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EverSQL
✓ verifiedPaid
AI SQL optimizer for PostgreSQL and MySQL; well-regarded niche developer tool.
👁 6.5K/mo
Pricing
Free Plan: $0 one-time
Hobby: $16/month
Standard: $83/month
Growth: $333/month
Auto Recharge Credits: $11/mo for 1000 credits
Credit Pack: $9/mo for 1000 credits
Enterprise Plan: Contact for Pricing
No public pricing
No public pricing
No public pricing
Free: $0 /month
Starter: $129 /month
Plus: $490 /month
Enterprise: $2898 /month
Core features
- ✦Web scraping
- ✦Web crawling
- ✦Data extraction in Markdown, JSON, and screenshot formats
- ✦Dynamic content handling
- ✦Rotating proxies
- ✦Rate limits management
- ✦Open-source availability
- ✦Media Parsing
- ✦Zero-ETL data integration
- ✦Federated Query
- ✦Streaming Ingestion
- ✦Instant Replication with CDC
- ✦API to SQL conversion
- ✦NoSQL to SQL conversion
- ✦SQL to API conversion
- ✦Self-service Integration
- ✦Generate SQL with AI
- —
- ✦Fast tensor operations
- ✦Differentiable tensors for gradient-based optimization
- ✦Network connectivity
- ✦Integration with Bun and Flashlight
- ✦Support for GPU computation with CUDA (Linux) and CPU computation (macOS)
- ✦Automatic SQL Query Optimization
- ✦Ongoing AI-based Performance Insights
- ✦Cost Reduction Recommendations
Use cases
- →Powering AI assistants with real-time web content
- →Enhancing sales data with web information
- →Adding scraping capabilities to code editors
- →Enabling customers to build AI apps with web data
- →Extracting comprehensive information for in-depth research
- →Query data directly from its source in real-time.
- →Process data wherever it is, blending data from different sources.
- →Ingest streaming data from Kafka, Segment, etc., into Peaka BI Table.
- →Replace nightly batch ingestion with real-time data access.
- →Treat every data source like a relational database by converting APIs to tables.
- →Use SQL to query NoSQL databases.
- →Query consolidated data and expose it with APIs.
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- →Creating and manipulating datasets
- →Training small machine learning models
- →Implementing advanced training and inference logic
- →Building applications that require tensor computations
- →Optimizing slow SQL queries to improve application performance.
- →Monitoring database performance to identify potential bottlenecks.
- →Reducing database costs by identifying redundant indexes and schema optimizations.
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