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How to Geo-Partition Data in Distributed SQL

We are excited to announce the availability of row-level geo-partitioning in YugabyteDB, a feature heavily requested by our user community and enterprise customers alike. This feature allows fine-grained control over pinning data in a user table (at a per-row level) to geographic locations, thereby allowing the data residency to be managed at the database level.

Making the nodes of a multi-region database cluster aware of the location characteristics of the data they store allows conforming to regulatory compliance requirements such as GDPR by keeping the appropriate subset of data local to different regions, and is arguably the most intuitive way to eliminate the high latency that would otherwise get incurred when performing operations on faraway, remote regions.

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How-To: YugabyteDB 2.5 Security Features

The YugabyteDB 2.5 release adds many critical enterprise-grade security features. This blog post outlines these newly added features.

Authentication

Adding scram-sha-256 Authentication

The first notable addition is the addition of a much improved, password-based authentication mechanism called Salted Challenge Response Authentication Mechanism (or simply SCRAM) as described in RFC5802. This scram-sha-256 authentication mechanism, identical to the most secure PostgreSQL authentication schema, is a challenge-response scheme that prevents password sniffing on untrusted connections and supports storing passwords on the server in a cryptographically hashed form that is thought to be secure. To enable this feature, simply pass the following flag when starting the yb-tserver.

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SQL Puzzle: Partial vs Expression Indexes

Here is an intriguing SQL puzzle we came across in the context of a real-world use case. This post shows the power of advanced RDBMS features such as partial indexes and expression indexes.

Let us assume we have a table in PostgreSQL named users, where each row in the table represents a user. The table is defined as follows.

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4 Data Sharding Strategies for Distributed SQL Analyzed

A distributed SQL database needs to automatically partition the data in a table and distribute it across nodes. This is known as data sharding, and it can be achieved through different strategies, each with its own tradeoffs. In this post, we will examine various data sharding strategies for a distributed SQL database, analyze the tradeoffs, explain the rationale for which of these strategies YugabyteDB supports, and what we picked as the default sharding strategy.

What is YugabyteDB? It is an open source, high-performance distributed SQL database built on a scalable and fault-tolerant design inspired by Google Spanner. Yugabyte’s SQL API (YSQL) is PostgreSQL wire compatible.

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The Effect of Isolation Levels on Distributed SQL Performance Benchmarking

This cottage has a high isolation level.


You may also like: SQL Server Tips and Techniques for Database Performance Optimization

The general perception is that benchmarks published by vendors can never be trusted; however, well-run benchmarks absolutely have their place, even if performed by a vendor. Benchmarks are well-run when the input parameters to the benchmarked systems match the needs of the target workloads included in the benchmark. The target workloads for the benchmark in question are simple inserts and secondary indexes served with high performance, massive scale and ACID guarantees.