Snowflake is a cloud-native data warehousing platform designed for scalability, flexibility, and high performance. Datachecks monitors within your Snowflake instance, alerting you to potential bugs so your analytics remain reliable and trustworthy.
Databricks is a unified analytics platform that combines data warehousing and machine learning capabilities. With Datachecks, you can detect anomalies in data processing jobs within your Databricks instance, so data quality is maintained across your lakehouse architecture.
BigQuery is a fully-managed, serverless data warehouse solution by Google Cloud, designed for large-scale, fast analytics and SQL. With Datachecks, you can track query performance, data freshness, and schema changes within your BigQuery instance to maintain data integrity and reliability.
Elasticsearch is a distributed search and analytics engine designed for real-time data processing. With Datachecks, you can detect issues in your Elasticsearch clusters, track index health, monitor document counts, and receive alerts on search performance degradation.
OpenSearch is an open-source search and analytics platform known for its scalability and security features. Datachecks detects issues in your OpenSearch deployment, tracking cluster health, index performance, and search reliability across distributed environments
MySQL is an open-source relational database management system (RDBMS) known for its reliability, flexibility, and ease of use. With Datachecks you can track table growth, query performance, replication lag, and data consistency to maintain operational reliability.
Trino is a distributed SQL query engine designed to execute fast analytic queries over large datasets. Datachecks monitors query execution, resource allocation, and cross-connector performance, enhancing query efficiency and improving data federation.
Postgres is an open-source object-relational database management system. Datachecks helps maintain performance by monitoring vacuum operations, connection pools, replication status, and query performance, all while safeguarding data consistency and backup integrity
