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Databases · head to head

Dragonfly vs Xata

Dragonfly logo

Dragonfly

Databases

High-performance Redis-compatible in-memory datastore with 25x better throughput

From
Free
Rated
-
Full reviewWebsite
Xata logo

Xata

Databases

Apache 2.0 platform for running many Postgres instances on Kubernetes, with copy-on-write branching and scale-to-zero.

From
Free
Rated
-
Full reviewWebsite

The short version

  • Each has a real cost: Dragonfly flex tier starting at $36/month may be underpriced, requiring careful usage monitoring; Xata self-hosting means operating Kubernetes and CloudNativePG, so the Apache 2.0 licence removes the vendor bill but replaces it with a platform team, and a database platform is not something a part-time operator maintains safely.
  • They diverge on capability: Dragonfly covers Redis API compatibility, Xata covers Copy-on-write branching.
  • Prices and features above were last checked on 30 August 2026.

Where they differ

Only the attributes on which Dragonfly and Xata actually diverge.

Attributes where Dragonfly and Xata differ
AttributeDragonflyXata
Pricing modelUsage-based cloud pricing with flexible tiersusage-based
PlatformsCloud, AWS, GCP, AzureWeb

Identical on both: starting price (Free), free tier (Yes), user rating (Not yet rated), category (Databases).

What each one covers

Drawn from each product's published feature list. An absence here means we hold no record of it - not that the product lacks it.

Only in Dragonfly

  • Redis API compatibility
  • Thread-per-core architecture
  • High-performance caching
  • Memory efficiency
  • Real-time leaderboards
  • Message queue support
  • ML feature serving
  • Cloud deployment

Only in Xata

  • Copy-on-write branching
  • Scale-to-zero compute
  • Compute autoscaling and bin-packing
  • High availability with failover
  • Point-in-time recovery
  • Serverless driver
  • pgroll migrations
  • pgstream replication

What people use each for

The jobs each tool is most often brought in to do.

Dragonfly

  • High-throughput caching for web applicationsnot Xata
  • Real-time leaderboards and rankingsnot Xata
  • Message queue and event processingnot Xata
  • ML model feature serving at millisecond latenciesnot Xata
  • Gaming session state and player data storagenot Xata

Xata

  • Giving every pull request or coding agent its own branch of the production database, with real data volumes rather than a seeded fixturenot Dragonfly
  • Running managed-Postgres economics in your own cloud account where data residency or compliance rules out a third-party control planenot Dragonfly
  • Consolidating many small, mostly idle Postgres databases onto shared infrastructure where scale-to-zero and bin-packing recover the idle costnot Dragonfly
  • Testing a destructive migration against a copy of production without waiting for a full restore or paying for a duplicate of the storagenot Dragonfly

Where each one falls short

Documented limitations, not opinions. Every one is a constraint you would hit in normal use.

Dragonfly

  • Flex tier starting at $36/month may be underpriced, requiring careful usage monitoring
  • Business tier $2,000/month represents significant jump in cost
  • Limited to in-memory storage, not suitable for cold data or archival
  • Bring-your-own-cloud requirement on Business tier adds operational complexity
  • Cloud availability dependent on AWS/GCP/Azure uptime

Xata

  • Self-hosting means operating Kubernetes and CloudNativePG, so the Apache 2.0 licence removes the vendor bill but replaces it with a platform team, and a database platform is not something a part-time operator maintains safely.
  • Copy-on-write branches are cheap to create but diverge as they are written to, so a long-lived branch carrying a heavy backfill quietly accumulates real storage and the cost arrives later than the decision that caused it.
  • Scale-to-zero means the first connection after an idle period pays a cold start, which is invisible in a busy production database and very visible in a demo, a staging environment or a cron job that runs once an hour.
  • The Xata sold before 2025 was a different product, a proprietary API and SDK layered over Postgres, so tutorials, blog posts and SDK examples from that era describe something that no longer exists and existing users had to migrate.
  • As a managed service it competes with RDS, Aurora and Cloud SQL, and it is a much smaller company, so procurement, certification coverage and the depth of the support bench behind a 3am corruption incident are all weaker than the incumbent even though the underlying Postgres is the same.

Pricing, plan by plan

Dragonfly

Free
  • Free TierFree
    • 100 cloud credits for new signups
    • Equivalent to free trial
  • Business$2000/month
    • Starting price for enterprise offering
    • Bring-your-own-cloud deployment
    • Auto-scaling with custom SLAs
  • Enterprise$undefined/custom
    • Custom pricing
    • Any-cloud deployment
    • Custom instances and sizing

Xata

Free
  • Free TrialFree
    • 14 days free
    • No credit card required
  • Usage-Based$1/per 1000 branches
    • 1,000 branches for $1
    • Scale-to-zero compute model
    • Branches hibernate when idle

Which should you pick?

Choose Dragonfly if

  • You need redis api compatibility.
  • You want to start without paying.
  • You work on Cloud, AWS, GCP, Azure.
  • You also want thread-per-core architecture.
Dragonfly review

Choose Xata if

  • You need copy-on-write branching.
  • You want to start without paying.
  • You also want scale-to-zero compute.
Xata review

Questions people ask

Is Dragonfly or Xata better?
Neither clearly leads. Dragonfly starts at Free and Xata at Free, and user ratings are close enough to be indistinguishable. Choose on capability and platform support.
Which is cheaper, Dragonfly or Xata?
Dragonfly starts at Free and Xata at Free.
Does Dragonfly or Xata run on more platforms?
Dragonfly runs on Cloud, AWS, GCP, Azure. Xata runs on Web.
Can I use Dragonfly for free?
Both have a free tier, so you can try either at no cost before committing.
What is Dragonfly best used for?
Dragonfly is most often used for high-throughput caching for web applications, real-time leaderboards and rankings, message queue and event processing, ml model feature serving at millisecond latencies. Of those, high-throughput caching for web applications and real-time leaderboards and rankings are not what Xata is typically brought in for.
What can Dragonfly do that Xata cannot?
Dragonfly covers Redis API compatibility, Thread-per-core architecture, High-performance caching, Memory efficiency. Xata covers Copy-on-write branching, Scale-to-zero compute, Compute autoscaling and bin-packing, High availability with failover.

Answered from the vendors’ own pages

Dragonfly: How much faster is Dragonfly than Redis?

Dragonfly achieves 3.97M queries per second compared to Redis's 718K QPS, representing a 25x improvement. Memory efficiency is also 30% better.

Source
Xata: Is it real Postgres or a compatible reimplementation?

Real Postgres. It runs upstream Postgres instances on Kubernetes via CloudNativePG, so extensions, the wire protocol and version upgrades behave as they do anywhere else.

Dragonfly: Can I migrate from Redis to Dragonfly without code changes?

Yes. Dragonfly maintains full API compatibility with Redis and Memcached, allowing drop-in replacement with minimal to no code modifications.

Source
Xata: Can I self-host the whole thing?

Yes. The platform is Apache 2.0 and designed for self-hosting a large number of Postgres instances on your own Kubernetes. Xata Cloud is the same platform run as a service.

Xata: Does branching copy my data?

No. Branches are copy-on-write at the storage layer, so creating one is near-instant regardless of database size and storage is only consumed as the branch diverges from its parent.

Xata: Is this the same Xata I used a couple of years ago?

No. The earlier product was a proprietary database API with its own SDK and search layer. The current product is a Postgres platform, and material written for the old one does not apply.

Xata: What happens to a branch when the parent changes?

A branch is a point-in-time fork. Later changes on the parent are not propagated, so long-lived branches drift and need to be recreated rather than refreshed if you want current data.

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