Amazon Security Lake Description
Amazon Security Lake seamlessly consolidates security information from various AWS environments, SaaS platforms, on-premises systems, and cloud sources into a specialized data lake within your account. This service enables you to gain a comprehensive insight into your security data across the entire organization, enhancing the safeguarding of your workloads, applications, and data. By utilizing the Open Cybersecurity Schema Framework (OCSF), which is an open standard, Security Lake effectively normalizes and integrates security data from AWS along with a wide array of enterprise security data sources. You have the flexibility to use your preferred analytics tools to examine your security data while maintaining full control and ownership over it. Furthermore, you can centralize visibility into data from both cloud and on-premises sources across your AWS accounts and Regions. This approach not only streamlines your data management at scale but also ensures consistency in your security data by adhering to an open standard, allowing for more efficient and effective security practices across your organization. Ultimately, this solution empowers organizations to respond to security threats more swiftly and intelligently.
Amazon Security Lake Alternatives
High-Performance Data Engineering. Total Sovereignty.
TIMi delivers the power of a complete cloud data stack—on-premises, fully sovereign, and ridiculously fast.
We reject artificial vendor lock-in and hidden costs. Instead, we offer absolute peace of mind through engineering excellence, giving your team the freedom to experiment, innovate, and solve complex AI, analytics, and automation challenges in record time.
Why Top Enterprises Choose TIMi?
Enterprise Integration & *No-Code* ETL/Data preparation: Automate complex workflows and seamlessly link your entire stack: SAP, Salesforce, SharePoint, S3, Azure Storage, PowerBI, Tableau, etc.
Unmatched Infrastructure Efficiency: Our competitors such as Databricks, Dataiku, and MS Fabric all rely on Spark—and that makes them inherently inefficient since a single €2k TIMi server outperforms a 267-node Spark cluster. TIMi process billions of rows in seconds and manage petabyte-scale data lakes at a fraction of the cost.
Proven AI Leadership: Harness pioneering machine learning from the creators of the first Auto-ML engine (est. 2007).
Whether deployed on-premises or via our EU-Hosted Sovereign Cloud, TIMi empowers leaders in Banking, Telecoms, Manufacturing, Retail, Defense and Government.
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Teradata VantageCloud: Open, Scalable Cloud Analytics for AI
VantageCloud is Teradata’s cloud-native analytics and data platform designed for performance and flexibility. It unifies data from multiple sources, supports complex analytics at scale, and makes it easier to deploy AI and machine learning models in production. With built-in support for multi-cloud and hybrid deployments, VantageCloud lets organizations manage data across AWS, Azure, Google Cloud, and on-prem environments without vendor lock-in. Its open architecture integrates with modern data tools and standard formats, giving developers and data teams freedom to innovate while keeping costs predictable.
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AWS Lake Formation
AWS Lake Formation is a service designed to streamline the creation of a secure data lake in just a matter of days. A data lake serves as a centralized, carefully organized, and protected repository that accommodates all data, maintaining both its raw and processed formats for analytical purposes. By utilizing a data lake, organizations can eliminate data silos and integrate various analytical approaches, leading to deeper insights and more informed business choices. However, the traditional process of establishing and maintaining data lakes is often burdened with labor-intensive, complex, and time-consuming tasks. This includes activities such as importing data from various sources, overseeing data flows, configuring partitions, enabling encryption and managing encryption keys, defining and monitoring transformation jobs, reorganizing data into a columnar structure, removing duplicate records, and linking related entries. After data is successfully loaded into the data lake, it is essential to implement precise access controls for datasets and continuously monitor access across a broad spectrum of analytics and machine learning tools and services. The comprehensive management of these tasks can significantly enhance the overall efficiency and security of data handling within an organization.
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Qlik Data Integration
The Qlik Data Integration platform designed for managed data lakes streamlines the delivery of consistently updated, reliable, and trusted data sets for business analytics purposes. Data engineers enjoy the flexibility to swiftly incorporate new data sources, ensuring effective management at every stage of the data lake pipeline, which includes real-time data ingestion, refinement, provisioning, and governance. It serves as an intuitive and comprehensive solution for the ongoing ingestion of enterprise data into widely-used data lakes in real-time. Employing a model-driven strategy, it facilitates the rapid design, construction, and management of data lakes, whether on-premises or in the cloud. Furthermore, it provides a sophisticated enterprise-scale data catalog that enables secure sharing of all derived data sets with business users, thereby enhancing collaboration and data-driven decision-making across the organization. This comprehensive approach not only optimizes data management but also empowers users by making valuable insights readily accessible.
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Pricing
Pricing Starts At:
$0.75 per GB per month
Free Trial:
Yes
Integrations
Company Details
Company:
Amazon
Year Founded:
1994
Headquarters:
United States
Website:
aws.amazon.com/security-lake/
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On-Premises
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Live Rep (24/7)
Online Support
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