Timescale

PostgreSQL and pgvector: Now Faster than Pinecone, 75% cheaper, 100% open-source. Introducing pgvectorscale, an open-source PostgreSQL extension that builds on pgvector, enabling greater performance and scalability. Here’s how pgvectorscale helps pgvector outperform specialized vector database like Pinecone: 1️⃣ StreamingDiskANN:  A new vector search index that overcomes limitations of in-memory indexes like HNSW the index on disk, making it more cost-efficient to run and scale as vector workloads grow. Inspired by the DiskANN paper from Microsoft. 2️⃣ Statistical Binary Quantization (SBQ): Developed by researchers at Timescale, this technique improves on standard binary quantization techniques by improving accuracy when using quantization to reduce the space needed for vector storage 3️⃣ Written in Rust, giving the PostgreSQL community to contribute to vector support. 📈The result? On our benchmark of 50 million Cohere embeddings (768 dimensions each), PostgreSQL with pgvector and pgvectorscale achieves 28x lower p95 latency and 16x higher query throughput compared to Pinecone for approximate nearest neighbor queries at 99 % recall, all at 75 % less cost when self-hosted on AWS EC2. We also tested it against Pinecone’s p2 high performance index, see the blog post at the end of this post for full results (spoiler: It’s just as impressive). Pgvectorscale is open-source under the PostgreSQL license and free for you to use on any PostgreSQL database for your AI projects. To get started, see the pgvectorscale github repo: https://lnkd.in/ghXj2e-U Or try it on Timescale Cloud on any new database service. Eager to learn more about pgvectorscale and how it works? Head over to our blog post with all the details: https://lnkd.in/gcMcxrVb

𝗛𝗼𝘄 𝗗𝗼𝗲𝘀 𝗣𝗲𝘁𝗮𝗯𝘆𝘁𝗲 𝗦𝗰𝗮𝗹𝗲 𝗦𝗼𝘂𝗻𝗱 𝗳𝗼𝗿 𝗬𝗼𝘂𝗿 𝗨𝘀𝗲 𝗖𝗮𝘀𝗲? 🚀 This week, Timescale announced a number of updates about how we've made PostgreSQL faster and more powerful. Our latest is "Scaling PostgreSQL to Petabyte Scale": https://lnkd.in/gu3-p5Bc The article covers how we've done that and what it means for you. Here's where you can get your free account and start scaling with Timescale today: https://lnkd.in/g9bKY8SX #timescale #databases #postgres #postgresql #timeseries #cloud

<𝙬𝙝𝙞𝙣𝙚> 𝘽𝙪𝙩 𝙋𝙤𝙨𝙩𝙜𝙧𝙚𝙎𝙌𝙇 𝙙𝙤𝙚𝙨𝙣'𝙩 𝙨𝙘𝙖𝙡𝙚... </𝙬𝙝𝙞𝙣𝙚> We've heard that concern ever since we launched Timescale 7 years ago. Our response? Yes, PostgreSQL can scale. It's not impossible, just hard—and we solved it. At first, that meant handling 100,000 metrics per second. Then, it meant storing and querying 100TB of data without losing performance. 𝗧𝗼𝗱𝗮𝘆, 𝘄𝗲'𝘃𝗲 𝘀𝗰𝗮𝗹𝗲𝗱 𝗣𝗼𝘀𝘁𝗴𝗿𝗲𝗦𝗤𝗟 𝘁𝗼 𝗼𝘃𝗲𝗿 𝟭𝟬𝟬 𝘁𝗿𝗶𝗹𝗹𝗶𝗼𝗻 𝗺𝗲𝘁𝗿𝗶𝗰𝘀—𝗺𝗼𝗿𝗲 𝘁𝗵𝗮𝗻 𝟭 𝗽𝗲𝘁𝗮𝗯𝘆𝘁𝗲 𝗼𝗳 𝗱𝗮𝘁𝗮. https://lnkd.in/gp8erJPW Our developers solve the hard problems so that you can have an easier developer experience.

