More indexes. More caching. More replicas.
#SingleStore Flow moves heavy analytics off your #MySQL or #Postgres while it keeps running.
⚡️ 1.5TB Postgres in <2 hrs
⚡️ 75TB MySQL in a week
https://t.co/RZg2viVFhy
Running Postgres for transactions, a warehouse for analytics and a separate vector store for AI features means three systems to sync? SingleStore from @singlestoredb is one distributed SQL database for transactions, analytics and vector search (IVF, HNSW, PQ). It has a freemium tier and ingests from Kafka, S3 and HDFS. It also speaks the MySQL and MongoDB wire protocols via SingleStore Kai.
$2.8M a year. That’s the gap between two data architectures, and a third of it never showed up on an invoice. 👀
Kevin Ng breaks down the hidden costs in your data stack 🔗 https://t.co/8ULDDq9m5E
Your business has an Aura. Can you read it?
That was Ed Hsu’s question to execs in Tribeca.
AI fails without context.
Aura Intelligence senses, decides, and acts in real time.
People ask. Agents act.
🔗https://t.co/5GydeSxXWQ
#AuraIntelligence#SingleStore
Models are getting smarter. Your data is getting… older. 👀
That tension was the main course at our Stockholm exec dinner 🇸🇪: real-time context, fragmented data, and scaling without complexity.
Tack så mycket to Mo Kheir, Hans Bak, Micah Bhakti & everyone who joined.
When underground pressure shifts, seconds matter.
Watch Lola Dove use #AuraIntelligence to ask a drilling rig one question, "Is the well kicking?", and get an answer in plain English, backed by live data. #singlestore
🔗 https://t.co/19QFXQHLqA
Smart AI. Stale data. Wrong answer.
Models reason better than ever. Doesn't matter if they're reasoning about yesterday.
That's the "last inch" problem: where enterprise AI quietly breaks.
This month's What's in Store closes it 👇
https://t.co/Qap6u5x4b2
#AI#RealTimeData
"Correctness is not something a better model can supply. It is a property of where context lives." — @SingleStoreDB CEO @RajVermaCEO
🔗 https://t.co/05xs304IZP
Memory errors on every node. Obvious checks came up empty.
Our new Observability Agent found the real cause in about 2 minutes.
It wasn't what anyone expected. 👇
https://t.co/a5C3kRw6ce
“Hey AI, show me a football.”
🏈
In London. 🤔
Technically right. Contextually useless.
Paying to rephrase it—or use a bigger model—is token maxxxxing.
AI needs your business context. That starts with your database.
#BigDataLDN saw it. Now you do. 👇
Give agents the context they need up front, so more of their time and tokens go toward useful work.
See how Context Engine works 👉https://t.co/FF1ze0Jo8g
#LTAP is new? 🤔
SingleStore unified transactions + analytics years ago.
But sure. Why would anyone deceive you?
Check the facts 👉 https://t.co/vd96fpC59o
@databricks says AI agents broke a 40-year-old database rule.
SingleStore broke it in 2019.
Transactions + analytics. One database. Live data. No pipelines. No stale copies.
AI didn’t create the need. It exposed it.
https://t.co/GMo0HNSITe
"The same analysis would have taken my team two weeks."
One of our first SingleStore Analyst customers — answered in minutes, on live data. No pipeline, no ticket.
Context + concurrency + real-time access, one engine.
👉 https://t.co/07ymyyCDcc
Agents are bad at joins. Databases aren't.
Stop making AI guess at relationships between disconnected systems. Let the database do the join — then give AI context it can trust.
See how Aura works 👉 https://t.co/OC63ZxmQzi
Your AI is only as real-time as the data underneath it.
One engine. Streaming, transactions, analytics, search, AI.
Less movement. Less waiting. More intelligence.
→ https://t.co/R9vDNowP5a