Releases

This is a reverse chronological summary of TinyJoin releases and their public compatibility boundaries. Every entry states what upgrading to it requires, so check the entries between the version in use and the target before upgrading. A release that needs no action says so explicitly.

v0.5.0

This release connects TinyJoin to the Drizzle ORM and the Kysely query builder, and adds what they need: a typed schema API, foreign keys, fuller ALTER TABLE, and more of the SQL dialect that hand-written statements and query builders use. It also fixes two v0.4.0 bugs, and reads rows faster.

A database with a column declared DEFAULT NULL opens again. v0.4.0 and earlier wrote such a column's default into a persistent database correctly, but read it back as no default at all, so the catalog no longer matched what had been written, and opening the database failed with PAGED_STORAGE_CORRUPT. v0.5.0 reads the default as it was written, so an affected v0.4.0 database opens with its data intact. In-memory databases, which are never reopened, were not affected.

Adding a NOT NULL column without a default to a table with rows fails again. v0.4.0 stopped writing every row again when ALTER TABLE ... ADD COLUMN adds a column, and with that stopped checking that the rows could hold it, so a NOT NULL column without a default could be added to a table with rows, which then held NULL in it: queries returned the NULL, and check() reported the table as corrupt. v0.5.0 refuses the statement with CONSTRAINT_VIOLATION, as v0.3.0 and PostgreSQL do. To repair a table that v0.4.0 left this way, give the column a value in every row, as in UPDATE t SET c = 0 WHERE c IS NULL, or drop its NOT NULL.

The new tinyjoin/drizzle entry point connects the Drizzle ORM to a TinyJoin Client: drizzle(client, {schema}) returns a Drizzle database whose queries run in TinyJoin's dialect, whose transactions are TinyJoin's callback transactions, and whose JSON columns store JSON values rather than JSON text. The application installs drizzle-orm 0.45 itself; TinyJoin declares it as an optional peer dependency and never bundles it, so the download sizes are unchanged. Its migrate() function applies the migrations that drizzle-kit generate writes, from SQL the application bundles, each atomically with the row that records it, so every tab can call it as it starts. Drizzle Kit's push and Drizzle's own migrators are not supported. See the Drizzle guide.

The new tinyjoin/kysely entry point connects the Kysely query builder to a TinyJoin Client. Its TinyJoinDialect, constructed with {client}, is a Kysely dialect whose queries run in TinyJoin's dialect, whose transactions are TinyJoin's callback transactions, whose introspector reads getSchema(), and under which Kysely's Migrator runs, one tab at a time. The application installs kysely 0.28 or later itself; TinyJoin declares it as an optional peer dependency and never bundles it. See the Kysely guide.

The new getSchema() method on the Client reads the database's tables, with their columns, primary keys, indexes, and foreign keys, as typed objects rather than through SQL catalog tables, which TinyJoin does not have. Each column carries its runtime type, whether it is nullable, any literal default, and any VARCHAR length. See reading the schema.

The new setSchema() method makes the database's tables match a schema in the shape getSchema() returns, in one atomic change: it creates what is missing, renames tables and columns from the names they had, changes defaults, nullability, and VARCHAR lengths, and makes each table's indexes the schema's, keeping every row, and drops what the schema leaves out only when asked. A schema the database already has changes nothing, and a schema version keeps a tab running older code from undoing newer changes. tinyjoin/drizzle adds push(), which sets a Drizzle schema this way, in place of migrations. See setting the schema.

Foreign keys are enforced. A column's REFERENCES, or a table's FOREIGN KEY ... REFERENCES, names the table and columns its values must be found in, unless one is NULL, and each key is checked as its statement ends, inside transactions too. Deleting or updating a referenced row does what the key's ON DELETE and ON UPDATE actions say: NO ACTION and RESTRICT refuse it, CASCADE deletes or updates the referencing rows in the same statement, and SET NULL and SET DEFAULT change their references. ALTER TABLE adds a key, checking every stored row, and drops one; renames follow into the keys; and dropping a table, column, or unique index a key needs takes CASCADE, which drops the key. getSchema() and setSchema() include each table's keys, and Drizzle's .references() pushes as one. See foreign keys.

