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


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Why another JDBC library? Why a different API from

  • Performance: there's a surprising amount of overhead in how ResultSet objects are converted to sequences of hash maps – which can be really noticeable for large result sets – so I want 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 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: 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 are my three primary drivers. In addition, the db-spec-as-hash-map approach in 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 back in December 2018 as an undocumented, experimental API in a separate namespace). It is the default behavior for execute! and execute!. The protocol-based function next.jdbc.result-set/datafiable-row can be used with reducible! if you need to add datafy/nav support to rows you are creating in your reduction.

At this point, I would consider the API to be fairly stable and alpha builds are now available on Clojars (2019-04-20). The "syntactic sugar" SQL functions (insert!, query, update!, and delete!) go beyond what I wanted to include in the core API so they are in next.jdbc.sql. I know that their equivalents in are heavily used (based on the number of questions and JIRA issues I get).

I am still considering whether this should go into Contrib as new namespaces in or whether it will continue to live standalone so I'm not accepting Pull Requests yet (but I can't disable them on GitHub!). There are pros and cons to both choices, in my mind.


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:

  • reducible! -- 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 {:gen-fn rs/as-arrays} and produce a vector with column names followed by vectors of row values. rs/as-maps is the default for :gen-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 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 reducible!, 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 (get-datasource {:dbtype "..." :dbname "..." ...})]
    (with-open [connection (get-connection my-datasource)]
      (execute! connection [...])
      (reduce my-fn init-value (reducible! connection [...]))
      (execute! connection [...])

Usage scenarios

There are three intended usage scenarios that may drive the API to change:

  • Execute a SQL 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 currently supported by execute-one!.
  • 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).
  • 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 reducible!.

In addition, convenience functions -- "syntactic sugar" -- are provided to insert rows, run queries, update rows, and delete rows, using the same names as in These are in next.jdbc.sql since they involve SQL creation -- they may move into a separate "sibling" library, since they are not part of the intended core API.

More Detailed Documentation


Copyright © 2018-2019 Sean Corfield

Distributed under the Eclipse Public License version 1.0.

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