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EDB Postgres AI
Experience zero data sprawl with EDB Postgres AI. Capable of handling 30B+ trades a day and managing 50 TB.
Most cited
Posts that commenters keep linking to, ranked by how many different people have cited them in Hacker News comments. 21 posts.
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Amazon’s Consumer Business Turned Off Final Oracle Database
Over my 17 years at Amazon, I have seen that my colleagues on the engineering team are never content to leave good-enough alone. They routinely re-evaluate every internal system to make sure that it is as scalable, efficient, performant, and secure as possible. When they find an avenue for improvement, they will use…
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We Can Do Better Than SQL
The questions we often hear are "Why create a new query language?" and "What's wrong with SQL?". This blog post contains answers to both.
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Keeping Open Source Open – Open Distro for Elasticsearch
中文版 – At AWS, we focus on solving problems for customers. Over the years, customer usage and dependencies on open source technologies have been steadily increasing; this is why we’ve long been committed to open source, and our pace of contributions to open source projects – both our own and others’ – continues to…
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Sqlite 3.30.0
This page provides a high-level summary of changes to SQLite. For more detail, see the Fossil checkin logs at https://sqlite.org/src/timeline and https://sqlite.org/src/timeline?t=release . See the chronology a succinct listing of releases.
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Pyodide: Bringing the scientific Python stack to the browser
Pyodide is an experimental project from Mozilla to create a full Python data science stack that runs entirely in the browser. We think it’s worthwhile to work on moving the ...
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Building columnar compression in a row-oriented database
Read how we built a flexible, high-performance columnar compression mechanism for PostgreSQL to add scalability to our favorite database.
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Hedge funds use satellite images to beat Wall Street
Berkeley Haas research finds there may be a dark side to the rise of “alternative data” in capital markets While Assoc. Prof. Panos Patatoukas was discussing Walmart in his Financial Information Analysis course last year, a student brought up the story of how company founder Sam Walton used to count cars in store…
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Microsoft acquires Citus Data (YC S11)
Data and analytics are increasingly at the center of digital transformation, with the most leading-edge enterprises leveraging data to drive customer acquisition and satisfaction, long-term strategic planning, and expansion into net new markets. This digital revolution is placing an incredible demand on technology…
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Reducing the Performance Gap of Intel's MKL on AMD Threadripper
In this post I'm going to show you a simple way to significantly speedup Python numpy compute performance on AMD CPU's when using Anaconda Python.
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Building CockroachDB on top of RocksDB
CockroachDB uses RocksDB for its storage engine because of RocksDB's rich feature set, which is necessary for a complex product like a distributed SQL database.
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Jepsen: YugaByte DB 1.3.1
2019-09-05: YugaByte’s blog post states YugaByte DB “passes Jepsen tests”. We feel obligated to state that YugaByte DB’s Jepsen test suite does not pass, though it may in the future. Race conditions in YugaByte DB’s schema system can cause correctness errors. For example, inserting rows into a freshly-created table…
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The New York Times course to teach its reporters data skills is now open-source
And how your reporters can learn to love spreadsheets, too
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FoundationDB Record Layer
Today, we are excited to announce the open source release of the FoundationDB Record Layer!
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Why Julia
it's faster than other scripting languages, allowing you to have the rapid development of Python/MATLAB/R while producing code that is as fast as C/Fortran
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How We Built a Vectorized SQL Engine
Using vectorized processing in an execution engine makes more efficient use of modern CPUs by changing the data orientation (from rows to columns) to get more out of the CPU cache and deep instruction pipelines by operating on batches of data at a time.
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Jepsen: TiDB 2.1.7
In 2010, Google engineers Daniel Peng & Frank Dabek published Large-scale Incremental Processing Using Distributed Transactions and Notifications , which described Percolator: a Google-internal database for random access transactional workloads where low latencies are not required. Percolator uses a global…
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The Empty Promise of Data Moats
Data has long been lauded as a competitive moat for companies, and that narrative’s been further hyped with the recent wave of AI startups. Network effects have been similarly promoted as a defensible force in building software businesses. So of course, we constantly hear about the combination of the two: “data…
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Apache Arrow Flight: A Framework for Fast Data Transport
This post introduces Arrow Flight, a framework for building high performance data services. We have been building Flight over the last 18 months and are looking for developers and users to get involved.
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CockroachDB's Consistency Model
CockroachDB's consistency model fits somewhere between serializability and linerarizability. We're proposing a new marketing phrase for CRDB's guarantees: no stale reads.