CREATE TABLE accepts the constraints and spellings that schema tools write: a named primary key, as in CONSTRAINT tags_pk PRIMARY KEY (post_id, tag); UNIQUE on a column or as a table constraint, which creates a unique index named as PostgreSQL would name it; a JSON default written as '{}'::jsonb; and USING btree on an index. ALTER TABLE can add and drop a unique constraint, and accepts DISABLE ROW LEVEL SECURITY, which changes nothing. DROP TABLE and DROP INDEX accept CASCADE and RESTRICT. Together these run the SQL that drizzle-kit generate writes for new tables. See constraints and indexes.

ALTER TABLE can now also rename a table or a column, drop a column, set or drop a column's default, and set or drop NOT NULL, and accepts a column type that restates the runtime type it has, as bigint does for integer. Existing rows keep their values: dropping a column, changing a default, and setting NOT NULL rewrite the table's rows, and SET NOT NULL fails, changing nothing, while a row holds NULL. A dropped column takes every index on it with it, as in PostgreSQL, and indexes follow renamed columns and tables.

A VARCHAR(n) or CHARACTER VARYING(n) column holds at most n characters, and a longer value fails with CONSTRAINT_VIOLATION, as in PostgreSQL, except that TinyJoin also refuses a value whose excess is spaces, which PostgreSQL would trim. n was previously rejected, so schemas that ORMs and migration tools write with lengths, such as Drizzle's varchar({length}) and Kysely's migration tables, now run. getSchema() reports the length as maxLength.

A statement over one table can qualify its columns with the table's name, as a join already could: SELECT tasks.id FROM tasks WHERE tasks.done = false ORDER BY tasks.title, or tasks.* for every column. UPDATE and DELETE accept the same in WHERE and RETURNING, and INSERT in RETURNING. A qualified statement is planned exactly as its plain spelling is, so it uses the same key lookups and index ranges. In ORDER BY, a qualified name is always the table's column, where a plain name matches an output alias first. See qualified columns.

A single-table SELECT, UPDATE, or DELETE also accepts a table alias, with or without AS, as each table of a join already did: SELECT t.id FROM tasks AS t WHERE t.done = false, or DELETE FROM tasks t WHERE t.id = $1. As in PostgreSQL, the alias replaces the table's name as the qualifier. Results, changed tables, and subscriptions still name the table.

A SELECT read with rowMode: "array" may now return several fields of one name, such as the id of each table in a join, because an array row holds its values by position. Object rows still require distinct output names and reject the same statement with INVALID_QUERY, as before. Query builders that map rows by position, as Drizzle does, depend on this. See repeated output names.

An UPDATE or ON CONFLICT DO UPDATE assignment can now work its value out from the row it updates, so a counter no longer needs a read before its write: UPDATE counters SET hits = hits + 1 WHERE id = $1. An expression combines columns, literals, and parameters with +, -, *, /, %, unary -, and ||. Integers stay within the JavaScript-safe range and divide by truncating, floats must stay finite and take no %, and there are no implicit casts. In an upsert, the stored row's columns are named with the table's name and the proposed row's with EXCLUDED, as in SET hits = counters.hits + EXCLUDED.hits. Types are checked before any row is read.

Either side of a WHERE comparison can now be an expression too, so a query can compare two columns, as in WHERE updated > created, or a value worked out from the row, as in WHERE price * quantity > $1. A comparison of a column with a value worked out from literals and parameters, such as created > $1 - 86400, still reads only a range of an index or the primary key.

A single-table or join query can also return expressions, as in SELECT id, price * quantity AS total FROM items ORDER BY total DESC, and ORDER BY can name an expression's alias. An expression without an alias is named ?column?, as in PostgreSQL. Aggregate and SELECT DISTINCT queries still return only columns and aggregates. See expressions.

A join's select list can use * for every column of every table and table.* for every column of one, as in SELECT p.*, u.name FROM posts p JOIN users u ON u.id = p.user_id, and a single table's can put * beside other outputs, as in SELECT *, price * quantity AS total FROM items. Object rows still need distinct names, so a * over tables that share a column name needs array rows.

IN and NOT IN can take the values of a subquery, as in WHERE user_id IN (SELECT id FROM users WHERE team = $1), in any statement with a WHERE clause. The subquery runs once, before the statement reads any row, must return one column and at most 1,024 rows, and cannot read the statement around it. See subqueries.

