{"passport":{"unfragile":{"@version":"1.0","version":"2026-05","artifact":{"id":"tool_sherloqdata","slug":"sherloqdata","name":"SherloqData","type":"product","url":"https://www.sherloqdata.io","page_url":"https://unfragile.ai/sherloqdata","categories":["data-pipelines"],"tags":[],"pricing":{"model":"paid","free":false,"starting_price":null},"status":"active","verified":false},"capabilities":[{"id":"tool_sherloqdata__cap_0","uri":"capability://automation.workflow.collaborative.sql.query.execution.with.real.time.multi.user.editing","name":"collaborative sql query execution with real-time multi-user editing","description":"Enables multiple team members to simultaneously write, edit, and execute SQL queries against connected databases within a shared workspace. The platform implements operational transformation or CRDT-based conflict resolution to merge concurrent edits, maintains a live execution context that reflects the latest query state, and broadcasts query results to all connected clients in real-time. This eliminates the need for manual query sharing via email or chat and ensures all collaborators work against the same query version and result set.","intents":["I want my team to collaborate on complex SQL queries without emailing query files back and forth","I need to see what my teammate is writing in real-time and contribute to the same query","I want query execution results to be immediately visible to all team members without manual refresh"],"best_for":["data teams with 3+ members who frequently pair on SQL analysis","organizations where query development is a collaborative process requiring feedback loops"],"limitations":["Real-time sync latency depends on network conditions; high-latency connections may experience 500ms+ delays in edit propagation","Concurrent edits to the same query section may require manual conflict resolution if CRDT implementation doesn't handle all edge cases","No offline mode — all editing requires active connection to SherloqData servers"],"requires":["Active internet connection with stable latency (<200ms recommended)","Database connection credentials configured in SherloqData workspace","Team members with SherloqData accounts in the same workspace"],"input_types":["SQL text","query parameters (variables)"],"output_types":["query results (tabular data)","execution metadata (duration, rows affected)","edit history with user attribution"],"categories":["automation-workflow","collaboration"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"tool_sherloqdata__cap_1","uri":"capability://automation.workflow.query.version.control.with.branching.and.audit.trails","name":"query version control with branching and audit trails","description":"Maintains a complete version history of all SQL queries with Git-like branching semantics, allowing teams to create isolated query branches, merge changes, and revert to previous versions. Each query version is tagged with author, timestamp, and execution metadata. The system stores diffs at the query text level and tracks which team member executed which version against which database, creating an immutable audit trail for compliance and debugging. This is implemented as a dedicated version control layer separate from the query execution engine.","intents":["I need to track who changed a query and when, for compliance auditing purposes","I want to experiment with a query variant without affecting the main version my team uses","I need to revert a query to a previous version if a recent change broke downstream reports"],"best_for":["regulated industries (finance, healthcare) requiring audit trails for data access","teams with formal change management processes","organizations where query stability is critical to downstream analytics"],"limitations":["Version history is stored in SherloqData's database, not in external Git repos, limiting integration with existing version control workflows","Branching is query-scoped, not workspace-scoped, so managing dependencies between related queries requires manual coordination","Audit trail retention depends on SherloqData's data retention policy; no option for indefinite archival to external systems"],"requires":["SherloqData workspace with version control feature enabled","User permissions to create branches and merge changes"],"input_types":["SQL query text","branch name","merge strategy (manual/auto)"],"output_types":["version history (list of commits with diffs)","audit log (user, timestamp, action, query state)","branched query (isolated copy for experimentation)"],"categories":["automation-workflow","safety-moderation"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"tool_sherloqdata__cap_10","uri":"capability://tool.use.integration.integration.with.external.data.sources.and.apis","name":"integration with external data sources and apis","description":"Allows queries to fetch data from external APIs (REST, GraphQL) and combine it with database query results. The platform provides a connector framework where users can define API endpoints, authentication, and response parsing. Query results can be exported to external systems (data warehouses, BI tools, cloud storage) via pre-built connectors or custom webhooks. Integration is configured through the UI without requiring code.","intents":["I want to enrich database query results with data from an external API","I need to export query results to my data warehouse automatically","I want to