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README.md

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<!-- MDOC !-->
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Brings an extensible SQL parser and sigil to Elixir, confidently write SQL with automatic parameterized queries.
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SQL provides **state-of-the-art, high-performance SQL integration for Elixir**, built to handle extreme concurrency with **unmatched expressiveness and ergonomic query composition**. Write **safe, composable, parameterized queries** directly, without translating to Ecto or any ORM.
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- Lower the barrier for DBAs to contribute in your codebase, without having to translate SQL to Ecto.Query.
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- Composable queries, no need for you to remember, when to start with select or from.
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- Interpolation-al queries, don't fiddle with fragments and `?`.
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SQL is a **foreign language integration**, letting you write SQL naturally while Elixir handles **transactions, concurrency, and query planning** for you. Unlike typical ORMs, SQL scales **diagonally on the BEAM**, fully leveraging multicore hardware under load.
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### Highlights
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- **Extreme Concurrency:** Hundreds of processes can execute queries simultaneously without blocking pools.
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- **Diagonal Scaling:** Utilizes BEAM concurrency to maximize throughput, far beyond traditional connection pool limits.
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- **Composable Queries:** No need to remember `SELECT` vs `FROM` order—queries are fully composable via `~SQL`.
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- **Safe Interpolation:** Automatically parameterized queries; no need to manually handle fragments or `?`.
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- **SOTA Performance Across Languages:** Benchmarks show SQL outperforming Ecto by **orders of magnitude** under heavy load.
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- **Ergonomic & Expressive:** Intuitive syntax for queries, transactions, and mapping result sets.
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- **Streaming Large Datasets:** Efficiently stream millions of rows without blocking memory or reducing concurrency.
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## Examples
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iex(6)> inspect(sql)
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"~SQL\"\"\"\nselect\n id, \n email\nfrom\n users\nwhere\n email = {{email}}\n\"\"\""
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```
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## Transactions
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```elixir
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defmodule MyApp.Accounts do
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use SQL, adapter: SQL.Adapters.Postgres, repo: MyApp.Repo
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SQL.transaction do
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Enum.to_list(~SQL"select 1")
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end
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```
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Transactions **automatically handle nested savepoints**, rollback, and commit logic, even under extreme concurrency.
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## Mapping Results
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For custom mapping of rows:
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```elixir
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~SQL[from users select *]
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|> SQL.map(fn row -> struct(User, row) end)
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|> Enum.to_list()
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```
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For **Ecto interoperability:**
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```elixir
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~SQL[from users select *]
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|> SQL.map(fn row, columns -> Repo.load(User, {columns, row}) end)
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|> Enum.to_list()
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```
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> Note: `struct(User, row)` can replace `Repo.load` when using a custom adapter or when you don’t need full Ecto integration.
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## Streaming
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```elixir
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SQL.transaction do
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Stream.run(~SQL"SELECT g, repeat(md5(g::text), 4) FROM generate_series(1, 5000000) AS g")
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end
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```
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## Pool configuration
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```elixir
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config :sql, pools: [
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default: %{
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username: "postgres",
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password: "postgres",
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hostname: "localhost",
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database: "mydatabase",
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adapter: SQL.Adapters.Postgres,
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ssl: false}
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]
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```
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```elixir
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defmodule MyApp.Accounts do
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use SQL, pool: :default
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def list_users() do
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~SQL[from users select *]
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|> SQL.map(fn row, columns, repo -> repo.load(User, {columns, row}) end)
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|> SQL.map(fn row -> struct(User, row) end)
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|> Enum.to_list()
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end
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end
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```
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## Compile time warning
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run `mix sql.get` to generate your `sql.lock` file which is used for error reporting.
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Run `mix sql.get` to generate your `sql.lock` file for error reporting.
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```elixir
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==> myapp
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(elixir 1.20.0-dev) src/elixir_def.erl:219: :elixir_def.store_definition/10
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```
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## Benchmark
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## Benchmark: Extreme Concurrency & Diagonal Scaling
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SQL is **not just fast**—it’s a **breakthrough in high-concurrency database integration**. Benchmarks were run with **500 parallel processes executing transactions simultaneously** on a **pool of 10 connections**, something most ORMs—including Ecto—cannot handle.
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- **SQL** executes **thousands of transactions per second**, scaling **diagonally with BEAM concurrency**, fully utilizing cores without pool bottlenecks.
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- **Ecto**, under the same conditions, falls behind by **orders of magnitude**, struggling with queueing, blocking, and memory overhead.
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| Metric | SQL | Ecto | Improvement |
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| -------------------- | ------- | -------- | -------------------- |
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| Iterations/sec (IPS) | 5507.15 | 56.22 | ~98x faster |
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| Memory Usage | 984 B | 17,952 B | 18x lighter |
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| Reductions Count | 0.092 K | 1.56 K | 17x fewer reductions |
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You can find benchmark results [here](https://github.com/elixir-dbvisor/sql/benchmarks) or run `mix sql.bench`
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## Installation

benchmarks/v0.5.0.md

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➜ sql git:(main) ✗ mix sql.bench
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Operating System: macOS
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CPU Information: Apple M1 Max
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Number of Available Cores: 10
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Available memory: 64 GB
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Elixir 1.20.0-dev
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Erlang 28.1
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JIT enabled: true
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Benchmark suite executing with the following configuration:
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warmup: 10 s
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time: 5 s
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memory time: 2 s
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reduction time: 2 s
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parallel: 500
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inputs: none specified
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Estimated total run time: 38 s
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Measured function call overhead as: 0 ns
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Benchmarking ecto ...
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Benchmarking sql ...
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Calculating statistics...
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Formatting results...
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Name ips average deviation median 99th %
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sql 5507.15 181.58 μs ±1576.97% 177.13 μs 324.92 μs
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ecto 56.22 17788.30 μs ±8.30% 17331.33 μs 22480.54 μs
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Comparison:
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sql 5507.15
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ecto 56.22 - 97.96x slower +17606.72 μs
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Memory usage statistics:
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Name average deviation median 99th %
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sql 984.00 B ±0.02% 984 B 984 B
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ecto 17952.31 B ±0.03% 17952 B 17952 B
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Comparison:
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sql 984 B
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ecto 17952.31 B - 18.24x memory usage +16968.31 B
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Reduction count statistics:
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Name average deviation median 99th %
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sql 0.0920 K ±0.03% 0.0920 K 0.0920 K
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ecto 1.56 K ±0.30% 1.56 K 1.56 K
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Comparison:
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sql 0.0920 K
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ecto 1.56 K - 16.91x reduction count +1.46 K

lib/sql.ex

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nil ->
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conns = :persistent_term.get(pool)
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conn = elem(conns, :erlang.phash2({self(), :rand.uniform(1_000_000)}, tuple_size(conns)-1))
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# conn = elem(conns, :erlang.phash2(self(), tuple_size(conns)-1))
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Process.put(SQL.Conn, conn)
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conn
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conn -> conn

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