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How YugabyteDB Scales Temenos’ Cloud Platform to 100K Business Transactions Per Second

Last week, Temenos made a major announcement – the Temenos Banking Cloud is achieving 100,000 transactions per second and running on a greener and more scalable platform.

Specifically, this has been a three-month project with multiple vendors, and YugabyteDB has had a significant role in the project’s success.

So, what does their benchmark of 100 million customers and 200 million deposit accounts with 100,000 transactions per second and 61 transactions per second per core mean for the database and business users?

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Fine-Grained Control for High Availability: Increasing Node Failure Threshold

The purpose of this blog post is to show how you can increase the failure threshold when a node goes down, which happens for a variety of reasons including hardware or network issues and most commonly maintenance. The failure threshold is the amount of time YugabyteDB would wait, after a node goes down, for it to potentially come back up. After reaching this threshold the physical data will begin to move from the dead node to other nodes in the cluster.

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Measuring the Performance Impact of TLS Encryption Using TPC-C

Organizations need to protect their data, especially the personal data entrusted to them from their users and customers. In order to do so, the data transferred by a database over the network needs to be secure. This is often accomplished using TLS encryption, an encryption protocol that secures communication across a network. When secured by TLS, a communication between a client and a server can enable the two parties to identify one another (preventing any impersonation),

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How We Learned to Stop Guessing and Love Low P-Values

“I don’t think it’s quite fair to condemn the whole program because of a single slip up, sir.” Famous last words from Kubrick’s 1964 classic Dr. Strangelove, as a forlorn general realizes his negligence is about to lead to nuclear apocalypse, may feel relatable to any engineer who has immediately regretted pushing the big red “release” button only to later find themselves putting out fires late into the night. Sometimes the answer is simply “write more tests!” or “write better tests!”,

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TPC-C Benchmark: 10,000 Warehouses on YugabyteDB

We are excited to announce that the TPC-C benchmark implementation for YugabyteDB is now open source and ready to use! While this implementation is not officially ratified by the TPC organization, it closely follows the TPC-C v5.11.0 specification.

For those new to TPC-C, the aim of the benchmark is to test how a database performs when handling transactions generated by a real-world OLTP application. This blog post shows the results of running the TPC-C benchmark in addition to outlining our experience of developing and running a TPC-C benchmark against YugabyteDB.

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Bringing Truth to Competitive Benchmark Claims – YugabyteDB vs CockroachDB, Part 2

In part 1 of this blog series, we highlighted multiple factual errors in the Cockroach Labs analysis of YugabyteDB. In this second post we provide the next layer of detail behind YugabyteDB’s architecture, with an emphasis on comparing it to that of CockroachDB’s.

Contents of this post

TLDR

Yugabyte SQL is based on a reuse of PostgreSQL’s native query layer.

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Achieving 10x Better Distributed SQL Performance in YugabyteDB 2.1

When starting the YugabyteDB project, our founding thesis was to build a high-performance distributed SQL database for the cloud native era. Achieving high performance will always remain an ongoing initiative, especially when additional optimizations are required to support new features and new use cases. We are excited that the current YugabyteDB 2.1 release has a number of improvements that make Yugabyte SQL’s performance 10x better on average than the previous 2.0 release (from September 2019).

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How YugabyteDB Scales to More than 1 Million Inserts Per Sec

There are a number of well-known experiments where eventually-consistent NoSQL databases were scaled out to perform millions of inserts and queries. Here, we do the same using YSQL, YugabyteDB’s PostgreSQL-compatible, strongly-consistent, distributed SQL API. We created a 100-node YugabyteDB cluster, ran single-row INSERT and SELECT workloads with high concurrency – each for an hour and measured the sustained performance (throughput and latency). This post details the results of this experiment as well as highlights the key aspects of the YugabyteDB architecture that makes it fit for such high-volume ingest workloads.

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The Effect of Isolation Levels on Distributed SQL Performance Benchmarking

This post addresses a concern raised about a benchmarking result we recently published comparing the performance of YugabyteDB, Amazon Aurora and CockroachDB. It was pointed out that we unfairly used the default isolation level for each database rather than use serializable isolation level in all databases (even though serializable level was not required for these workloads). In addition, we are also happy to share additional results with the workloads run at YugabyteDB’s serializable isolation level.

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Comparing Distributed SQL Performance – YugabyteDB vs. Amazon Aurora PostgreSQL vs. CockroachDB

Update: A new post “The Effect of Isolation Levels on Distributed SQL Performance Benchmarking” includes performance results from running these workloads at serializable isolation level in YugabyteDB.

We are excited to announce the general availability of YugabyteDB 2.0 this week! One of the flagship features of the release was the production readiness of the PostgreSQL-compatible YugabyteDB SQL (YSQL) API. In this blog post, we will look at the performance and scalability of YSQL as compared to two other PostgreSQL-compatible distributed SQL databases –

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