Fast and reliable SAP HANA performance diagnosis

Helps database and application teams prevent costly slowdowns by providing deep performance intelligence for SAP HANA workloads. When slow queries, blocking, and unclear bottlenecks affect reporting, billing, analytics, and customer-facing applications, DPA shows query executions, wait events, execution plans, and blocking conditions in context, helping you quickly identify root causes, prioritize the high impact issues, and optimize performance.

Benefits

  • Pinpoint SAP HANA bottlenecks faster

    Continuously polling SAP HANA surfaces wait events, costly queries, real-time sessions, blocking chains, and resource trends in one familiar workflow, so teams can resolve issues before they impact business. As SAP HANA runs in-memory, it tracks memory alongside CPU, disk, connections, and SQL activity, and reveals plan cache data and execution plan changes to show why performance shifted, reducing downtime and keeping critical processes running.

  • Diagnose slowdowns in minutes

    Teams can resolve slowdowns faster since wait-time analytics reveal what is actually delaying performance, not just how hard CPU, memory, and disk are working. By showing how an issue stems from SQL, locking, input/output (I/O), storage pressure, or CPU contention, and enabling the user to drill from high-level indicators into specific waits, and workloads behind it, teams can diagnose and get to the true cause quickly.

  • Tune queries for peak performance

    Optimize the queries that matter most and improve performance because execution-plan details are surfaced and plan changes are tracked over time, making it easy to investigate when a query turns expensive after the SAP HANA optimizer picks a different plan. By highlighting top SQL statements by cumulative wait time, database teams can quickly isolate high-impact tuning candidates and focus efforts where they deliver the greatest return.

  • Monitor every database in one place

    Users can troubleshoot faster and manage more efficiently since a single, consistent approach monitors mixed estates spanning SAP HANA, Oracle, Microsoft SQL Server, MySQL, PostgreSQL, IBM Db2, MariaDB, Azure SQL Database, Amazon RDS, and more, removing the need to switch between tools. Standardized visibility across platforms is essential to support modern application stacks, reducing complexity, and keeping critical services running reliably.

  • Gain visibility without agents or additional overhead

    Teams gain full performance visibility without adding load or risk to production systems because an agentless design connects to SAP HANA through Java Database Connectivity (JDBC) using a read-only monitoring user. With no software to install on database hosts and no distributed agents to manage, teams reduce overhead, simplify deployment and maintenance, and protect the stability and performance of critical SAP HANA environments.

Features

Analyze performance by wait time

Ranks issues by the application and end-user wait times they cause in SAP HANA, rather than generic health metrics, so teams can focus on the queries and sessions that will deliver the greatest performance improvement when resolved.

Analyze performance by wait time
Enlarge

Detect anomalies with machine learning

The application learns normal SAP HANA wait-time patterns from historical data and flags anomalies when waits run significantly higher than expected, using standard deviation to predict future wait times and set warning and critical thresholds automatically.

Detect anomalies with machine learning
Enlarge

Monitor across database platforms without agents

Monitors SAP HANA (cloud and on-premise) and SAP Adaptive Server Enterprise (ASE) alongside SQL Server, Oracle, MySQL, PostgreSQL, MariaDB, and IBM Db2, whether workloads are running on premises or in Amazon Web Services, Microsoft Azure, or Google Cloud, using a lightweight agentless design.

Monitor across database platforms without agents
Enlarge
Show moreView media gallery

Plans and pricing

All plans include:

Wait-time based analysis that ranks issues by the application and end-user wait times they cause in SAP HANA, so teams fix what delivers the greatest performance gain.Machine learning anomaly detection that learns normal SAP HANA wait-time patterns and flags anomalies when waits run significantly higher than expected.Agentless cross-platform monitoring for SAP HANA (cloud and on-premise) and SAP Adaptive Server Enterprise, SQL Server, Oracle, MySQL, PostgreSQL, MariaDB, and IBM Db2, on premises or in the cloud.Query and table tuning advisors that surface inefficient SAP HANA queries and tables daily, with table structure, existing indexes, and actionable recommendations.AI query assist that sends a query's text and execution plan through SolarWinds artificial intelligence, with sensitive data masking, to return side-by-side rewrite suggestions.