Dolt
Dolt is a version-controlled SQL database — branch, merge, diff, and time-travel your data the way you do your code.
Dolt earns its place if your team already reviews changes before they land. The workflow is genuinely the one you know: branch from main, experiment, read the diff, merge through a pull request. Doltgres hitting 1.0 matters most right now — Postgres shops get branch-and-merge on data without switching protocols, and multi-dimensional array support landed in September 2026. DumboDB's Replication V1 gives MongoDB users a versioned destination rather than a rewrite. Skip it for plain high-frequency OLTP with no audit requirement; the versioning overhead buys you nothing there. If you only need point-in-time recovery, Neon-style branching or snapshot backups may be the lighter call.
Verified 4d ago · liveness 67/100 · cite: rightaichoice.com/tools/dolt
- Data teams that already review changes through pull requests
- Regulated and analytics teams needing reproducible queries at a past commit
- Developers fluent in Git who want the same workflow on SQL tables
- PostgreSQL shops evaluating Doltgres after its 1.0 release
- High-frequency OLTP workloads where nobody inspects commit history
- Teams with no version control experience and no appetite for merge semantics
- Projects needing drop-in full PostgreSQL compatibility without extension testing
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Skip Dolt if your workload is high-frequency OLTP and nobody on the team will ever open a diff or ask what a row looked like last Tuesday — the versioning overhead buys you nothing there.
Versioning every change means history accumulates, so storage grows with write volume in a way a plain database's does not — budget for it on write-heavy tables.
Dolt's core database, DoltHub's public hosting, and DoltLab self-hosting are open source and free, which makes the entry point cheaper than most versioned-data or managed-Postgres options. Private DoltHub databases and Hosted Dolt are quoted custom, so cost scales with how much managed infrastructure you hand over. If you only need branching for ephemeral dev environments, a clone-based Postgres workflow may be cheaper than a full versioned engine.
In short
Dolt — Dolt is a version-controlled SQL database — branch, merge, diff, and time-travel your data the way you do your code. Best for Data teams that already review changes through pull requests, Regulated and analytics teams needing reproducible queries at a past commit, Developers fluent in Git who want the same workflow on SQL tables. Free to use.
What's new in Dolt
Checked 4 days agoAcross the latest 5 updates: 4 feature updates and 1 news mention.
PostgreSQL Database Clones vs. Doltgres Branches: When Are Clones Enough?
DoltHub compares PostgreSQL 18 database clones with Doltgres branches and lays out when a clone-based workflow is sufficient and when a branch is the better fit.
DumboDB: Introducing Merge Modes
DumboDB adds merge modes, with compare-and-swap operations now working in the MongoDB-compatible product.
Doltgres now supports multi-dimensional arrays
Doltgres added multi-dimensional array support matching Postgres behavior, closing a compatibility gap for Postgres users evaluating the 1.0 release.
Your Replica Doesn't Need to Know Everything
Dolt added MySQL-compatible wildcard table filters for binlog replication, letting a replica selectively apply row changes rather than taking everything.
DumboDB: Announcing Replication V1
Dumbo ships Replication V1, replicating updates from MongoDB into Dumbo so users can bring existing document data into a versioned store.
What people actually say about Dolt — is it worth it?
We ran a structured research pass across product reviews, community discussions, and post-purchase forum threads to surface the patterns vendors won't publish themselves. Below: the recurring strengths, the hidden costs people mention most, and the cohort that consistently regrets adopting this tool.
45 mentions across 2 sources (Hacker News, Lemmy) · researched Jul 3, 2026.
Average across the 2 sources that answered — each source counts once, not each post.
- +Full Git-style branching and merging for tables and rows.
- +MySQL-compatible — works with existing MySQL clients and tools.
- +Time-travel queries and rollback to any commit.
- +Unique pull request workflow for database changes.
- +Open source and free core with paid hosted options.
- −Reliability concerns under heavy production load.
- −Small community means fewer integrations and examples.
- −Not a drop-in replacement for MySQL in all cases.
- −Maturity: still evolving core features and edge cases.
- −Learning curve for Git-like workflows in databases.
- • Hosted Dolt pricing not publicly detailed; may surprise at scale.
- • DoltLab enterprise tier pricing undisclosed.