trigger downstream tools (BI dashboards, ML pipelines) when a query completes"],"best_for":["organizations with data in multiple systems requiring integration","teams building data pipelines that span databases and external APIs"],"limitations":["API integration is limited to simple request/response patterns; complex streaming or event-based APIs are not supported","No built-in retry logic or error handling for failed API calls — queries fail if external APIs are unavailable","Custom connectors require manual configuration; no marketplace or pre-built connectors for popular APIs"],"requires":["API endpoint URL and authentication credentials","Network connectivity from SherloqData servers to external APIs"],"input_types":["API endpoint configuration (URL, auth, headers)","query results (to be exported)"],"output_types":["enriched query results (with API data)","export confirmation (success/failure)","integration logs"],"categories":["tool-use-integration","data-processing-analysis"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"tool_sherloqdata__cap_11","uri":"capability://automation.workflow.team.workspace.management.and.user.provisioning","name":"team workspace management and user provisioning","description":"Provides workspace-level organization where teams can create isolated environments with separate databases, queries, and user access. Workspaces support multiple users with role-based access control (admin, editor, viewer). User provisioning can be automated via SAML/OAuth or managed manually. Workspace settings control features (caching, scheduling, integrations) and enforce organizational policies. Audit logs track all user actions within a workspace.","intents":["I want to create separate workspaces for different teams or projects","I need to provision users in bulk via SAML/OAuth instead of manually","I want to enforce organizational policies (e.g., no scheduling queries) at the workspace level"],"best_for":["organizations with multiple teams or departments","enterprises requiring SSO and centralized user management"],"limitations":["Workspace isolation is logical, not physical — all workspaces share the same SherloqData infrastructure","Cross-workspace queries are not supported — data cannot be shared between workspaces","SAML/OAuth integration requires IT setup; no self-service SSO configuration"],"requires":["SherloqData account with admin privileges","SAML/OAuth provider (optional, for automated provisioning)"],"input_types":["workspace name and settings","user email and role","SAML/OAuth configuration"],"output_types":["workspace created","user provisioned","audit log (user actions)"],"categories":["automation-workflow","safety-moderation"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"tool_sherloqdata__cap_2","uri":"capability://safety.moderation.role.based.access.control.with.database.level.and.query.level.permissions","name":"role-based access control with database-level and query-level permissions","description":"Enforces fine-grained access policies at multiple levels: database connections (which users can access which databases), query visibility (who can view/edit/execute specific queries), and data row/column access (via integration with database-native row-level security). The system implements a permission matrix where roles are assigned to users, and permissions are inherited hierarchically (workspace > database > query). Access decisions are evaluated at query execution time, preventing unauthorized data access even if a user has network access to the database.","intents":["I need to ensure junior analysts can only query non-sensitive tables while senior analysts have full access","I want to restrict certain queries to specific teams without managing database-level permissions separately","I need to audit which users accessed which data and when, for compliance reporting"],"best_for":["organizations with strict data governance requirements (PII, regulated data)","multi-tenant environments where data isolation is critical","teams with diverse skill levels requiring graduated access"],"limitations":["Row-level security integration depends on database support (PostgreSQL RLS, SQL Server RLS); not all databases support this feature","Permission changes may take 30-60 seconds to propagate across all active sessions due to caching","No dynamic permission evaluation based on query content — permissions are static role assignments, not query-aware policies"],"requires":["SherloqData workspace with access control feature enabled","User authentication system (SAML, OAuth, or SherloqData native auth)","Database with RLS support (optional, for row-level filtering)"],"input_types":["role definition (name, permissions)","user-to-role assignment","database connection credentials"],"output_types":["access decision (allow/deny)","filtered query results (rows/columns removed based on permissions)","access audit log (user, query, timestamp, result)"],"categories":["safety-moderation","automation-workflow"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"tool_sherloqdata__cap_3","uri":"capability://data.processing.analysis.query.execution.with.multi.database.support.and.connection.pooling","name":"query execution with multi-database support and connection pooling","description":"Executes SQL queries against multiple database backends (PostgreSQL, MySQL, Snowflake, BigQuery, etc.) through a unified interface. The platform maintains