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next.jdbc

The next generation of clojure.java.jdbc: a new low-level Clojure wrapper for JDBC-based access to databases.

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TL;DR

The latest versions on Clojars and on cljdoc:

The documentation on cljdoc.org is for the current version of next.jdbc:

Getting Started
API Reference
Migrating from clojure.java.jdbc
Feedback via issues or in the #sql channel on the Clojurians Slack or the #sql stream on the Clojurians Zulip.

The documentation on GitHub is for develop since the 1.2.674 release -- see the CHANGELOG and then read the corresponding updated documentation on GitHub if you want. Older versions of next.jdbc were published under the seancorfield group ID and you can find older seancorfield/next.jdbc documentation on cljdoc.org.

This project follows the version scheme MAJOR.MINOR.COMMITS where MAJOR and MINOR provide some relative indication of the size of the change, but do not follow semantic versioning. In general, all changes endeavor to be non-breaking (by moving to new names rather than by breaking existing names). COMMITS is an ever-increasing counter of commits since the beginning of this repository.

Motivation

Why another JDBC library? Why a different API from clojure.java.jdbc?

Performance: there's a surprising amount of overhead in how ResultSet objects are converted to sequences of hash maps in clojure.java.jdbc – which can be really noticeable for large result sets – so I wanted a better way to handle that. There's also quite a bit of overhead and complexity in all the conditional logic and parsing that is associated with db-spec-as-hash-map.
A more modern API, based on using qualified keywords and transducers etc: :qualifier and reducible-query in recent clojure.java.jdbc versions were steps toward that but there's a lot of "legacy" API in the library and I want to present a more focused, more streamlined API so folks naturally use the IReduceInit / transducer approach from day one and benefit from qualified keywords.
Simplicity: clojure.java.jdbc uses a variety of ways to execute SQL which can lead to inconsistencies and surprises – query, execute!, and db-do-commands are all different ways to execute different types of SQL statement so you have to remember which is which and you often have to watch out for restrictions in the underlying JDBC API.

Those were my three primary drivers. In addition, the db-spec-as-hash-map approach in clojure.java.jdbc has caused a lot of frustration and confusion in the past, especially with the wide range of conflicting options that are supported. next.jdbc is heavily protocol-based so it's easier to mix'n'match how you use it with direct Java JDBC code (and the protocol-based approach contributes to the improved performance overall). There's a much clearer path of db-spec -> DataSource -> Connection now, which should steer people toward more connection reuse and better performing apps.

I also wanted datafy/nav support baked right in (it was added to clojure.java.jdbc back in December 2018 as an undocumented, experimental API in a separate namespace). It is the default behavior for execute! and execute-one!. The protocol-based function next.jdbc.result-set/datafiable-row can be used with plan if you need to add datafy/nav support to rows you are creating in your reduction.

As next.jdbc moved from alpha to beta, the last breaking change was made (renaming reducible! to plan) and the API should be considered stable. Only accretive and fixative changes will be made from now on.

After a month of alpha builds being available for testing, the first beta build was released on May 24th, 2019. A release candidate followed on June 4th and the "gold" (1.0.0) release was on June 12th. In addition to the small, core API in next.jdbc, there are "syntactic sugar" SQL functions (insert!, query, update!, and delete!) available in next.jdbc.sql that are similar to the main API in clojure.java.jdbc. See Migrating from clojure.java.jdbc for more detail about the differences.

Usage

The primary concepts behind next.jdbc are that you start by producing a javax.sql.DataSource. You can create a pooled datasource object using your preferred library (c3p0, hikari-cp, etc). You can use next.jdbc's get-datasource function to create a DataSource from a db-spec hash map or from a JDBC URL (string). The underlying protocol, Sourceable, can be extended to allow more things to be turned into a DataSource (and can be extended via metadata on an object as well as via types).

From a DataSource, either you or next.jdbc can create a java.sql.Connection via the get-connection function. You can specify an options hash map to get-connection to modify the connection that is created: :read-only, :auto-commit.

The primary SQL execution API in next.jdbc is:

plan -- yields an IReduceInit that, when reduced, executes the SQL statement and then reduces over the ResultSet with as little overhead as possible.
execute! -- executes the SQL statement and produces a vector of realized hash maps, that use qualified keywords for the column names, of the form :<table>/<column>. If you join across multiple tables, the qualified keywords will reflect the originating tables for each of the columns. If the SQL produces named values that do not come from an associated table, a simple, unqualified keyword will be used. The realized hash maps returned by execute! are Datafiable and thus Navigable (see Clojure 1.10's datafy and nav functions, and tools like Cognitect's REBL). Alternatively, you can specify {:builder-fn rs/as-arrays} and produce a vector with column names followed by vectors of row values. rs/as-maps is the default for :builder-fn but there are also rs/as-unqualified-maps and rs/as-unqualified-arrays if you want unqualified :<column> column names (and there are also lower-case variants of all of these).
execute-one! -- executes the SQL or DDL statement and produces a single realized hash map. The realized hash map returned by execute-one! is Datafiable and thus Navigable.

In addition, there are API functions to create PreparedStatements (prepare) from Connections, which can be passed to plan, execute!, or execute-one!, and to run code inside a transaction (the transact function and the with-transaction macro).

Since next.jdbc uses raw Java JDBC types, you can use with-open directly to reuse connections and ensure they are cleaned up correctly:

  (let [my-datasource (jdbc/get-datasource {:dbtype "..." :dbname "..." ...})]
    (with-open [connection (jdbc/get-connection my-datasource)]
      (jdbc/execute! connection [...])
      (reduce my-fn init-value (jdbc/plan connection [...]))
      (jdbc/execute! connection [...])))

Usage scenarios

There are three intended usage scenarios that have driven the design of the API:

Execute a SQL statement and process it in a single eager operation, which may allow for the results to be streamed from the database (how to persuade JDBC to do that is database-specific!), and which cleans up resources before returning the result -- even if the reduction is short-circuited via reduced. This usage is supported by plan. This is likely to be the fastest approach and should be the first option you consider for SQL queries.
Execute a SQL or DDL statement to obtain a single, fully-realized, Datafiable hash map that represents either the first row from a ResultSet, the first generated keys result (again, from a ResultSet), or the first result where neither of those are available (next.jdbc yields {:next.jdbc/update-count N} when it can only return an update count). This usage is supported by execute-one!. This is probably your best choice for most non-query operations.
Execute a SQL statement to obtain a fully-realized, Datafiable result set -- a vector of hash maps. This usage is supported by execute!. You can also produce a vector of column names/row values (next.jdbc.result-set/as-arrays).

In addition, convenience functions -- "syntactic sugar" -- are provided to insert rows, run queries, update rows, and delete rows, using the same names as in clojure.java.jdbc. These are in next.jdbc.sql since they involve SQL creation -- they are not considered part of the core API.

License

Distributed under the Eclipse Public License version 1.0.

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