Viability Score
How well maintained and how widely used is Dolt? Built from what the vendor actually publishes (docs, changelog, tutorials, integrations, pricing), whether the site is live, and how much real users discuss it. How we calculate this
Last calculated: October 2026
How we score →Key Features
- Git-style version control for tables: branch, merge, diff, commit, push, pull
- dolt CLI mirrors the Git CLI command for command
- Time-travel queries as of a past commit, branch, or tag
- Rollback to any previous commit without a restore from backup
- MySQL-compatible SQL interface and client connections
- Doltgres: PostgreSQL-compatible version control, 1.0
- Doltgres multi-dimensional array support (September 2026)
- DoltLite: versioned SQLite for local-first and embedded use (beta)
- DumboDB: MongoDB-compatible versioning
- DumboDB Replication V1 replicating MongoDB updates into Dumbo
- DumboDB merge modes including compare-and-swap operations
- DumboDB RBAC, auto-commit, and validator support
- Versioned MySQL replica deployment
- MySQL-compatible wildcard table filters for binlog replication
- DoltHub: hosted public and private databases with forks and pull requests
About Dolt
Dolt is a SQL database that behaves like a Git repository. You run the same commands you already know — dolt add, dolt commit, dolt branch, dolt merge, dolt push, dolt pull — against tables instead of files, and connect with any MySQL client to write ordinary SQL. Because history is stored in the engine, you can query data as of a past commit, branch, or tag, and roll a table back to a known-good state without a restore from backup. Change review works like code review: make changes on a branch, inspect the diff, and merge through a pull request. The ecosystem now spans several protocols. Dolt itself is the MySQL-compatible core and is at 2.0. Doltgres carries the same version-control semantics to PostgreSQL and is at 1.0, with multi-dimensional array support added in September 2026. DoltLite is a versioned SQLite for local-first and embedded use and remains in beta. DumboDB covers MongoDB compatibility, shipping Replication V1 and merge modes (including compare-and-swap operations) in September 2026. Hosting and tooling run alongside: DoltHub for hosted public and private databases, DoltLab as the self-hosted DoltHub, Hosted Dolt as a managed service, and Dolt Workbench as a desktop SQL workbench with Agent Mode for AI-assisted schema exploration and query writing. Dolt can also be deployed as a versioned MySQL replica, so you can add branching and history to a MySQL you already run rather than migrating everything at once. This is for data teams that want audit trails, reproducible queries, and pull requests on relational data — not for high-frequency OLTP where nobody will ever ask what changed.
Behind the Verdict
The interesting thing about Dolt is where the version control lives. It is not a layer bolted onto a database that watches for changes — branching, diffing, and merging are properties of the storage engine, and the SQL interface is a standard one, so your existing MySQL tooling, drivers, and ORMs keep working. That is the difference between Dolt and the collection of products that clone a database volume on a schedule. The practical consequence is that the unit of review becomes a change to data, not a file. You can branch from main, mutate rows, run a diff that shows exactly which cells moved, and merge through a pull request with a reviewer attached. Because history is queryable, you can also ask what a table looked like as of a commit or a tag — useful when a number has to be reproduced exactly as it was reported months ago. The migration story is unusually gentle. Dolt speaks MySQL, Doltgres speaks Postgres, DoltLite speaks SQLite, and DumboDB speaks MongoDB. Dolt can additionally run as a versioned MySQL replica, so you can attach versioning to a database you already operate instead of moving it. The September 2026 release of MySQL-compatible wildcard table filters for binlog replication is a good example of the ecosystem maturing toward real production topologies rather than demos — replicas can now selectively apply row changes. Where it strains. Versioning everything means storing everything, so plan for storage growth proportional to how much you change. High-frequency transactional workloads pay a tax for history they will likely never read. DoltLite is still beta, and Doltgres, now at 1.0, is young enough that you should test the Postgres extensions you depend on rather than assume parity. Non-technical teammates face a real learning curve: merge conflicts on data are conceptually harder than merge conflicts on text, and the tool will not resolve a semantic conflict for you. Benchmarks and Metrics exist, and BranchBench now measures agentic SQL workflows, but you should run your own workload before committing. Hosted Dolt and DoltHub carry the collaboration surface — forks, clones, pull requests, a web GUI for browsing commit history — while DoltLab puts the same thing inside your network so data never leaves. If your team already argues about pull requests on application code, extending that argument to the tables underneath is a small conceptual step and a large operational one.
