EmergentDB Analytics
Help the user retrieve analytics and usage data from their EmergentDB account.
TypeScript SDK
import { EmergentDB } from "emergentdb";
const db = new EmergentDB("emdb_your_api_key");
// Request stats by endpoint (last 30 days)
const endpoints = await db.analyticsEndpoints();
// [{ endpoint, requestCount, totalBytes, avgLatencyMs, p95LatencyMs, errorCount }]
// Usage by namespace (last 30 days)
const namespaces = await db.analyticsNamespaces();
// [{ namespace, requestCount, totalVectors, avgLatencyMs }]
// Latency percentiles by day (last 30 days)
const latency = await db.analyticsLatency();
// [{ date, p50, p95, p99, requestCount }]
// Error rates by day (last 30 days)
const errors = await db.analyticsErrors();
// [{ date, totalRequests, errorCount, error4xx, error5xx }]
// Per-API-key usage (last 30 days)
const keys = await db.analyticsKeys();
// [{ apiKeyId, keyName, keyPrefix, requestCount, totalBytes, avgLatencyMs, lastUsed }]
// Vector count growth (daily snapshots, last 90 days)
const growth = await db.analyticsGrowth();
// [{ date, vectorCount }]
Python SDK
from emergentdb import EmergentDB
db = EmergentDB("emdb_your_api_key")
endpoints = db.analytics_endpoints() # request stats per endpoint
namespaces = db.analytics_namespaces() # usage per namespace
latency = db.analytics_latency() # p50/p95/p99 by day
errors = db.analytics_errors() # 4xx/5xx counts by day
keys = db.analytics_keys() # per-API-key stats
growth = db.analytics_growth() # vector count by day (90 days)
Available Analytics
| Method |
Data |
Window |
analyticsEndpoints / analytics_endpoints |
Requests, bytes, latency per endpoint |
30 days |
analyticsNamespaces / analytics_namespaces |
Requests, vectors, latency per namespace |
30 days |
analyticsLatency / analytics_latency |
p50, p95, p99 latency by day |
30 days |
analyticsErrors / analytics_errors |
Error counts (4xx, 5xx) by day |
30 days |
analyticsKeys / analytics_keys |
Usage stats per API key |
30 days |
analyticsGrowth / analytics_growth |
Total vector count by day |
90 days |
Error Codes
| Code |
Meaning |
| 401 |
Missing or invalid API key |
| 429 |
Rate limit exceeded |
| 500 |
Server error — retry with backoff |
Plans & Limits
| Plan |
Vectors |
Price |
| Free |
10,000 |
$0/mo |
| Launch |
500,000 |
$29/mo |
| Scale |
2,500,000 |
$99/mo |
When helping the user, suggest the right analytics method based on what they want to understand (performance, errors, growth, etc.).
1---2name: emdb-analytics3description: View EmergentDB analytics and usage stats. Use when the user wants to check API usage, latency, errors, growth, or per-key stats.4---56# EmergentDB Analytics78Help the user retrieve analytics and usage data from their EmergentDB account.910## TypeScript SDK1112```typescript13import { EmergentDB } from "emergentdb";1415const db = new EmergentDB("emdb_your_api_key");1617// Request stats by endpoint (last 30 days)18const endpoints = await db.analyticsEndpoints();19// [{ endpoint, requestCount, totalBytes, avgLatencyMs, p95LatencyMs, errorCount }]2021// Usage by namespace (last 30 days)22const namespaces = await db.analyticsNamespaces();23// [{ namespace, requestCount, totalVectors, avgLatencyMs }]2425// Latency percentiles by day (last 30 days)26const latency = await db.analyticsLatency();27// [{ date, p50, p95, p99, requestCount }]2829// Error rates by day (last 30 days)30const errors = await db.analyticsErrors();31// [{ date, totalRequests, errorCount, error4xx, error5xx }]3233// Per-API-key usage (last 30 days)34const keys = await db.analyticsKeys();35// [{ apiKeyId, keyName, keyPrefix, requestCount, totalBytes, avgLatencyMs, lastUsed }]3637// Vector count growth (daily snapshots, last 90 days)38const growth = await db.analyticsGrowth();39// [{ date, vectorCount }]40```4142## Python SDK4344```python45from emergentdb import EmergentDB4647db = EmergentDB("emdb_your_api_key")4849endpoints = db.analytics_endpoints() # request stats per endpoint50namespaces = db.analytics_namespaces() # usage per namespace51latency = db.analytics_latency() # p50/p95/p99 by day52errors = db.analytics_errors() # 4xx/5xx counts by day53keys = db.analytics_keys() # per-API-key stats54growth = db.analytics_growth() # vector count by day (90 days)55```5657## Available Analytics5859| Method | Data | Window |60|---|---|---|61| `analyticsEndpoints` / `analytics_endpoints` | Requests, bytes, latency per endpoint | 30 days |62| `analyticsNamespaces` / `analytics_namespaces` | Requests, vectors, latency per namespace | 30 days |63| `analyticsLatency` / `analytics_latency` | p50, p95, p99 latency by day | 30 days |64| `analyticsErrors` / `analytics_errors` | Error counts (4xx, 5xx) by day | 30 days |65| `analyticsKeys` / `analytics_keys` | Usage stats per API key | 30 days |66| `analyticsGrowth` / `analytics_growth` | Total vector count by day | 90 days |6768## Error Codes6970| Code | Meaning |71|------|---------|72| 401 | Missing or invalid API key |73| 429 | Rate limit exceeded |74| 500 | Server error — retry with backoff |7576## Plans & Limits7778| Plan | Vectors | Price |79|------|---------|-------|80| Free | 10,000 | $0/mo |81| Launch | 500,000 | $29/mo |82| Scale | 2,500,000 | $99/mo |8384When helping the user, suggest the right analytics method based on what they want to understand (performance, errors, growth, etc.).
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