Cribl Lake Description
Experience the freedom of storage that allows data to flow freely without restrictions. With a managed data lake, you can quickly set up your system and start utilizing data without needing to be an expert in the field. Cribl Lake ensures you won’t be overwhelmed by data, enabling effortless storage, management, policy enforcement, and accessibility whenever necessary. Embrace the future with open formats while benefiting from consistent retention, security, and access control policies. Let Cribl take care of the complex tasks, transforming data into a resource that delivers value to your teams and tools. With Cribl Lake, you can be operational in minutes instead of months, thanks to seamless automated provisioning and ready-to-use integrations. Enhance your workflows using Stream and Edge for robust data ingestion and routing capabilities. Cribl Search simplifies your querying process, providing a unified approach regardless of where your data resides, so you can extract insights without unnecessary delays. Follow a straightforward route to gather and maintain data for the long haul while easily meeting legal and business obligations for data retention by setting specific retention timelines. By prioritizing user-friendliness and efficiency, Cribl Lake equips you with the tools needed to maximize data utility and compliance.
Cribl Lake Alternatives
AnalyticsCreator
Accelerate your data journey with AnalyticsCreator—a metadata-driven data warehouse automation solution purpose-built for the Microsoft data ecosystem. AnalyticsCreator simplifies the design, development, and deployment of modern data architectures, including dimensional models, data marts, data vaults, or blended modeling approaches tailored to your business needs.
Seamlessly integrate with Microsoft SQL Server, Azure Synapse Analytics, Microsoft Fabric (including OneLake and SQL Endpoint Lakehouse environments), and Power BI. AnalyticsCreator automates ELT pipeline creation, data modeling, historization, and semantic layer generation—helping reduce tool sprawl and minimizing manual SQL coding.
Designed to support CI/CD pipelines, AnalyticsCreator connects easily with Azure DevOps and GitHub for version-controlled deployments across development, test, and production environments. This ensures faster, error-free releases while maintaining governance and control across your entire data engineering workflow.
Key features include automated documentation, end-to-end data lineage tracking, and adaptive schema evolution—enabling teams to manage change, reduce risk, and maintain auditability at scale. AnalyticsCreator empowers agile data engineering by enabling rapid prototyping and production-grade deployments for Microsoft-centric data initiatives.
By eliminating repetitive manual tasks and deployment risks, AnalyticsCreator allows your team to focus on delivering actionable business insights—accelerating time-to-value for your data products and analytics initiatives.
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Cribl Stream
Cribl Stream allows you create an observability pipeline that helps you parse and restructure data in flight before you pay to analyze it. You can get the right data in the format you need, at the right place and in the format you want. Translate and format data into any tooling scheme you need to route data to the right tool for the job or all of the job tools. Different departments can choose different analytics environments without the need to deploy new forwarders or agents. Log and metric data can go unused up to 50%. This includes duplicate data, null fields, and fields with zero analytical value. Cribl Stream allows you to trim waste data streams and only analyze what you need. Cribl Stream is the best way for multiple data formats to be integrated into trusted tools that you use for IT and Security. Cribl Stream universal receiver can be used to collect data from any machine source - and to schedule batch collection from REST APIs (Kinesis Firehose), Raw HTTP and Microsoft Office 365 APIs.
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Infor Data Lake
Addressing the challenges faced by modern enterprises and industries hinges on the effective utilization of big data. The capability to gather information from various sources within your organization—whether it originates from different applications, individuals, or IoT systems—presents enormous opportunities. Infor’s Data Lake tools offer schema-on-read intelligence coupled with a rapid and adaptable data consumption framework, facilitating innovative approaches to critical decision-making. By gaining streamlined access to your entire Infor ecosystem, you can initiate the process of capturing and leveraging big data to enhance your analytics and machine learning initiatives. Extremely scalable, the Infor Data Lake serves as a cohesive repository, allowing for the accumulation of all your organizational data. As you expand your insights and investments, you can incorporate additional content, leading to more informed decisions and enriched analytics capabilities while creating robust datasets to strengthen your machine learning operations. This comprehensive approach not only optimizes data management but also empowers organizations to stay ahead in a rapidly evolving landscape.
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BigLake
BigLake serves as a storage engine that merges the functionalities of data warehouses and lakes, allowing BigQuery and open-source frameworks like Spark to efficiently access data while enforcing detailed access controls. It enhances query performance across various multi-cloud storage systems and supports open formats, including Apache Iceberg. Users can maintain a single version of data, ensuring consistent features across both data warehouses and lakes. With its capacity for fine-grained access management and comprehensive governance over distributed data, BigLake seamlessly integrates with open-source analytics tools and embraces open data formats. This solution empowers users to conduct analytics on distributed data, regardless of its storage location or method, while selecting the most suitable analytics tools, whether they be open-source or cloud-native, all based on a singular data copy. Additionally, it offers fine-grained access control for open-source engines such as Apache Spark, Presto, and Trino, along with formats like Parquet. As a result, users can execute high-performing queries on data lakes driven by BigQuery. Furthermore, BigLake collaborates with Dataplex, facilitating scalable management and logical organization of data assets. This integration not only enhances operational efficiency but also simplifies the complexities of data governance in large-scale environments.
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Pricing
Free Version:
Yes
Free Trial:
Yes
Integrations
Company Details
Company:
Cribl
Year Founded:
2018
Headquarters:
United States
Website:
cribl.io/lake/
Media
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Product Details
Platforms
Web-Based
Types of Training
Training Docs
Live Training (Online)
Webinars
In Person
Training Videos
Customer Support
Business Hours
Online Support
Cribl Lake Features and Options
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