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Real-world workflow fit
Concrete scenarios for the personas Dolt actually fits — and what changes day-one when you adopt it.
You branch from the production database, rewrite a transformation that has been producing wrong totals, run a diff to confirm exactly which rows shift, and open a pull request.
Outcome: A reviewer sees the row-level diff before anything reaches main, and the merge is recorded in the same history you can time-travel back to.
You point Dolt at your existing MySQL as a versioned replica rather than migrating, then query the replica as of a past commit to debug an incident.
Outcome: You get branch and history capability without touching the application's connection string or rewriting schema.
You host the dataset on DoltHub, accept a contributor's fork, review their changes in a pull request, and merge the accepted rows.
Outcome: Public contribution works the way open source code does, with attribution and a full commit history on every cell.
Use Cases
- Branch from production data, experiment safely, and merge the result back through a pull request.
- Roll a table back to any past commit to undo a bad migration instead of restoring from backup.
- Reproduce a historical report by querying data as of the commit that produced it.
- Clone a database into development, testing, or CI/CD pipelines with full history attached.
- Deploy Dolt as a versioned MySQL replica to add branching and diffs to an existing MySQL.
- Fork an open dataset on DoltHub, edit it, and submit a pull request to the maintainers.
- Version MongoDB documents with DumboDB while keeping SQL-like queries and RBAC.
- Embed DoltLite for a local-first application that needs versioned, file-based data.
Limitations
- Dolt assumes you know Git concepts and SQL.
- Versioning all history increases storage use, and merge semantics on data have a real learning curve for non-technical teammates.
- DoltLite is still beta, and Doltgres only reached 1.0 in August 2026, so its ecosystem is young — test the Postgres extensions you depend on rather than assuming parity.
- High-frequency OLTP workloads can see overhead from versioning they will never read.
- DumboDB is younger still and adding capabilities release by release, so treat it as maturing rather than settled.
as of 2026-10-04
Verification history
We have re-verified Dolt 9 times since . Each pass re-reads the vendor's own pages and re-checks every listed field against that evidence; passes where nothing had changed are marked as such.
- — re-verified summary, description, our verdict, our analysis, pricing model, pricing tiers, features, integrations, who it suits, who should skip it
- — re-verified summary, description, our verdict, our analysis, pricing model, pricing tiers, features, integrations, who it suits, who should skip it
- — re-verified summary, description, our verdict, our analysis, pricing model, pricing tiers, features, integrations, who it suits, who should skip it
- — re-verified summary, description, our verdict, our analysis, pricing model, pricing tiers, features, integrations, who it suits, who should skip it
- — re-verified summary, description, our verdict, our analysis, pricing model, pricing tiers, features, integrations, who it suits, who should skip it
- — re-verified summary, description, our verdict, our analysis, pricing model, pricing tiers, features, integrations, who it suits, who should skip it
Showing the 6 most recent of 9 verification passes.
Free to cite with attribution — this page re-verifies continuously.
12-month cost
Project the real annual outlay, including the implied monthly cost when only an annual tier is published.
Vendor list price only. Add-on usage, seat overages, and contract minimums are surfaced under Hidden costs & gotchas.
Plans compared
For each published Dolt tier: who it actually fits, and what it adds vs. the previous tier. Cross-reference the cost calculator above for projected annual outlay.
Dolt (Open Source)
$0/mo
Ideal for
Engineers who want to try branch, diff, and merge on real tables locally before committing a team to it.
What this tier adds
Starting tier: the versioned MySQL-compatible database itself, free and open source, with time-travel and rollback included.
DoltHub (Public Databases)
$0/mo
Ideal for
Open data publishers and anyone sharing a dataset that contributors should be able to fork and improve.
What this tier adds
Adds cloud hosting and the pull request workflow on top of the free database, for databases you make public.
DoltLab (Self-Hosted)
$0/mo
Ideal for
Regulated or security-constrained teams that want DoltHub's collaboration features but cannot let data leave their network.
What this tier adds
Same fork-and-pull-request collaboration as DoltHub, deployed on your own infrastructure with your own branding.
