The B2B platform for the best purchasing descision. Identify and compare relevant B2B manufacturers, suppliers and retailers
Close
Filter
Result configuration
Continents
Select continent
Locations
Result types
Company type
Select company type
Industries
Select industry
Company status
Select company status preset
Number of employees
Min.
Max.
Founding year
DataLakeHouse
-
1-10 Employees
2019
Key takeaway
DataLakeHouse.io (DLH.io) specializes in data orchestration, ELT, and data security, providing a streamlined platform that allows businesses to automate workflows and focus on delivering insights. With its pre-built source connector integrations and a strong emphasis on collaboration and efficiency, DLH.io transforms data management, making it easier to harness data for strategic decision-making.
Reference
Core business
DataLakeHouse.io
Databricks Ventures
San Francisco, United States
B
1001-5000 Employees
2013
Key takeaway
Databricks is highlighted as a leader in the data lake space, offering a unique lakehouse platform that integrates the advantages of both data lakes and data warehouses. This approach allows users to unlock the full potential of their data, particularly through Azure Databricks.
Reference
Product
Data Lakehouse Platform – Databricks
Click to learn how to unlock the potential of your data lake with Azure Databricks.
Lakebed.io
Vancouver, Canada
A
1-10 Employees
2018
Key takeaway
Lakebed serves as a central hub for storing and managing data from various sources, allowing users to easily create reports and gain a comprehensive view of their marketing initiatives. With its user-friendly interface and ability to quickly install and populate a data lake, Lakebed simplifies the process of transforming disorganized data into actionable intelligence.
Reference
Core business
Lakebed.io | Data lakes made easy
Looking for more accurate results?
Find the right companies for free by entering your custom query!
25M+ companies
250M+ products
Free to use
Lake Network
Bengaluru, India
D
1-10 Employees
2019
Key takeaway
Lake offers secure, reliable, and decentralized file storage, making it an ideal partner for apps that require efficient data management. With SDKs available for easy integration into Desktop, Web, and Mobile applications, Lake supports developers in creating robust decentralized storage solutions for DApps and blockchains.
Reference
Core business
Lake - Decentralized Storage for DApps and Blockchains.
SmartDataLake
Vienna, Austria
A
11-50 Employees
-
Key takeaway
SmartDataLake focuses on creating innovative methods and tools for advanced analytics over Big Data Lakes, highlighting their expertise in sustainable data management for extreme-scale analytics.
Reference
Core business
SmartDataLake
Treeverse
Tel-Aviv, Israel
B
11-50 Employees
2020
Key takeaway
lakeFS by Treeverse is a data version control platform that simplifies the lives of data engineers, data scientists, and analysts, enabling them to manage their data like code. With features that support best practices in data engineering, lakeFS enhances data quality and allows for effective testing and experimentation.
Reference
Core business
Git for Data - lakeFS
lakeFS is an open-source data version control that transforms your object storage to Git-like repositories. Start managing data the way you manage your code.
Qubole
United States
B
251-500 Employees
2011
Key takeaway
Qubole, an Idera Inc company, offers a simple and secure data lake platform designed for machine learning, streaming, and ad-hoc analytics, providing end-to-end services that streamline data management and analytics. With a focus on cost-efficiency and flexibility, Qubole supports organizations in leveraging their data assets for real-time insights and historical analysis, making it a valuable solution for modern data architecture and big data integration.
Reference
Product
Cloud Data Lake | Solutions | Qubole
Qubole is a big data integration and data lake platform that provides comprehensive solutions for all types of cloud data lake projects.
Fast Forward Labs
New York, United States
B
1-10 Employees
2014
Key takeaway
Cloudera offers a comprehensive Data Lake Service that enables organizations to create and maintain secure and governed data lakes across various storage architectures. This service is designed to help businesses efficiently manage and derive real-time insights from their data, driving value and competitive differentiation.
Reference
Product
Data Lake Service | Cloudera
Create safe, secure, and governed data lakes, protecting your data wherever it’s stored, from object stores to Hadoop Distributed File System (HDFS), with Cloudera Data Lake Service.
DataPhoenix
Bracknell, United Kingdom
A
1-10 Employees
2019
Key takeaway
DataPhoenix specializes in creating data lakes, transforming diverse data streams into a unified and valuable resource for businesses. Their expertise in data discovery and cloud solutions empowers organizations to unlock the potential of their data, enabling them to compete effectively in the data-driven landscape.
Reference
Service
Data Lake – DataPhoenix.io
Data Lake Transform a flood of data from multiple streams into a single, navigable data lake that delivers real business value. Contact Us Data Lake Services Why? Time was you could invest in a single operational database or CRM system and that would be a single source of truth for all your business information. In
Loamics
Boulogne-Billancourt, France
A
51-100 Employees
-
Key takeaway
Loamics specializes in data management solutions, particularly through its Data Lake architecture, which facilitates data-driven decision-making by cross-referencing diverse and secure data in real time. This approach accelerates digital transformation and enhances the use of Data Science and Artificial Intelligence across various business sectors.