📢[𝐋𝐢𝐯𝐞 𝐬𝐞𝐬𝐬𝐢𝐨𝐧] 𝐁𝐮𝐢𝐥𝐝𝐢𝐧𝐠 𝐀𝐈 𝐚𝐩𝐩𝐥𝐢𝐜𝐚𝐭𝐢𝐨𝐧𝐬 𝐰𝐢𝐭𝐡 𝐏𝐨𝐬𝐭𝐠𝐫𝐞𝐒𝐐𝐋: 𝐀 𝐛𝐮𝐬𝐲 𝐝𝐞𝐯𝐞𝐥𝐨𝐩𝐞𝐫'𝐬 𝐠𝐮𝐢𝐝𝐞 ➡️Register to attend live or get the recording: https://lu.ma/0v7nwfxd Postgres is all you need to build state of the art AI applications. Join me today for a "state of the union" of developing AI applications with PostgreSQL. For intermediate folks, you'll learn ideas and tactics for how to improve your AI application. For beginners, you'll learn enough to start building today. It's happening at 12 ET/ 9AM PT / 6PM CET (register even if you can't make it live). Here's a sneak peak of what we'll cover: #pgvector #vectorsearch #rag #aiagents #postgresql

🚨 Only 2 hours left! 🚨 🗓 Join us for Building AI Applications with PostgreSQL: A Busy Developer's Guide to discover best practices, tools, and how to avoid common pitfalls in AI development with PostgreSQL! ⏰ When: Today at 13:00 ET | 10:00 PT | 18:00 CET 🎤 Speaker: 🔥 Avthar Sewrathan, PM AI & Vector, Timescale 💡 Learn why PostgreSQL is ideal for AI and watch live demos on Search, RAG, Agents, and Text to SQL! Can’t attend live? No worries—register now to receive the recording via email. https://lu.ma/0v7nwfxd

The Timescale Engineering Team is pushing the boundaries of PostgreSQL, scaling it to store petabytes 😱 of data. And the best thing? If they can do it, so can you—with Timescale Cloud. ✨ https://lnkd.in/dXJiZ53t

Petabyte scale friends! If you're a developer curious if Timescaledb can hold your data workload, check this blog post. I'm so glad to see how Timescale mix technologies to just do more with the same lovely PostgreSQL ❤️ 🧠

Postgres at petabyte scale and ingesting almost a trillion metrics per day? 😱 Our multi-tenant Timescale Insights product is powered by a standard Timescale database service in our cloud. The exact same as our customers can use. - 800 billion metrics per day - 100 trillion metrics recorded - >1 PB of data With Timescale, build powerful applications on #PostgreSQL. 💥 But how are those storage volumes possible or cost effective? Our hybrid cloud-native storage architecture, that tiers data from our high performance row-columnar engine hyperstore, to Parquet files on bottomless, low-cost S3. And a lot of optimization went into supporting even point-queries against this S3 data as well. More on that soon!

⚖️ Scaling PostgreSQL to Petabyte Scale—All on a Single Instance ⚖️ Last year, we launched our Insights product backed by a Timescale instance, handling hundreds of terabytes of data and billions of records daily. Now, a year later, we are still using the same instance, but check out the crazy numbers below! 🧨 The Power Behind Insights Our Insights feature offers detailed query performance stats: timing, memory, I/O usage, and more. This real-time monitoring tool helps users understand their databases better, showing under-performing queries which are dragging your system down. We started out with a dozen metrics per query, but we now track over 100 to ensure even deeper analysis and optimization. 🫶The Growth As customer needs grow and more queries are run, the volume of data we ingest has skyrocketed. But thanks to Timescale’s tiered storage architecture, hypertables, compression, and continuous aggregates our instance has kept up. 📈The Numbers Last year: 🔹 350+ TB stored 🔹 100 billion metrics/day This year: 🔹 1+ PB stored 🔹 800+ billion metrics/day 🔹 100+ trillion metrics ingested since launch And, yes, all of this runs on a Timescale instance which you could deploy yourself. It’s proof that you don’t need complex setups to scale PostgreSQL—you just need the right mindset and the right tools. Learn more about scaling PostgreSQL to a petabyte scale using Timescale Cloud. 👇👇👇 https://lnkd.in/g7SYMCh5

🗣️ We're just over halfway through Timescale PostgreSQL survey, and there's still time to share your thoughts! Survey closes Sept 30th. 👉 Take the Survey https://lnkd.in/dfHrTBPN #PostgreSQL #CommunitySurvey 🐘 Aiven