persistent connection pools to each configured database, reusing connections across query executions to reduce latency. Query execution is asynchronous — the client submits a query and receives a job ID, then polls for results or subscribes to a WebSocket for real-time result streaming. The execution engine handles query timeouts, resource limits, and graceful error reporting.","intents":["I want to run queries against multiple databases without switching tools or managing separate connections","I need fast query execution with connection reuse rather than establishing a new connection for each query","I want to see query results stream in real-time as they're returned from the database"],"best_for":["teams working with multiple database systems (data warehouse + operational databases)","organizations needing a unified query interface across heterogeneous data sources"],"limitations":["Cross-database joins are not supported — each query executes against a single database","Query timeout defaults to 5-10 minutes; long-running analytical queries may be terminated","Connection pooling is per-workspace, not per-user, so high concurrency may exhaust pool capacity"],"requires":["Database connection credentials (host, port, username, password or API key)","Network connectivity from SherloqData servers to database endpoints","Supported database driver (PostgreSQL, MySQL, Snowflake, BigQuery, etc.)"],"input_types":["SQL query text","database connection identifier","query parameters (for parameterized queries)"],"output_types":["query results (tabular data, JSON, CSV)","execution metadata (duration, rows returned, query plan)","error messages with line numbers"],"categories":["data-processing-analysis","automation-workflow"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"tool_sherloqdata__cap_4","uri":"capability://data.processing.analysis.query.result.caching.and.materialization","name":"query result caching and materialization","description":"Automatically caches query results in memory or persistent storage, allowing subsequent identical queries to return results instantly without re-executing against the database. The caching layer uses query text (with parameter normalization) as the cache key and respects user-defined TTLs (time-to-live). Teams can also explicitly materialize query results as temporary tables or snapshots for downstream use. Cache invalidation is manual (user-triggered) or automatic (based on TTL or detected schema changes).","intents":["I want to run the same exploratory query multiple times without hitting the database each time","I need to create a snapshot of query results at a specific point in time for reproducibility","I want to share cached results with teammates without re-executing expensive queries"],"best_for":["teams running repeated analytical queries with acceptable staleness windows","exploratory data analysis workflows where query iteration is common"],"limitations":["Cache invalidation is not automatic for schema changes — stale results may be returned if underlying tables are modified","Materialized snapshots consume storage; retention policies depend on SherloqData's storage quotas","No cache warming or predictive caching — caches are built on-demand"],"requires":["Query result caching feature enabled in workspace","User-defined TTL configuration (default: 1 hour)"],"input_types":["SQL query text","cache TTL (seconds)","materialization target (temporary table, snapshot)"],"output_types":["cached query results (instant return)","cache metadata (hit/miss, age, size)","materialized table reference"],"categories":["data-processing-analysis","automation-workflow"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"tool_sherloqdata__cap_5","uri":"capability://automation.workflow.query.parameterization.and.templating","name":"query parameterization and templating","description":"Allows queries to be written with named parameters (e.g., `WHERE date >= :start_date`) that can be bound at execution time without modifying the query text. The platform provides a parameter UI where users input values, and the execution engine substitutes parameters into the query before sending to the database. Templates can be saved with default parameter values, enabling non-technical users to execute complex queries by simply filling in a form. Parameter types (date, number, string) are validated client-side and server-side.","intents":["I want to create a reusable query template that different team members can run with different date ranges","I need to prevent SQL injection by parameterizing user inputs","I want non-technical stakeholders to run queries without understanding SQL syntax"],"best_for":["teams with recurring analytical queries that vary only in filter values","organizations enabling self-service analytics for non-technical users"],"limitations":["Parameters cannot be used in structural parts of queries (table names, column names) — only in WHERE clauses and VALUES","No support for array or JSON parameters — only scalar types (string, number, date, boolean)","Parameter validation is basic; complex business logic validation must be implemented in the query itself"],"requires":["Query written with named parameter syntax (`:param_name`)","Parameter type definitions (string, number, date, boolean)"],"input_types":["SQL query with parameter placeholders","parameter values (string, number, date, boolean)"],"output_types":["parameterized