DoltHub (Private Databases)
Custom
Ideal for
Teams collaborating on private datasets who want hosted forks and pull requests without running infrastructure.
What this tier adds
Private cloud-hosted databases with access controls, beyond what the free public hosting covers.
Hosted Dolt
Custom
Ideal for
Teams building a production application on Dolt or Doltgres who would rather not run the servers.
What this tier adds
Fully managed deployments with Dolt engineers on call and a REST API documented by an OpenAPI contract.
Where the pricing makes sense
The company stage and team size where Dolt's pricing actually pencils out — and where peers do it cheaper.
Dolt's core database, DoltHub's public hosting, and DoltLab self-hosting are open source and free, which makes the entry point cheaper than most versioned-data or managed-Postgres options. Private DoltHub databases and Hosted Dolt are quoted custom, so cost scales with how much managed infrastructure you hand over. If you only need branching for ephemeral dev environments, a clone-based Postgres workflow may be cheaper than a full versioned engine.
Setup time & first value
How long it actually takes to get something useful out of Dolt — broken out by persona, not the marketing-page minute.
Installing the Dolt CLI and connecting a MySQL client takes minutes — if you know Git, the commands map one to one. Attaching Dolt to an existing MySQL as a versioned replica is an afternoon of configuration. Standing up DoltLab on your own infrastructure is a real deployment project, not a quick install, and should be scoped as one.
Switching to or from Dolt
How to bring data in from common predecessors and how to get it back out — written for the switcher, not the buyer.
- →From MySQL: run Dolt as a versioned MySQL replica to add branching and diffs without migrating the application.
- →From Git-managed schema files: import the schema into Dolt and let the database itself track changes going forward.
- →From PostgreSQL: move to Doltgres, which keeps Postgres-compatible SQL and adds branch, diff, and merge.
- →From MongoDB: use DumboDB, which now supports Replication V1 to bring MongoDB updates into a versioned store.
- →From flat files: import CSV, JSON, or Parquet and commit the result as the first revision.
- ↗To plain MySQL: dump the current revision and load it into MySQL, accepting that commit history is left behind.
- ↗To PostgreSQL: export schema and data into Postgres if you only needed the versioning temporarily.
- ↗To snapshot backups: replace branch-and-merge with scheduled volume snapshots if you never actually read the diffs.
- ↗To a managed Postgres with branching: evaluate clone-based workflows if your need is ephemeral dev copies rather than a reviewed history.
Integrations
Resources & Guides
Tutorials & Learning
YouTube returned 6 videos for “Dolt”, and we withheld 6: 6 could not be judged, because “Dolt” is a single word that other videos use for other things. We are showing none, because we could not prove any of them are about Dolt.
Official links
Tools that pair well with Dolt
Common stack mates teams adopt alongside Dolt, with the specific reason each pairing earns its keep.
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Chat2DB
Chat2DB is an open-source AI SQL client that turns plain English into queries across 40+ database engines, with query execution kept on your machine.
Featured Head-to-Head Comparisons
Dolt vs Spider Cloud
Choose Spider Cloud if you need fast, AI-friendly web scraping with structured output at low cost. Choose Dolt if you need Git-like version control for your SQL database, enabling branching, merging, and audit trails. They serve completely different needs; your decision hinges on whether you need to extract web data or version your own data.
Dolt vs Screenplayiq
ScreenplayIQ and Dolt serve entirely different domains, so the choice depends on your role. ScreenplayIQ is ideal for screenwriters and producers who want data-driven script feedback and box office estimates. Dolt is a must-have for data teams needing version control for databases, with recent updates improving performance and PostgreSQL compatibility. If you're a data professional, Dolt wins; if you're in film, ScreenplayIQ is the pick.
Dolt vs Temporal Ai
Choose Temporal AI if you need rock-solid orchestration for long-running, failure-prone AI agents or microservices — its durable execution is unmatched. Choose Dolt if your pain point is versioning and collaborating on data itself, not code; it's a drop-in MySQL with Git workflows. They solve different problems: Temporal orchestrates processes; Dolt versions data. Your choice hinges on whether your primary need is workflow reliability or data historization.
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BlazeSQL
BlazeSQL turns plain-English questions into SQL answers, dashboards, and reports from your existing database.
Frequently Asked Questions
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