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Introducing Workers KV
In 1864 British computer pioneer Charles Babbage described the first key-value store to be used as part of his Analytical Engine.
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How I slashed a SQL query's runtime with two Unix commands
I was trying to run a simple join query on MariaDB (MySQL) and its performance was horrendous. Here’s how I cut down the query’s run time from over 380 hours to under 12 hours by executing part of it with two simple Unix commands.
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The hacker's guide to uncertainty estimates
I made a New Year's resolution: every plot I make during 2018 will contain uncertainty estimates. Nine months in and I have learned a lot, so I put together a summary of some of the most useful methods.
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What they don’t tell you about event sourcing
Event sourcing and CQRS gained a lot of popularity recently. The advantages are obvious and they share a very peculiar symbiosis with the…
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Predicting Stock Performance with Natural Language Deep Learning
We developed an NLP deep learning model using a one-dimensional convolutional neural network to predict future stock market performance of companies using Azure ML Workbench and Keras with open source for you to replicate.
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GitLab is working on a tool just for data teams
Meltano is an open source tool for the entire data science lifecycle, and we want your contributions and feature requests!
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Jepsen: MongoDB 3.6.4
MongoDB is a long-time user of Jepsen . Over the past three years, Jepsen has performed several analyses for MongoDB, and MongoDB has integrated an expansive Jepsen test suite into their CI system. In March, MongoDB requested Jepsen perform an analysis on a previously untested configuration: sharded clusters. We also…
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Caching Beyond RAM: The Case for NVMe
memcached
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Anna: A Fast, Scalable, Flexibly Consistent Key-Value Store
There’s fast and there’s fast. This post is about Anna*, a key/value database design from our team at Berkeley that’s got phenomenal speed and buttery smooth scaling, with an unpr…
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Archive.org and California to start a data sharing and preservation project
Research and cultural heritage institutions are facing increasing costs to provide long-term public access to historically valuable collections of scientific data, born-digital records, and other digital artifacts. With many institutions moving data to cloud services, data sharing and access costs have become more…
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A Missing Link in Postgres 11: Fast Column Creation with Defaults
How a seemingly minor enhancement in Postgres 11 fills one of the system’s biggest operational holes.
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A new storage engine for PostgreSQL to provide better control over bloat
In the past few years, PostgreSQL has advanced a lot in terms of features, performance, and scalability for many-core systems. However, o...
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AWS Outperforms GCP in the 2018 Cloud Report
Customers rely on us to help navigate the increasingly competitive cloud wars. This inspired the 2018 Cloud Report, a benchmark of AWS and GCP on performance, latency, CPU, network, I/O, and cost.
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PostgreSQL 11 and Just in Time Compilation of Queries
PostgreSQL 11 includes a new component in the execution engine: a JIT expression compiler. A benchmark comparison shows up to 29.31% speed improvements in PostgreSQL 11 using the JIT expression compiler, executing TPC-H Q1 at scale factor 10 in 20.5s instead of 29s when using PostgreSQL 10.
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Scaling a High-Traffic Rate Limiting Stack with Redis Cluster
Flattening a single very hot vertical Redis node into a horizontal Redis Cluster at Stripe.
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Stream and Go: News feeds for 300M users, built on RocksDB and Raft
Discover the tech stack used by Stream. Explore 42 tools across 5 categories.
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Datomic: Event Sourcing without the hassle
When I got started using the Datomic database, I remember someone describing it to me as 'Event Sourcing without the hassle'. Having built Event Sourcing systems both with and without Datomic, I think this is very well put, although it might not be obvious, especially if you don't have much experience with Datomic.
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Truth First, or Why You Should Mostly Implement Database-First Designs
In this much overdue article, I will explain why I think that in almost all cases, you should implement a “database first” design in your application’s data models, rather than a …