Three years ago, we announced Dolt 1.0, signalling that Dolt was ready for production workloads. We haven’t stopped improving the world’s first and only version-controlled SQL database. Today, we are excited to announce Dolt 2.0.

What Did Dolt 1.0 Mean?#

Dolt 1.0 meant four things:

1. Forward Storage Compatibility
2. Production Performance
3. MySQL Compatibility
4. Stable Version Control Interface

Dolt 2.0 maintains the promises of Dolt 1.0. Dolt 2.0 improves on the performance and correctness metrics established in Dolt 1.0.

What Does Dolt 2.0 Mean?#

Dolt 2.0 also means four things:

1. Automated Garbage Collection on by Default
2. Archive Compression on by Default
3. Faster than MySQL on sysbench
4. Beta Vector Support
5. Adaptive Storage

Unlike Dolt 1.0, Dolt 2.0 is fully backwards compatible with all Dolt 1.0 versions. No storage migration using dolt migrate is required. Let’s dive into the details of each of these points.

Garbage Collection#

Dolt makes a lot of disk garbage, especially during import. Dolt is copy-on-write so all intermediate committed transaction state is preserved to disk. Any intermediate state that is not in a Dolt commit is garbage and can be collected.

Dolt already must preserve all history in the commit graph on disk. Adding extra garbage can eat through your disk very quickly.

Dolt 2.0 has automatic garbage collection on by default, meaning most users don’t have to care about disk garbage. Many users have been running in this mode for over a year. We’re confident it is stable.

Dolt 2.0 databases do not require extra garbage maintenance, just like other modern SQL engines.

Archives#

Following on the disk space theme, we also have a new on disk format we call archives that can reduce Dolt’s storage footprint by an additional 30-50%. Archives use dictionary compression to de-duplicate storage in the deepest layers of Dolt, saving even more disk space.

As with automatic garbage collection, archives have been the default format for new Dolt databases for months. We’re confident the format is stable and delivers real disk space wins.

Dolt 2.0 databases are kind to your disk with automatic garbage collection and archives. Version control already requires more disk space than traditional databases. Dolt 2.0 preserves that disk for your data’s history.

Faster than MySQL on sysbench#

We’ve long used the industry standard sysbench to measure and benchmark the latency of simple SQL queries in Dolt. We started at about 10X slower on reads and 20X slower on writes than MySQL. We’ve worked tirelessly to improve Dolt’s performance and we are now 13% faster than MySQL on writes and 5% faster on reads, averaging out to 8% faster than MySQL on sysbench style workloads.

Dolt 2.0 databases deliver real production database performance coupled with version control functionality.

Beta Vector Support#

We announced vector index support early last year. We have a much bigger challenge than traditional databases with vector indexes because our vector indexes must be version-controlled. We’ve done the hard computer science to achieve this. We adopted the Vector type from MariaDB in September 2025.

Dolt 2.0 databases have Beta vector support. Dolt is the only database where your vectors are version-controlled. We still have some edge cases on the read query path where a vector index should be used but it is not. Closing these gaps will reove the Beta tag from Dolt’s vector support.

Adaptive storage for large column types#

Borrowing from our Doltgres adaptive storage work to support TOAST types, we’re excited to announce Dolt 2.0 has adaptive storage.

For large column types like TEXT, BLOB, and JSON, databases generally store the value “out of band”, as a file on disk with a pointer to the file in the actual table structure. A different strategy, popularized by Postgres, is to examine the size of the value and store small values in the table structure while preserving the files and pointers strategy for large values. This strategy allows the user to be less disciplined about sizing VARCHAR columns and just use TEXT instead. It’s also a big performance win for these types when the values are small.

Dolt 2.0 has adaptive storage making MySQL databases that use TEXT, BLOB, GEOMETRY, or JSON columns a good fit regardless of whether they need version control or not.

Conclusion#

Dolt 2.0 is here. It’s kinder to your disk and it’s fast. Questions? Stop by our Discord and just ask.

WASHINGTON, D.C. — Donald Trump called an impromptu press conference in front of the White House this week to deliver a life-changing message to actor Mark Hamill, revealing that he was, in reality, the actor’s father.

The actor was reportedly reluctant to accept the invitation to appear at the press conference but sensed something deep within himself that made him feel compelled to be present.

"Search your feelings, Mark, you know it to be true," Trump said while extending his hand toward Hamill. "George Lucas never told you what happened to your father."

Hamill recoiled in fear, somehow knowing what was next. "He told me enough," he said. "He told me you’re basically Hitler and that you’re destroying democracy. We have to stop you."

"No. I am your father, Trump explained.

"No… no… that’s not true," Hamill sobbed. "That’s impossible!"