A query can nest queries that read each of its rows, as ORMs write them to load related rows: a (SELECT ...) in the select list that returns one value, as in (SELECT count(*) FROM posts p WHERE p.user_id = u.id), and a LEFT JOIN LATERAL (SELECT ...) alias ON true. Their rows can be gathered into JSON with json_agg, json_build_array, to_json, and coalesce(..., '[]'), including from a query in FROM (SELECT ...) alias. Each nested query runs once for every row around it, up to 100,000 in a statement. Drizzle's relational queries with with, and Kysely's jsonArrayFrom and jsonObjectFrom, run this way. See nested queries.

The warm-up Worker that create() starts runs its loops three-quarters as long, and so finishes sooner. It was still running while a database ran its first statements, and slowed them: in the comparative benchmark, timed workloads now run about 5% faster overall, point reads about 8% faster, and indexed range aggregates about a fifth faster.

A single-table SELECT whose rows arrive in key order no longer builds each row as an object of its values under their names before the Worker writes the row out. Reading all 10,000 rows of the comparative benchmark takes two-fifths less time, and a point read by key about 3% less, for 1.2 KiB more of compressed engine.

The compressed download is now 339 KiB, up from 301 KiB in v0.4.0, for the engine's new SQL, foreign keys, and schema API. The Drizzle and Kysely entry points, and the libraries they connect, load only in an application that imports them.

Upgrading from v0.4.0 needs no action. Install, rebuild, and redeploy. The page format stays at format 3, so an existing database opens with no migration and no OPFS namespace change. A database that holds a VARCHAR(n) column, a schema version from setSchema(), or a foreign key cannot be opened by v0.4.0, which reports its catalog as corrupt, so do not roll back past v0.5.0 once a database holds any of them. The Worker protocol moves from version 10 to 11 for the schema request. Client and Worker ship together and are upgraded together by a normal install, so this affects only a deployment that pins or caches a Worker file independently of the client bundle, where a mismatched pair fails cleanly with PROTOCOL_MISMATCH. The new syntax was previously rejected, so statements that already worked keep their meaning, with one exception: where a table has a column whose quoted name begins with the table's own name and a dot, such as "extra.value" in a table named extra, an unquoted extra.value in WHERE used to read that column and now reads the table's value column. Quote the name to read it.

v0.4.0

Persistent storage breaks compatibility with v0.3.0 and earlier. v0.4.0 introduces page format 3, which stores each row as packed binary columns rather than as JSON text, and encodes keys so that they sort in the same order SQL compares their values. Rows take less space, a query can read the columns it needs without parsing the rest of the row, and ALTER TABLE ... ADD COLUMN no longer rewrites every existing row.

v0.1.0 through v0.3.0 use page format 2. Opening a page format 2 database with v0.4.0 fails with UNSUPPORTED_PAGE, and so does opening a page format 3 database with an earlier release. There is no automatic migration, and changing the OPFS name does not copy existing data.

In-memory databases, including every tinyjoin/node database, are unaffected.

Object rows now list their columns in field order. A row's keys follow the result's fields, as in PostgreSQL, so SELECT title, id returns rows whose first key is title, and a changed key lists a composite primary key's columns in the order the key declares them. Earlier releases sorted both alphabetically. Code that reads a row or key by column name is unaffected; only code that depends on key order, such as Object.keys(row) or JSON.stringify(row), sees a difference.

The Worker protocol version moves from 8 to 10. Client and Worker ship together and are upgraded together by a normal install, so this affects only a deployment that pins or caches a Worker file independently of the client bundle. A mismatched pair fails cleanly with PROTOCOL_MISMATCH, and tabs running different releases fail with DATABASE_VERSION_MISMATCH, rather than misreading each other's results.

Numbers keep every bit. Numbers in JSON values and SQL text are now read with correct rounding. Earlier releases read about one in ten numbers that need all 17 significant digits, such as many results of Math.random(), as a neighboring value. In v0.3.0 and earlier, a row holding one could then not be read at all: reading it failed with PAGED_STORAGE_CORRUPT, because the row no longer matched its stored text.

