KeeperDB vs DBeaver: Secure database access comparison

KeeperDB handles credentials differently depending on how it runs. In the standalone desktop app, the user authenticates with Face ID or Windows Hello, and connections pull credentials directly from Keeper Secrets Manager, so passwords aren't typed or copied into the client. When KeeperDB runs through the vault or the KeeperDB Proxy, connections are fully passwordless: the user launches a session from a vault record, the credential is handled within Keeper's zero-knowledge, zero-trust environment, and the session runs inside Keeper Remote Browser Isolation, so nothing touches the local machine.

The vault and Proxy paths remove the most common database attack vector: credentials sitting in local configuration files, environment variables or shared connection strings.

When KeeperDB runs in the vault, it records every database session in full, with central management in the vault. Every query, every action, every session is captured as immutable audit evidence. These recordings can be used for monitoring, investigation and compliance in regulated sectors. KeeperAI also includes encrypted activity summaries, making auditing much easier.

Because recording is built into the vault access path, it is automatically applied to every session once KeeperDB is deployed through KeeperPAM, with no per-session setting for an administrator to toggle. The standalone desktop app is a working client and does not record sessions on its own; teams that need full recording route KeeperDB through the vault or connect an existing client through the KeeperDB Proxy.

When deployed through the vault, KeeperDB access is governed by the same centralized policy engine as the rest of KeeperPAM. Database access is scoped to user and role identity, granted JIT and tied to the organization's broader privileged access controls. The same vault that manages passwords, secrets and privileged sessions also governs who can reach which database.

This means database access isn't a separate silo with its own permissions model. It inherits the identity governance, Role-Based Access Controls (RBAC) and approval workflows already in place across the platform.

The standalone desktop app runs natively on Mac, Windows and Linux for teams that want desktop performance and a tool that beats legacy clients on its own. It authenticates with Face ID or Windows Hello, integrates directly with Keeper Secrets Manager for vault-credential retrieval, ships a modern UI and includes a built-in AI agent that can run on the customer's preferred LLM. It can connect directly with credentials in an OS-native secure store, through Keeper Tunnels or through the KeeperDB Proxy, which fetches credentials Gateway-side so the user never sees or types them.

The embedded mode launches from the Keeper Vault in a browser through Remote Browser Isolation. No VPN or local setup is required, and the database connection never reaches the user's machine directly. This configuration is for regulated, zero-trust environments and adds session recording, governance and JIT access while using the same client.

KeeperAI is built into KeeperDB with full schema context. It answers natural language questions, writes and runs queries autonomously, generates charts from live result sets, explores existing SQL and triages performance issues from the monitor. Read-only queries run automatically; any write commands surface a confirmation modal, so the user is always the approver. Server-side guardrails keep it scoped to database work and block off-topic code generation, even under prompt injection.

Administrators can pin KeeperAI to their own Azure OpenAI, AWS Bedrock or Vertex AI endpoint, so prompts and schema never leave their network. When KeeperDB runs in the vault, every AI-executed statement is recorded in the session the same way a human-typed query is.

KeeperDB covers PostgreSQL, MySQL/MariaDB, SQL Server, Oracle, Redshift and SQLite with native drivers, without requiring an ODBC or JDBC Bridge. The interface includes a query editor with multi-statement execution, an editable data grid with CSV/JSON/SQL export, ER diagrams and a notebook scratchpad.

Its performance monitor is built in: active process list, blocking chains, lock analysis and one-click session termination across all supported engines except SQLite.