Today we are revealing the Next Big Thing for DuckDB: Quack, a protocol that turns DuckDB into a client-server database.
True to DuckDB's philosophy, Quack is simple and fast. Setting it up takes seconds, and it works for both bulk operations and small write transactions.
🔗 duckdb.org/quack
Why the Zig programming language matters, when to use it, and why correctness is a system design problem, not a language problem. Interesting thoughts from @joran.tigerbeetle.com.
tigerbeetle.com/blog/2025-10...#ziglang
In 2018, “Protocol-Aware Recovery” set the standard for Durability in ACID, making Prof. Ram Alagappan and Aishwarya Ganlat giants in the field.
TigerBeetle is grateful, not only to stand on their shoulders, but to support their ongoing work.
siebelschool.illinois.edu/news/Alagapp...
TripleZip (YC W25), now processing commercial rent transactions with TigerBeetle.
Congrats, Grayson and Yash, on going into production! We're cheering for you.
Yes, it was really interesting to learn that TigerBeetle was inspired by research out of UW–Madison on storage faults.
I’ve also heard great things about their database group.
Thoroughly enjoying the IronBeetle series on YouTube about how @tigerbeetle.com works. There are some very interesting ideas behind it and they are well explained
How to add rate limiting to your API using TigerBeetle, including how to capture/visualise with #grafana
Thanks for this great post, @mcadariu.bsky.socialdev.to/mcadariu/how...
As announced on the Systems Distributed 25 website, TigerBeetle has generously donated 8k USD to ZSF.
Thank you Joran & team for both the donation and for hosting a conference of rare quality.
This is from a 40 year old textbook:
The database should guarantee durability under the weakest possible system assumptions.
That includes hardware corruption, yet no mainstream database today cares about it. Most just assume hardware is sound. (TigerBeetle is an exception)
TigerBeetlex 0.16.47 now includes structs and functions to decode TigerBeetle CDC events streamed on RabbitMQ.
Bonus material: a guide to create a pipeline to process them in ~50 LOC, powered by Broadway.
hexdocs.pm/tigerbeetlex...#weBEAMTogether@elixir-lang.org#ziglang@tigerbeetle.com
Okay we're done with Benchmarking. Bringing up the whole Tigerbeetle team to take bows. Calling out the individual work each person did on the benchmarking demo and the conference.
Picture of the vs screen, though I think it loses a bit without the animations and the music
(oh hey the lights turned yellow because the last race is with DuckDB)
They plan to release the program so you can make your own database races
Tigerbeetle also had the ability to do full replication and durability checks, since it was fast enough to afford to spend cycles on that.
That was at 10% contention. Now benchmarking 50% contention with the proprietary postgres million-dollar cluster. Gets 2 minute headstart vs tigerbeetle
I mean they had the potential to change color, they just didn't until the closing keynote.
To the beat of the synthwave.
That is playing.
What a conference, man
Aaaaaanyway that was a benchmark visualization. Postgres avged 1k tps, tigerbeetle avged 300k tps for same latency levels
client runs on separate machine. Proprietary cluster users anonymized. Missed a bit of theother benchmark details.
"The time has come to race."
Gonna replay the real performance traces for us. Showing that now for psql, plus analytic database
Again, this ONLY does OLTP. No general-purpose processing, no custom data, no user passwords or workflow state machines, just accounts and debits/credits, nothing else. Specialization gives special interfaces gives power.
Benchmark time! Every db [except cluster?] runs on i8g.16xlarge...
Tigerbeetle learns from history. While SQL is the language of databases for 5 decades, DebitCredit has been language of transactions for 5 centuries. Tailor interface for that.
We can fit 8000+ transactions in 1mb, getting a lot more work done per network round-trip.
#sd25
tbf it's not fair, because it was provided as one giant batch. Also since DuckDB is OLAP it doesn't have any durability or high-availability. Just shows that if we can avoid locks, we can process many more transactions.
Benchmark #4: Tigerbeetle (duh). True OLTP, nothing BUT transactions.
So benchmark is adapted to look like an analytics workload, just for fun.
DuckDB hits 2k transactions/sec for 0% contention. 10% contention: 2k t/s. 90% contention: 2k t/s. 90% with 10ms roundtrip: 2k t/s.
No performance degradation because no row locks.
Write contention is what separates OLTP from OLGP. At 10% contention, the proprietary cluster never goes above 12% cpu utilization.
What about stored procedures? Keep processing in a single in-process transaction without row locks!
Benchmark #3: DuckDB.
Kinda ill-suited, as DuckDB is OLAP
#sd25
They'll benchmark the "cluster" on 16 machines that cost 84k/month total, or 1m/year.
Instead of 12k transactions/sec under 0% contention, got 7.5k transactions/sec, a little better than half (for a million dollars a year). 10% contention: 570 t/s. 8 machines: 600 t/s. 1 machine: 800 t/s!
