mnemiq vs SQLAI.ai

mnemiq is an open-source text-to-SQL engine for enterprise data agents, configured and measured against a user's own database. Before execution, a deterministic check verifies that proposed SQL is read-only, uses permitted objects, compiles in the source dialect, and passes EXPLAIN. Access permissions apply before schema retrieval, so the model is not shown tables the caller cannot access. Each answer includes the SQL run, the tables it touched, and the enrichment version used. mnemiq can profile columns and build descriptions, grain, glossary terms, and coded-value meanings; a human owner can certify semantic definitions. Listed databases are PostgreSQL, SQLite, DuckDB, Oracle, Snowflake, and Databricks, with DuckDB as the universal executor. Models can use any OpenAI-compatible /v1 endpoint, including local servers such as vLLM, Ollama, llama.cpp server, and LM Studio. Its MCP server offers two read-only, access-scoped tools: db_read(question) and get_schema(). One process can also serve a workbench and HTTP endpoints for asking, chatting, and retrieving schema. The Apache-2.0 engine is free and runs in the user's environment. Local model hosting keeps schemas, questions, and rows inside the user's network, according to the maker.

SQLAI.ai is a web and API toolbox for generating and working with SQL and NoSQL queries. Its text-to-SQL generator turns plain-language requests in many languages into queries; other tools optimize, validate, format, explain, and convert them. The SQL optimizer offers index-aware rewrites and explains performance changes. Database rules, schema autosuggest, a VS Code-style editor, side-by-side diff view, and large-schema support provide additional query tools. Its directory lists 28 database engines, including MySQL, PostgreSQL, SQL Server, Oracle PL/SQL, and MongoDB; some support live connections and others schema-only workflows. Users can run natural-language queries against connected databases, and the site recommends read-only connections for improved security. The company says it stores schemas rather than actual database data and encrypts credentials routed through a proxy. The public API uses an access token in a request header; API requests cost 3 credits per query or 5 for very large schemas. Hobby costs $4 a month and includes 50 queries per month; a 7-day trial is listed, but no free plan.