query (with values substituted)","query results","parameter validation errors"],"categories":["automation-workflow","code-generation-editing"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"tool_sherloqdata__cap_6","uri":"capability://automation.workflow.query.documentation.and.annotation","name":"query documentation and annotation","description":"Allows users to attach rich documentation to queries, including descriptions, expected output schemas, usage examples, and inline code comments. Documentation is versioned alongside query code and searchable. The platform supports Markdown formatting for documentation and can auto-generate schema documentation from query result metadata. Annotations can be added to specific query sections (e.g., 'this JOIN is expensive, consider materialization'). Documentation is displayed in the IDE alongside the query and is accessible to all team members.","intents":["I want to document why a complex query is written a certain way so future maintainers understand the logic","I need to communicate expected output schema and data quality assumptions to downstream consumers","I want to flag performance issues or data quality concerns directly in the query"],"best_for":["teams with complex analytical queries requiring institutional knowledge","organizations prioritizing knowledge transfer and onboarding"],"limitations":["Documentation is stored in SherloqData, not in external knowledge bases, limiting integration with wiki or documentation systems","No automatic documentation generation from query execution plans or data lineage","Documentation search is basic keyword matching, not semantic search"],"requires":["Query created in SherloqData workspace"],"input_types":["Markdown documentation text","inline code comments","schema annotations"],"output_types":["rendered documentation (HTML)","searchable documentation index","versioned documentation history"],"categories":["automation-workflow","memory-knowledge"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"tool_sherloqdata__cap_7","uri":"capability://automation.workflow.query.scheduling.and.automated.execution","name":"query scheduling and automated execution","description":"Enables users to schedule queries to run on a recurring basis (hourly, daily, weekly, monthly) or on-demand via webhooks. Scheduled queries execute asynchronously and results are stored in a results table or exported to external systems (email, Slack, S3, data warehouse). The scheduling engine supports cron expressions for complex schedules and includes retry logic for failed executions. Execution history is tracked with logs and error messages. Scheduled queries inherit the permissions of the user who created them, ensuring data access controls are maintained.","intents":["I want to run a daily report query automatically and email results to stakeholders","I need to refresh a materialized view every hour by executing a query","I want to trigger a query execution when an external event occurs (via webhook)"],"best_for":["teams with recurring reporting requirements","organizations automating data pipeline tasks"],"limitations":["Scheduled query execution uses the creator's permissions; if the creator's access is revoked, scheduled queries may fail silently","No built-in data quality checks — failed queries are logged but not automatically escalated","Webhook-triggered execution has no request validation; any caller can trigger a query if they know the webhook URL"],"requires":["Query created and tested in SherloqData","Schedule definition (cron expression or fixed interval)","Destination for results (email, Slack, S3, database table)"],"input_types":["query identifier","schedule (cron expression or interval)","result destination","notification settings"],"output_types":["execution history (timestamp, status, duration)","query results (sent to destination)","execution logs and error messages"],"categories":["automation-workflow","tool-use-integration"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"tool_sherloqdata__cap_8","uri":"capability://data.processing.analysis.data.lineage.and.impact.analysis","name":"data lineage and impact analysis","description":"Tracks data lineage by analyzing query dependencies — which tables/columns are read by each query and which downstream queries depend on those results. The system builds a directed acyclic graph (DAG) of query dependencies and can visualize the lineage. Impact analysis allows users to see which queries will be affected if a table schema changes or if a source query is modified. Lineage is automatically extracted from query text parsing (table/column references) and can be manually annotated for complex cases.","intents":["I want to understand which queries depend on a table before I modify its schema","I need to trace data from source tables through intermediate queries to final reports","I want to see the impact of changing a query on downstream analytics"],"best_for":["organizations with complex query dependencies and data pipelines","teams managing data quality and schema governance"],"limitations":["Lineage extraction relies on query text parsing; dynamic queries (generated at runtime) are not tracked","Cross-database lineage is not supported — lineage is tracked within a single database","Manual lineage annotation is required for complex cases (e.g., queries that read from external APIs)"],"requires":["Queries created in SherloqData