The best Baidu EasyDAP alternatives

APM suits teams that need to follow requests across microservices and inspect application performance, errors, and dependencies.

It suits enterprise teams managing mixed-schema data lakes or building parallel data-processing and query workflows.

Parseable may suit teams that need logs, metrics, and traces in one observability platform, with a choice of self-hosted or managed deployment.

HDFS suits teams managing large data sets on self-hosted clusters that prioritize batch processing or streaming throughput.

Ozone is aimed at teams with lakehouse, AI/ML, cloud-native, Hadoop ecosystem, or other large-scale storage workloads.

It suits data analysts, engineers, and scientists working across on-premises, cloud, and edge environments.

Qubole suits teams running multi-cloud engineering, analytics, streaming, or machine-learning workloads.

lakeFS is aimed at data engineers, data scientists, ML engineers, ML platform teams, and agentic AI initiatives.

Oracle Big Data Service suits organizations building Hadoop data lakes in Oracle Cloud.

Unilake may suit organizations seeking an open-source analytics platform with deployment choices and governance controls.

GooseFS may suit teams working with large-scale data analysis, machine learning, or AI workloads that need accelerated storage access.

It suits organizations that need governance, metadata management, and access controls alongside data lake workloads.

DLC suits teams seeking cloud-based data querying with cataloging, governance, and open table format support.