Migration Guide

44s Cache speaks native Redis protocol. Use your existing redis-py, ioredis, Jedis, or any Redis client.

1Update Connection String

REDIS_URL=redis://localhost:6379
# or
REDIS_URL=redis://my-redis.aws.com:6379

REDIS_URL=redis://api.44s.io:6379
# With auth:
REDIS_URL=redis://:YOUR_API_KEY@api.44s.io:6379

2That's It

No code changes. Your existing Redis commands work identically:

import redis

# Same code, just different host
r = redis.Redis(host='api.44s.io', port=6379, password='YOUR_API_KEY')

r.set('user:123', 'data')      # ✓ Works
r.get('user:123')               # ✓ Works
r.hset('hash', 'field', 'val')  # ✓ Works
r.lpush('list', 'item')         # ✓ Works
r.sadd('set', 'member')         # ✓ Works

Supported Commands

• ✓All string operations (GET, SET, MGET, MSET, INCR, etc.)
• ✓Hash operations (HGET, HSET, HMGET, HGETALL, etc.)
• ✓List operations (LPUSH, RPUSH, LPOP, LRANGE, etc.)
• ✓Set operations (SADD, SMEMBERS, SINTER, etc.)
• ✓Sorted sets (ZADD, ZRANGE, ZRANK, etc.)
• ✓Key expiration (EXPIRE, TTL, PEXPIRE)

44s Database speaks PostgreSQL wire protocol. Use psycopg2, SQLAlchemy, Prisma, or any Postgres client.

1Update Connection String

DATABASE_URL=postgres://user:pass@localhost:5432/mydb
# or
DATABASE_URL=postgres://user:pass@rds.aws.com:5432/db

DATABASE_URL=postgres://api:YOUR_API_KEY@api.44s.io:5432/default

2Migrate Schema

# Export from existing Postgres
pg_dump -h old-host -U user -s mydb > schema.sql

# Import to 44s (via HTTP API)
curl -X POST https://api.44s.io:8600/query \
  -H "Authorization: Bearer YOUR_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{"sql": "CREATE TABLE users (id SERIAL PRIMARY KEY, name TEXT)"}'

3Migrate Data

# Export data
pg_dump -h old-host -U user --data-only mydb > data.sql

# Import via your ORM or direct SQL
python migrate_data.py  # Your existing migration scripts work

44s Object Store is S3-compatible. Use boto3, AWS CLI, or any S3 client.

1Update SDK Configuration

import boto3

s3 = boto3.client('s3')
s3.upload_file('file.txt', 'my-bucket', 'file.txt')

import boto3

s3 = boto3.client('s3',
    endpoint_url='https://api.44s.io:9000',
    aws_access_key_id='YOUR_API_KEY',
    aws_secret_access_key='YOUR_API_KEY'
)
s3.upload_file('file.txt', 'my-bucket', 'file.txt')

2Sync Existing Data

# Using AWS CLI with custom endpoint
aws s3 sync s3://old-bucket s3://new-bucket \
  --endpoint-url https://api.44s.io:9000

# Or using rclone
rclone sync aws:old-bucket 44s:new-bucket

Supported Operations

• ✓PutObject, GetObject, DeleteObject
• ✓ListObjects, ListObjectsV2
• ✓CreateBucket, DeleteBucket, ListBuckets
• ✓Multipart uploads
• ✓Pre-signed URLs

44s Streaming uses a simple HTTP API. Migrate producers and consumers individually.

1Update Producer

from kafka import KafkaProducer

producer = KafkaProducer(
    bootstrap_servers=['kafka:9092']
)
producer.send('events', b'message')

import requests

requests.post(
    'https://api.44s.io:5470/topics/events/produce',
    headers={'Authorization': 'Bearer KEY'},
    json={'messages': [{'value': 'message'}]}
)

2Update Consumer

from kafka import KafkaConsumer

consumer = KafkaConsumer('events')
for msg in consumer:
    process(msg.value)

import requests

while True:
    resp = requests.get(
        'https://api.44s.io:5470/topics/events/consume',
        headers={'Authorization': 'Bearer KEY'},
        params={'group': 'my-group'}
    )
    for msg in resp.json()['messages']:
        process(msg['value'])

44s Vector provides a simple HTTP API for vector similarity search.

1Create Collection

curl -X POST https://api.44s.io:9002/collections \
  -H "Authorization: Bearer YOUR_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{"name": "embeddings", "dimension": 1536}'

2Export & Import Vectors

import pinecone

index = pinecone.Index('my-index')
# Export vectors (pagination required)
results = index.query(
    vector=[0]*1536,
    top_k=10000,
    include_values=True
)

import requests

# Upsert to 44s
requests.post(
    'https://api.44s.io:9002/collections/embeddings/upsert',
    headers={'Authorization': 'Bearer KEY'},
    json={'vectors': [
        {'id': 'vec1', 'values': [...], 'metadata': {...}}
    ]}
)

3Update Query Code

# 44s Vector query
response = requests.post(
    'https://api.44s.io:9002/collections/embeddings/query',
    headers={'Authorization': 'Bearer YOUR_API_KEY'},
    json={
        'vector': embedding,  # Your query vector
        'top_k': 10,
        'include_metadata': True
    }
)
results = response.json()['results']