workspace","Query text must be parseable (no dynamic SQL generation)"],"input_types":["SQL query text"],"output_types":["lineage graph (DAG visualization)","impact analysis (list of affected queries)","dependency list (upstream/downstream queries)"],"categories":["data-processing-analysis","planning-reasoning"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"tool_sherloqdata__cap_9","uri":"capability://data.processing.analysis.query.performance.profiling.and.optimization.suggestions","name":"query performance profiling and optimization suggestions","description":"Analyzes query execution plans to identify performance bottlenecks (full table scans, missing indexes, inefficient joins). The system fetches the query plan from the database, parses it, and generates optimization suggestions (e.g., 'add index on column X', 'rewrite JOIN to use hash join'). Suggestions are ranked by estimated performance impact. The platform also tracks query execution time over time and alerts users if a query's performance degrades. Performance metrics are stored and can be compared across query versions.","intents":["I want to understand why a query is slow and get suggestions to optimize it","I need to detect performance regressions when a query is modified","I want to identify missing indexes that would improve query performance"],"best_for":["teams with large datasets where query performance is critical","organizations optimizing data warehouse costs"],"limitations":["Optimization suggestions are generic and may not apply to specific data distributions or workloads","Performance profiling requires database support for EXPLAIN plans; some databases (BigQuery) have limited plan visibility","Suggestions are not automatically applied — users must manually implement optimizations"],"requires":["Database support for EXPLAIN or query plan analysis","Query execution history (for trend analysis)"],"input_types":["SQL query text"],"output_types":["query execution plan (parsed)","optimization suggestions (ranked by impact)","performance metrics (duration, rows scanned)","performance trend analysis"],"categories":["data-processing-analysis","planning-reasoning"],"confidence":0.5,"matches":0,"success_rate":0}],"trust":{"score":40,"verified":false,"data_access_risk":"high","permissions":["Active internet connection with stable latency (<200ms recommended)","Database connection credentials configured in SherloqData workspace","Team members with SherloqData accounts in the same workspace","SherloqData workspace with version control feature enabled","User permissions to create branches and merge changes","API endpoint URL and authentication credentials","Network connectivity from SherloqData servers to external APIs","SherloqData account with admin privileges","SAML/OAuth provider (optional, for automated provisioning)","SherloqData workspace with access control feature enabled"],"failure_modes":["Real-time sync latency depends on network conditions; high-latency connections may experience 500ms+ delays in edit propagation","Concurrent edits to the same query section may require manual conflict resolution if CRDT implementation doesn't handle all edge cases","No offline mode — all editing requires active connection to SherloqData servers","Version history is stored in SherloqData's database, not in external Git repos, limiting integration with existing version control workflows","Branching is query-scoped, not workspace-scoped, so managing dependencies between related queries requires manual coordination","Audit trail retention depends on SherloqData's data retention policy; no option for indefinite archival to external systems","API integration is limited to simple request/response patterns; complex streaming or event-based APIs are not supported","No built-in retry logic or error handling for failed API calls — queries fail if external APIs are unavailable","Custom connectors require manual configuration; no marketplace or pre-built connectors for popular APIs","Workspace isolation is logical, not physical — all workspaces share the same SherloqData infrastructure","builder identity is not verified yet","no observed match outcomes yet"],"rank_breakdown":{"adoption":0.31666666666666665,"quality":0.72,"ecosystem":0.15000000000000002,"match_graph":0.25,"freshness":0.75,"weights":{"adoption":0.25,"quality":0.25,"ecosystem":0.1,"match_graph":0.35,"freshness":0.05}},"observed_outcomes":{"matches":0,"success_rate":0,"avg_confidence":0,"top_intents":[],"last_matched_at":null},"maintenance":{"status":"active","updated_at":"2026-05-24T12:16:33.096Z","last_scraped_at":"2026-04-05T13:23:42.559Z","last_commit":null},"community":{"stars":null,"forks":null,"weekly_downloads":null,"model_downloads":null,"model_likes":null}},"distribution":{"claim_url":"https://unfragile.ai/submit?claim=sherloqdata","compare_url":"https://unfragile.ai/compare?artifact=sherloqdata"}},"signature":"KNiDd6aNTVZeemTGhtDB+PHSyYek15ejEVlHTOUB6Z8nenIhRSAqz7uB8Lf9G/CdcG2nRzfpPMe1cua43M4lBg==","signedAt":"2026-06-20T17:09:16.275Z","signedBy":"unfragile.ai","version":1},"_links":{"self":"https://unfragile.ai/api/v1/passport/sherloqdata","artifact":"https://unfragile.ai/sherloqdata","verify":"https://unfragile.ai/api/v1/verify?slug=sherloqdata","publicKey":"https://unfragile.ai/api/v1/trust-passport-public-key","spec":"https://unfragile.ai/trust","schema":"https://unfragile.ai/schema.json","docs":"https://unfragile.ai/docs"}}