"It’s true. It’s a beautiful thing, maybe the best fatherhood in the history of families. Many people are saying it," Trump answered.

"NOOOOOOOOOOOOOO! NO!" the actor then shouted as members of the media looked on.

"This is a great opportunity, Mark," Trump continued as he adjusted his red power tie. "You can destroy the Left. The Democrats have foreseen this. Join me, and together we can make America great again as father and son."

Hamill was later seen fleeing the press conference and was unavailable for comment.

At publishing time, Trump also announced that he had ordered the United States military to destroy all copies of any Star Wars movies made after Return of the Jedi, a move that skyrocketed his popularity with Republicans and Democrats alike.

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Every hour a racist loses hope, will you help the Southern Poverty Law Center to help a racist in need?

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Laravel ClickHouse is a database driver that integrates ClickHouse with Laravel, including Eloquent, the Query Builder, Schema Builder, and more:

• Eloquent models with non-incrementing ID support
• Query Builder with ClickHouse-specific clauses (i.e.,FINAL, ARRAY JOIN, SAMPLE)
• Schema Builder with ENGINE, PARTITION BY, ORDER BY, and LowCardinality column types
• Laravel migration support via artisan migrate
• Concurrent query execution using Guzzle’s async HTTP pool
• Dual HTTP transport options: Guzzle and Curl/phpclickhouse

ClickHouse is an open-source column-oriented database built for analytical workloads. It stores data by column rather than by row, making aggregations over large datasets fast—capable of querying billions of rows in seconds. It’s a common choice for event tracking, time-series data, and analytics dashboards where read performance at scale is the priority.

Eloquent Models

You can define Eloquent models pointing at ClickHouse the same way you would for any other database connection:

class Event extends Model
{
 protected $connection = 'clickhouse';
}
 
$events = Event::where('user_id', 1)->get();

ClickHouse doesn’t use auto-incrementing primary keys, so the driver configures models with non-incrementing IDs by default. Scopes and collections work as expected.

Query Builder with ClickHouse Extensions

The Query Builder covers standard Laravel methods and adds ClickHouse-specific clauses. The final parameter applies the FINAL modifier to a query, which forces ClickHouse to merge duplicate rows at read time—useful with the ReplacingMergeTree engine:

$events = DB::connection('clickhouse')
 ->table('events', final: true)
 ->where('user_id', 1)
 ->get();

Other extensions include PREWHERE (ClickHouse’s pre-filter for primary key columns), ARRAY JOIN, SAMPLE, LIMIT BY, and SEMI/ANTI/ASOF join types.

Schema Builder and Migrations

The Schema Builder supports ClickHouse DDL via a ClickHouseBlueprint, letting you define table engines, partition keys, order keys, and column types like LowCardinality:

Schema::connection('clickhouse')->create('events', function (ClickHouseBlueprint $table) {
 $table->engine('MergeTree()');
 $table->orderBy(['id', 'created_at']);
 $table->partitionBy('toYYYYMM(created_at)');
});

Standard artisan migrate commands work with a ClickHouse-compatible migration repository, so you can manage schema changes alongside your other databases.

Concurrent Query Execution

The package includes a Parallel helper that runs multiple queries at the same time using Guzzle’s async HTTP pool:

$results = Parallel::get([
 'users' => User::where('active', 1),
 'events' => Event::where('type', 'click'),
]);

Both users and events execute concurrently, and the results are returned as a keyed array once all queries resolve.

You can find the full documentation and source on GitHub.

EAST OF EDEN — After discovering the horrific murder of their son Abel, Adam and Eve sat down to compile a comprehensive list of possible suspects.

Declaring the case to be a real "whodunit," the first man and woman puzzled long into the night as to who could be the killer.

"Think, Adam, think. Who else could it be?" said Adam, staring at his list. "Don’t get in a rush here. Leave no stone unturned. We’re going to solve this riddle and catch the killer, whoever it may be. I didn’t do it. And I asked Eve, and she said it wasn’t her. That does narrow it down somewhat."

The couple reportedly spent several hours brainstorming potential culprits, such as "rogue fig tree" and "very aggressive breeze," before coming up with their exhaustive list of people who could have perpetrated the heinous act.

"We’re following all the clues," said Eve. "I feel like we’re getting close now. We’ll start the interview process soon and begin gathering clues. It may help to draw an outline on the ground of where the body was when we found it. I think we’re finally starting to get to the bottom of this enigma."

At publishing time, the couple had begun wondering who they could select to serve on an impartial jury.

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California transplants Steve and Timpani try to be the perfect Texas hosts for Brittuni’s visit, but Steve quickly realizes he needs a sensible vehicle now that he’s about to become a dad.

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