Opening a database checks its catalog, not every row. Earlier releases read every row and index entry when opening a database, so opening took time in proportion to its size, and refused a database that failed. Each page is still checked when it is read, and the new check() reads the whole database on demand, rejecting with the first problem it finds. A database whose damage no statement reads now opens, and only check() reports it. See checking a database.

This release is also much faster. In the comparative benchmarks, most workloads in v0.3.0 took 10 to 1,400 times as long as the faster of SQLite and PGlite. None now takes as much as twice as long, and reopening a database, reading every row, LIKE scans, GROUP BY, joins, building indexes, and committing a single insert are quicker than in either.

The compressed download is now 301 KiB, up from 295 KiB in v0.3.0.

v0.3.0

This release closes some of the most commonly encountered gaps in the SQL dialect. Each form is new syntax that was previously rejected, so an existing statement keeps its meaning.

BETWEEN and NOT BETWEEN are accepted wherever a WHERE clause is, including in aggregates, joins, UPDATE, DELETE, and prepared statements. price BETWEEN $1 AND $2 means exactly price >= $1 AND price <= $2, with the same type checking and NULL behavior as those two comparisons, and it is inclusive at both ends. There is no SYMMETRIC form, so a range whose bounds are reversed matches nothing rather than being swapped.

A single-table SELECT can now rename its columns with AS, as aggregate and join queries already could: SELECT id AS task_id, title FROM tasks. The alias becomes the result field name, ORDER BY can refer to it, and one column may be returned under several names. As in PostgreSQL, an ORDER BY name matches an output alias before a source column of the same name. Output names must still be distinct.

SELECT DISTINCT removes duplicate rows from a single-table or join projection, which is especially useful for collapsing the rows a many-to-many join multiplies, as in SELECT DISTINCT tag.name FROM post_tags JOIN tags AS tag ON post_tags.tag_id = tag.id. NULLs compare as equal to one another, and LIMIT and OFFSET count distinct rows. As in PostgreSQL, ORDER BY must name projected columns. The projection must list its columns explicitly and cannot contain JSON columns or aggregates, and DISTINCT ON and aggregate DISTINCT, such as COUNT(DISTINCT column), remain unsupported. A column named distinct remains usable.

INSERT ... ON CONFLICT makes an upsert one atomic statement rather than an UPDATE followed by a conditional INSERT inside a transaction, which held every tab sharing the database for the duration. ON CONFLICT (id) DO NOTHING skips conflicting rows, and ON CONFLICT (id) DO UPDATE SET value = EXCLUDED.value rewrites the stored row. The target is the primary key or the columns of one unique index, and DO NOTHING may omit it to treat every unique constraint as an arbiter. Rows are handled one at a time as in PostgreSQL, so a statement that would update the same row twice fails with CONSTRAINT_VIOLATION. SET accepts literals, parameters, DEFAULT, and EXCLUDED columns, but cannot read the existing row or change its primary key, and DO UPDATE ... WHERE is not supported. RETURNING, the row count, and changed keys include only inserted and updated rows, so a statement that skips every row reports no change. See upserts.

LIKE, ILIKE, and their NOT forms match a text column against a pattern in which % matches any run of characters and _ exactly one, so a search box no longer has to filter rows in JavaScript: WHERE title ILIKE $1 with '%' + term + '%'. Backslash escapes a literal % or _ unless an ESCAPE clause names another character, and a pattern that ends in its escape character is rejected. A search term from user input should have its own %, _, and backslash characters escaped before being wrapped in wildcards. ILIKE folds only ASCII letters, as PostgreSQL does under the C locale, which is consistent with TinyJoin's code-point ordering, so 'É' ILIKE 'é' is false. Pattern matching always scans candidate rows rather than using an index.

Upgrading from v0.2.0 needs no action. Install, rebuild, and redeploy. The Worker protocol stays at version 8 and the page format stays at format 2, so an existing database opens with no migration and no OPFS namespace change. The new syntax was previously rejected, so statements that already worked keep their results.

The engine is now built with Rust 1.98.1 rather than 1.91.1. That more than offsets the new SQL, so the compressed WebAssembly engine is about 4 KiB smaller than in v0.2.0.

v0.2.0

Subscriptions and statement results now report which rows changed, not only which tables. A TablesChangedEvent and every Results carry a keys map of table name to the primary keys that changed, so a listener can refresh individual rows instead of re-reading a table. Keys are reported for writes from any connected Client, which makes a change made in another tab resolvable to individual rows. See refreshing individual rows.

