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hypequery roadmap

A command to re-generate types, identify schema drift, smoke test the queries with performance testing and differences. Something like the below: <code>$ npx hypequery test</code><code>🔍 Schema Check </code><code>✓ All types match database schema </code><code>⚠️ New column 'users.deleted_at' detected</code><code>🧪 Smoke Test (running queries) </code><code>✓ activeUsers (45ms, 12 rows) </code><code>✓ revenueByMonth (120ms, 24 rows) </code><code>✓ topCustomers (2100ms, 50 rows)</code><code>📊 Performance Check </code><code>✓ All queries within thresholds </code><code>⚠️ topCustomers is slow (2100ms &gt; 1000ms threshold)</code>

In Review

hypequery test package for query testing

Luke

ContextCurrently only the underlying query builder supports streaming, we need first class support through <code>defineServe.</code>GoalSupport for streaming large result sets. Integration with serve package for HTTP streaming responses.

Streaming query support in serve package

ContextEnable easier adoption of hypequery from existing toolingGoalBuild automated migration tools from Cube.js (data model converter), Metabase (question importer), and custom SQL (translator to query builder). Include side-by-side comparison guides. Lower barrier to adoption.

Migration Tools from Alternatives

ContextPublish performance benchmarks for comparisonGoal Benchmark hypequery performance to raw ClickHouse queries, Cube.js, and custom APIs. Include cache effectiveness analysis, query latency comparisons, and type safety overhead measurements.

Performance Benchmarks

ContextUsers can only currently define standalone queries which limits the following use cases :<ul><li>AI Agents: Can't accurately generate queries based on natural language questions, without a pre-defined query</li><li>Dashboard Builders: Users can't drag-and-drop dimensions/measures</li><li>BI Tool Integration: Can't accept dynamic SQL/GraphQL queries</li><li>Multi-Tenant Custom Views: Each tenant can't define their own metrics</li></ul>GoalCreate dynamic API for runtime queries, with a separate entry point to queries.I imagine the API looking something like the below: <pre><code>// generated-datasets.ts (auto-generated)
export const datasets = {
 trips: defineDataset({
 table: 'trips',
 dimensions: {
 pickup_datetime: dimension.datetime('pickup_datetime'),
 pickup_date: dimension.date('toDate(pickup_datetime)'),
 payment_type: dimension.string('payment_type'),
 // ... all columns from schema
 },
 measures: {
 count: measure.count(),
 total_revenue: measure.sum('total_amount'),
 avg_distance: measure.avg('trip_distance'),
 // ... common aggregations
 },
 }),
} as const;

// ===== DYNAMIC QUERIES =====
const dynamicResults = await db.queryDataset(datasets.trips, {
 dimensions: ['pickup_date', 'payment_type'] as const,
 measures: ['count', 'total_revenue'] as const,
});
// Type: Array&lt;{ pickup_date: Date; payment_type: string; count: number; total_revenue: number }&gt;

// ===== FULLY DYNAMIC (No Type Inference) =====
const aiResults = await db.queryDataset(datasets.trips, parseUserInput(query));
// Type: DynamicQueryResult (Record&lt;string, any&gt; with metadata)

// ===== AI AGENT TOOL GENERATION =====
const tools = db.generateTools(datasets.trips, {
 mode: 'per-query', // One tool per predefined query
 // OR
 mode: 'catalog', // Single tool with dimension/measure selection
});

export const api = defineServe({
 queries: {
 // Auto-generated from dataset
 ...datasets.trips.toQueries(),
 }
});</code></pre>

Add dynamic dataset api

ContextImprove developer experienceGoalCurrently the hypequery dev server just provides documentation for the generated endpoints, it would be great to have further features for tracing, observability and debugging.<ul><li>Query list for inspection (raw sql &amp; query builder syntax) and running via a UI to test the output with parameterised inputs</li><li>Logs showing run query history, completion status, cache status</li></ul>

Expand hypequery dev server feature set

ContextEnable first class caching support in defineServe for better control and loggingGoalCurrently, caching is managed just at the underlying query builder level, which does not enable observability at the query definition layer.By managing this instead where users defined queries we can improve the management of cache controls, observability and reporting

Caching support in serve package

ContextFor successful adoption and deployment GoalComprehensive deployment guides for Kubernetes (Helm chart), Docker Compose, AWS ECS/Fargate, Vercel Edge, and Cloudflare Workers. Include reference architectures and best practices. Currently NO deployment guides exist.

Planned

Production Deployment Guides

ContextHelp users get started faster with hypequeryGoalCreate a github repo of hypequery runnable examples to get users up to speed faster. This should include the major use cases:<ul><li>Frontend integration (next, vite)</li><li>Background jobs and scheduled reports</li><li>AI agent integration (langchain, ai sdk)</li><li>Data export APIs</li><li>Analytics microservices</li></ul>

Community Examples Library

ContextEnable users to start using hypequery faster, with no frictionGoalExpand the documentation quickstart and recipes sections with the following:<ul><li>Authentication</li><li>Cron</li><li>Background jobs</li><li>Multi-tenancy</li></ul>

Expand documentation of quickstart and recipes

ContextRe-enable automated deploymentGoalRe-enable automated releases with Changesets (currently disabled). Set up automated NPM publishing on merge to main, changelog generation, release notes, and pre-release channels (beta, rc).