SQLer

SQLer is an application-facing service that translates natural-language questions into SQL for relational databases. It suits developers building a governed text-to-query layer who can maintain schema and business context. Its strongest case is context-rich generation with tenant isolation; monthly query quotas and split-database handling are the important constraints.

Overview

SQLer comes from DaaX, a Silicon Valley AI startup, and supports MS SQL, MySQL, PostgreSQL and SQLite across four SQL dialects. DaaX reports 96% equivalence to expert-written SQL on a customer benchmark of 300 production queries. That is a useful quality signal, but teams should still validate generated statements against their own data models and business rules.

Developers can add company vocabulary, business rules, schema descriptions and question-to-SQL examples. This makes the service more suitable for domain-specific terminology than a generic prompt box. SQLer generates SQL for the customer application to execute, while results remain in the customer environment. Single-tenant security is listed for deployments where isolation matters.

Key features

Schema and context management

Schema information can be established through a direct connection, the GATHERer Kubernetes container or manual SQL DDL upload. GATHERer runs in the customer’s application environment and can transfer gathered setup information to SQLer with developer permission, reducing the need to move setup-collection activity outside that environment. Developers can refresh the setup through GATHERer, Direct Connection or Manual Upload as schemas and metadata change. That maintenance path is valuable for production applications, where stale definitions can undermine otherwise accurate generation.

Application workflow and security

SQLer returns SQL rather than executing queries itself; the surrounding application controls execution, and query results stay in the customer environment. This separation fits teams that already have their own authorization, logging and execution layers. Single-tenant security adds an isolation option, although the product still requires separate queries when a schema is split across separate databases. It is therefore a poor fit for workflows that need one generated statement to join data across database boundaries.

Developer resources

Documentation, a REST API reference, a developer dashboard sandbox and a community forum support implementation. The API and sandbox are particularly relevant when SQLer is being embedded into an existing product rather than used as a standalone analyst tool.

Pricing

SQLer uses monthly query allowances rather than seat-based prices. The Free plan costs nothing (billed $0/month) and includes 50 NL2SQL queries per month. It is suitable for proof-of-concept work or a small, low-volume integration, but the cap can be reached quickly in an active application.

Lift-Off costs $199 a month (billed $199/month) for 2,500 total NL2SQL queries per month. Growth is $399 a month (billed $399/month) for 6,000 queries, while Turbo is $899 a month (billed $899/month) for 15,000. Those tiers provide progressively more headroom for production traffic; the cheaper tiers give up capacity rather than a stated feature set. Custom has custom query allowance and custom pricing (billed Contact Us), making it the route for requirements beyond the published quotas.

Platforms

SQLer is offered through an API and web interface. The API orientation favors teams integrating generation into their own applications, while the web option provides a direct workspace for setup and evaluation.

Who it's for

Choose SQLer when developers can supply reliable schema information and business rules, need natural-language input inside an application, and value customer-environment execution with single-tenant isolation. It is less suitable for casual, high-volume querying on the free tier or for systems whose data model spans separate databases and requires cross-database queries.

Pros and cons

• Pros: Four listed SQL dialects cover common relational systems; business vocabulary, rules and examples let teams tailor generation; three schema-ingestion and refresh methods support different deployment practices; SQL execution and results remain in the customer environment; single-tenant security addresses isolation needs.
• Cons: The Free plan allows only 50 queries per month; paid plans start at $199 per month; quotas are fixed by tier; split schemas require separate queries for each database; the benchmark result is a vendor-reported signal rather than a guarantee for every workload.

Alternatives

For a free, open-source local installation, choose Natural Language SQL, which runs on API, Linux, macOS, self-hosted and web platforms. Outerbase AI is a better match if you want a freemium workspace with a free tier for up to five users, one base and ten EZQL queries per month. Choose NatureQuery for a $0 plan with 50 queries per month, one database connection, exports and 30-day history.

QueryPlane fits self-hosted or web deployments needing up to three apps and 50 AI prompts monthly on its free tier. Savvina AI offers a free community tier for one user with PostgreSQL and MySQL support. Choose SQL Mocker when a web-based tool with 50 total AI queries and five saved projects is enough. Wren AI is an alternative with a free open-source context engine for individual developers. IDERA AI SQL Query Generator is a free web option.

See the broader AI SQL Generators list for more choices.

Verdict

SQLer is a strong choice for developers embedding natural-language-to-SQL into applications that can provide detailed business and schema context. Its multi-dialect support, refreshable schema setup and customer-environment execution are the main reasons to choose it. Look elsewhere if monthly quotas do not fit your traffic or if one query must span separate databases.