQL queries on object-based storage, eliminating the necessity for internal IT teams to handle these tasks.
Dec-2020: Amazon Web Services Inc. introduced Amazon HealthLake, a HIPAA-eligible healthcare data lake service that centralizes and normalizes data from various sources using machine learning, tagging critical information and creating a standardized timeline.
Acquisition and Mergers:
Jun-2020: Microsoft Corporation acquired ADRM Software, a supplier of extensive industry data models. With combined ADRM and Azure's expansive storage and computing capabilities, customers and channel partners can now establish intelligent data lakes in the cloud.
Market Segments covered in the Report:
By Component
By Enterprise Size
By Deployment Type
By Vertical
By Geography
Companies Profiled
Unique Offerings from KBV Research