Reporting is a bounded best effort, and the changed-table list stays authoritative. A table appears in keys only when every key it changed fits the bound of 1,000 keys per table; a table that changed more rows is absent rather than partially listed, so an absent table means its rows cannot be named and must be re-queried. keys is always empty alongside reset: true. Code that assumes keys are present will silently miss large writes, so handle the absent case.

The Worker protocol version moves from 7 to 8. Client and Worker ship together and are upgraded together by a normal install, so this affects only a deployment that pins or caches a Worker file independently of the client bundle. A mismatched pair fails cleanly with PROTOCOL_MISMATCH rather than misreading a result. Applications using tinyjoinOffline() are unaffected: the plugin revisions both files by content, so a rebuild replaces them together.

Upgrading from v0.1.0 needs no action. Install, rebuild, and redeploy. Persistent storage is unchanged: the page format remains format 2, so an existing database opens with no migration and no OPFS namespace change. The keys field is additive, so application code that ignores it behaves exactly as it did before.

Grouped and aggregate queries now use a secondary index when their predicate supplies every column of one, instead of always scanning the table. Results are unchanged, because the predicate is still evaluated for each candidate row. Because the scan limit counts candidate rows, a grouped query that previously exceeded QUERY_WORK_LIMIT_EXCEEDED on a large table may now succeed.

tinyjoin/node no longer fails to start when the parent process runs with a flag that Node rejects for a worker thread, such as the --stack-trace-limit that several test runners set. Inherited flags are dropped rather than the database failing to open.

v0.1.0

The new Node entry point, tinyjoin/node, opens in-memory databases in Node.js 22 or later. It constructs a Worker thread and loads WASM automatically, returning the same Client API without additional dependencies. Each Client owns an independent database; filesystem persistence is not included.

Persistent storage breaks compatibility with v0.0.5. The npm v0.0.5 release uses page format 1; v0.1.0 uses page format 2. Opening a v0.0.5 database with v0.1.0 fails with UNSUPPORTED_PAGE. There is no automatic migration, and changing the OPFS name does not copy existing data.

This release also makes predicate and assignment type validation consistent across reads and writes, compares heterogeneous JSON values consistently, and bounds shared parameter-graph traversal and expanded SQL bindings before copying values. Append-only transactions now validate new row statements incrementally, including unique-index checks; mixed writes retain complete staged write-set validation.

Selective multi-table joins now use their actual comparison count rather than a worst-case Cartesian estimate. Scan, build-row, result, memory, and shared script-work limits remain in force.

Page checksum calculation is faster while preserving the stored checksum values, storage format, and corruption checks. This improves mixed writes and populated startup; the repository's workload measurements retain the before/after samples and runtime hashes.

UPDATE and DELETE now use direct primary-key lookup for exact complete key predicates, including staged transaction rows. Other predicates retain their scan path, and statement validation and constraint checks remain in force.

Persistent startup avoids a redundant table scan for unique indexes whose columns are all NOT NULL. Table validation and complete index-entry checks remain in force; nullable indexes and indexes without uniqueness retain the existing count scan.

Duplicate output names in simple projections and RETURNING now fail consistently with INVALID_QUERY before execution. LIMIT and OFFSET reject nonnumeric parameter values consistently in ordinary, aggregate, and join queries, including JSON objects shaped like internal prepared placeholders.

Persistent Clients now coordinate automatically across tabs and within a page. One elected Worker owns the database; operations, prepared statements, and notifications follow it through handover. Callback transactions exclude other Clients for their duration. In-flight operations interrupted by owner loss reject without automatic replay, and incompatible releases reject explicitly.

The optional tinyjoin/vite build plugin precaches a complete production application, including lazy Worker, OPFS, and WASM assets. New starter apps enable it by default. Updates wait for old controlled tabs to close; existing service workers can use its generated manifest and helper instead. See the offline guide.

v0.0.5

This release establishes TinyJoin as a standalone, SQL-first browser database package.

TinyJoin remains experimental and deliberately smaller than PostgreSQL. This release does not include a PostgreSQL server or wire protocol, hosted service, remote replication, or offline-write synchronization.