"Those who would trade safety for performance deserve neither safety nor performance."
What if we use a CLOUD database? They give UNLIMITED* INFINITE* SCALE*
These often have the same interface as postgres, but as a proprietary cluster. "Looks like / talks like Postgres", runs on many machines
Amdahl's law is a killer. That, plus network times, give hard limits to how fast a truly general db can process transactions under high contention. Many engineers give up, believing we either need "correct but not fast" or "fast but not correct".
"No. Give me serializable or give me death!"
#sd25
For low contention, 10k transactions/sec. For high contention, gradually drops to 4 transactions/sec
(I was closest!)
Postgres super sensitive to network costs: 10ms roundtrips more than 10x worse than 1ms roundtrips. Needs to do row locks across 2 roundtrips, which creates bottlenecks.
To transfer money from alice to bob, psql first gets their balanes, then adds to alice's debits and bob's balance, then writes an (alice, bob, amnt) record to the transfers table.
Will take somewhere between 1 and 10 roundtrips.
"How many transactions/sec?"
I guessed 2
We're going to benchmark four databases. "Before we use interfaces to unlock performance, we will use them to LOCK performance".
First db, Postgres, OLGP (online general purpose). Have to build out transfers as a general relational table. #sd25
Example: 14mm people tried to get tickets for Oasis, and they sold out in minutes. Pareto principle: 80% of volume involves 20% of power users.
Transactions are not complex queries. Rather, simpler queries but lots of them. In some fields, up 10000x volume since 2015.
DebitCredit is "rewrite account, write history, rewrite teller, rewrite *branch*." Branch is a "hot account", adding in contention. It's possible, with hot accounts like a company account, for upwards of 90% of transactions to have contention. Can't handle big scale without handling contention.
Standard interface is SQL ∪ over network ∪ trasnsaction processing. "No OLGP or OLAP", specifically ultra-high volume transactions, OLTP in the most restricted sense.
Inventor of OLTP Jim Grey proposed in 1985 three benchmarks: scan, sort, and DebitCredit. kicked off optimization race.
#sd25
"We're gonna do a challenge. We're gonna take one of the most valuable workloads in the world today and show that popular database have a performance limit, and this comes from the interface, not implementation", meaning adding more hardware won't improve the limit. Then we'll fix the limit.
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"1000x: The Power of an Interface for Performance", Joran Dirk Greef, #sd25
"A million dollars, 16 machines, a race" between good implementations and a good interface. Interfaces expose, and impose, and play a profound influence on how well systems scale.
Still buzzing from Systems Distributed '25
Every talk, every chat, every moment was exceptional. From start to finish, the best conference I've ever attended
Massive thanks to the speakers, the attendees, and the team at @tigerbeetle.com for making this event unforgettable
The opening talk of #systemsdistributed, organized by our friends @tigerbeetle.com in the Eye Film museum in Amsterdam, was given by @hannes.muehleisen.org of
@duckdb.org about:
DuckLake (ducklake.select)
and this was very well received
movie poster refers back to CIDR2025 😄
DuckLake: leverage DB tech for Data Lake metadata.
works on duckdb, postgres, MySQL & SQLite
provides:
- multi-statement &
multi-table transactions
- SQL views
- delta queries
- encryption
- low latency: no S3 metadata &
inlining: store small inserts in-catalog
and more!
Greetings from #sd25! It's a two-day single-track conference hosted by
@tigerbeetle.com. I'll be aiming to liveskeet as many of the talks as I can. Super excited to be here!
systemsdistributed.com
And a proof to myself that I made it here…finally, after 2y of struggle to attend…still feels surreal 🙏 #SystemsDistributed
Finally meeting the legends @joran.tigerbeetle.com@dominiktornow.bsky.social and the amazing Tigerbeetle crew!
When the best of low-level performance optimization techniques have all failed, and with both hands tied...
@joran.tigerbeetle.com will deconstruct/reconstruct one of the world's most popular interfaces, to show the power of an interface for performance.
We trust our systems to store acknowledged writes, serve them up later, and isolate transactions from one another. But can we really trust them?
How three unconventional systems ensure (or violate!) key safety properties, with @aphyr.woof.group.ap.brid.gy
A new #Jepsen report! We worked with TigerBeetle to find seven crashes, elevated latencies during single-node failures, and requests which were retried forever in version 0.16.11. We found only two safety issues: missing results for queries with multiple predicates, and incorrect timestamps in a […]
Tired of software relicensing and BSL, but don't know how to navigate it? Joran Dirk Greef of TigerBeetle has a very interesting take youtube.com/watch?v=Z0kz...
This is preaching to the choir, but I'm sure there's a great podcast episode here, nudge nudge @bcantrill.bsky.social@ahl.bsky.social