Time-series Databases

Vol. 18 No. 6 – November-December 2020

Time-series Databases

Always-on Time-series Database: Keeping Up Where There's No Way to Catch Up:
A discussion with Theo Schlossnagle, Justin Sheehy, and Chris McCubbin

What if you found you needed to provide for the capture of data from disconnected operations, such that updates might be made by different parties at the same time without conflicts? And what if your service called for you to receive massive volumes of data almost continuously throughout the day, such that you couldn't really afford to interrupt data ingest at any point for fear of finding yourself so far behind present state that there would be almost no way to catch up?

by Theo Schlossnagle, Justin Sheehy, Chris McCubbin

Baleen Analytics:
Large-scale filtering of data provides serendipitous surprises.

Data analytics hoovers up anything it can find and we are finding patterns and insights that weren't available before, with implications for both data analytics and for messaging between services and microservices. It seems that a pretty good understanding among many different sources allows more flexibility and interconnectivity. Increasingly, flexibility dominates perfection.

by Pat Helland

The Non-psychopath's Guide to Managing an Open-source Project:
Respect your staff, learn from others, and know when to let go.

Transitioning from one of the technical faithful to one of the hated PHBs (pointy-haired bosses), whether in the corporate or the open-source world, is truly a difficult transition. Unless you are a type who has always been meant for the C-suite?, it's going to take a lot of work and a lot of patience, mostly with yourself, to make this transition. Doing something "for the good of (blank)" usually means you are sublimating your own needs to the needs of others, and if you don't acknowledge that, you are going to get smacked and surprised by your own reactions to people very, very quickly.

by George V. Neville-Neil

Best Practice: Application Frameworks:
While powerful, frameworks are not for everyone.

While frameworks can be a powerful tool, they have some disadvantages and may not make sense for all organizations. Framework maintainers need to provide standardization and well-defined behavior while not being overly prescriptive. When frameworks strike the right balance, however, they can offer large developer productivity gains. The consistency provided by widespread use of frameworks is a boon for other teams such as SRE and security that have a vested interest in the quality of applications. Additionally, the structure of frameworks provides a foundation for building higher-level abstractions such as microservices platforms, which unlock new opportunities for system architecture and automation. At Google, such frameworks and platforms have seen broad organic adoption and have had a significant positive impact.

by Chris Nokleberg, Brad Hawkes

Let's Play Global Thermonuclear Energy:
It's important to know where your power comes from.

For us to grow and progress as a civilization, we need more investment in providing electricity to the world through clean, safe, and efficient processes. Thermonuclear energy is a huge step forward. This article is mostly focused on the use cases around grid-scale reactors. It's hard to see a future without some sort of thermonuclear energy powering all sorts of things around us.

by Jessie Frazelle

Enclaves in the Clouds:
Legal considerations and broader implications

With organizational data practices coming under increasing scrutiny, demand is growing for mechanisms that can assist organizations in meeting their data-management obligations. TEEs (trusted execution environments) provide hardware-based mechanisms with various security properties for assisting computation and data management. TEEs are concerned with the confidentiality and integrity of data, code, and the corresponding computation. Because the main security properties come from hardware, certain protections and guarantees can be offered even if the host privileged software stack is vulnerable.

by Jatinder Singh, Jennifer Cobbe, Do Le Quoc, Zahra Tarkhani

Offline Algorithms in Low-Frequency Trading:
Clearing Combinatorial Auctions

Expectations run high for software that makes real-world decisions, particularly when money hangs in the balance. This third episode of the Drill Bits column shows how well-designed software can effectively create wealth by optimizing gains from trade in combinatorial auctions. We'll unveil a deep connection between auctions and a classic textbook problem, we'll see that clearing an auction resembles a high-stakes mutant Tetris, we'll learn to stop worrying and love an NP-hard problem that's far from intractable in practice, and we'll contrast the deliberative business of combinatorial auctions with the near-real-time hustle of high-frequency trading. The example software that accompanies this installment of Drill Bits implements two algorithms that clear combinatorial auctions.

by Terence Kelly