Reference
Product
DataLake - Loamics
LOAMICS provides data management solutions on Data Lake architecture forquality machine learning data. It works seamlessly on Microsoft Azure.
Technologies which have been searched by others and may be interesting for you:
A data lake is a centralized repository that allows organizations to store vast amounts of structured and unstructured data at scale. This storage solution enables users to retain data in its raw form, making it accessible for various analytics and processing tasks. Unlike traditional databases, which require data to be pre-processed and structured, data lakes can accommodate diverse data types, including text, images, and videos, facilitating advanced analytics, machine learning, and real-time processing. In addition, data lakes support big data technologies, allowing organizations to leverage tools like Apache Hadoop and Apache Spark for data processing and analytics. This flexibility helps businesses harness valuable insights from their data, driving better decision-making and innovation.
A data lake stores vast amounts of raw data in its native format until it is needed for analysis. This flexibility allows organizations to accommodate various data types, including unstructured and semi-structured data, which can be ingested without a predefined schema. In contrast, a data warehouse is designed for structured data and requires a defined schema before data can be loaded, optimizing it for complex queries and reporting purposes. The scalability of a data lake enables it to handle large volumes of data, making it suitable for big data analytics. On the other hand, data warehouses offer faster query performance due to their structured nature, but they may struggle with accommodating the diverse data types found in modern data environments.
1. Scalability
Data Lakes offer scalable storage solutions that can accommodate vast amounts of structured and unstructured data. This flexibility allows organizations to grow their data storage needs without significant investment in new infrastructure.
2. Cost-Effectiveness
Utilizing a Data Lake can be more cost-effective compared to traditional data warehousing. By leveraging inexpensive storage options, companies can store large volumes of data without incurring high costs, making it accessible for analysis and processing.
3. Diverse Data Types
Data Lakes support a variety of data formats, including raw data, semi-structured, and structured data. This capability enables businesses to gather insights from diverse sources, enhancing data analysis and decision-making processes.
4. Real-Time Analytics
Data Lakes facilitate real-time data processing, allowing businesses to analyze and act on data as it arrives. This immediacy can lead to quicker insights and more informed business decisions.
5. Enhanced Flexibility
The architecture of Data Lakes provides a high level of flexibility for data ingestion and processing. Organizations can easily adapt to changing data requirements and integrate various data sources without extensive reconfiguration.
1. Big Data Analytics
Data lakes are often employed for storing vast amounts of unstructured data, enabling organizations to perform advanced analytics and gain insights from diverse data sources.
2. Data Archiving
Organizations use data lakes to archive historical data that may not be needed for immediate analytics but is valuable for compliance and future analysis.
3. Machine Learning
Data lakes provide a platform for data scientists to access and process large datasets, facilitating the development and training of machine learning models.
4. Real-Time Data Processing
With the ability to ingest data streams, data lakes support real-time analytics, allowing businesses to respond swiftly to changing conditions.
5. Data Integration
Data lakes serve as a centralized repository, integrating data from various sources, which simplifies data management and enables a holistic view of an organization’s information.
Ensuring security in a Data Lake involves implementing multiple layers of protection. One approach is to utilize encryption for data at rest and in transit, which safeguards sensitive information from unauthorized access. Another essential aspect is access control, where organizations can define user roles and permissions to limit access to specific datasets. Utilizing identity and access management (IAM) tools helps in monitoring and managing user activities, ensuring only authorized personnel can interact with the data. Additionally, regular audits and compliance checks can help identify vulnerabilities and ensure that security policies are being adhered to.
Some interesting numbers and facts about your company results for Data Lake
| Country with most fitting companies | United States |
| Amount of fitting manufacturers | 6455 |
| Amount of suitable service providers | 6351 |
| Average amount of employees | 11-50 |
| Oldest suiting company | 2011 |
| Youngest suiting company | 2020 |
20%
40%
60%
80%
Some interesting questions that has been asked about the results you have just received for Data Lake
What are related technologies to Data Lake?
Based on our calculations related technologies to Data Lake are Big Data, E-Health, Retail Tech, Artificial Intelligence & Machine Learning, E-Commerce
Which industries are mostly working on Data Lake?
The most represented industries which are working in Data Lake are IT, Software and Services, Other, Consulting, Finance and Insurance, Logistics, Supply Chain and Transportation
How does ensun find these Data Lake Companies?
ensun uses an advanced search and ranking system capable of sifting through millions of companies and hundreds of millions of products and services to identify suitable matches. This is achieved by leveraging cutting-edge technologies, including Artificial Intelligence.
