YugabyteDB

Enhancing RocksDB for Speed & Scale

Enhancing RocksDB for Speed & Scale

As described in our previous post “How We Built a High Performance Document Store on RocksDB?”, YugabyteDB’s distributed document store (DocDB) uses RocksDB as its per-node storage engine. We made multiple performance and data density related enhancements to RocksDB in the course of embedding it into DocDB’s document storage layer (figure below). These enhancements are distributed as part of the YugabyteDB open source project. The goal of this post is to deep dive into these enhancements for the benefit of engineering teams interested in leveraging RocksDB beyond its original design intent of a fast monolithic key-value store.

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7 Issues to Consider When Evaluating FoundationDB

7 Issues to Consider When Evaluating FoundationDB

FoundationDB enjoys a unique spot in the transactional NoSQL space given its positioning as a basic key-value database that can be used to build new, more application-friendly databases. Given that many of the guarantees provided by its core engine (such as multi-shard ACID transactions and high fault tolerance) are similar to those provided by the YugabyteDB database, our users often ask us for a comparison. These users are essentially trying to understand whether they should build their app directly using one of the three YugabyteDB APIs or should they explore/build a new database layer on FoundationDB first.

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Distributed Backups in Multi-Region YugabyteDB Clusters

Distributed Backups in Multi-Region YugabyteDB Clusters

Our post Getting Started with Distributed Backups in YugabyteDB details the core architecture powering distributed backups in YugabyteDB. It also highlights a few backup/restore operations in a single region, multi-AZ cluster. In this post, we perform distributed backups in a multi-region YugabyteDB cluster and verify that we achieve performance characteristics similar to those observed in a single region cluster.

We configured a 9 node cluster with 3 availability zones across 2 regions and repeated the benchmark introduced in the post.

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Getting Started with Distributed Backups in YugabyteDB

Getting Started with Distributed Backups in YugabyteDB

YugabyteDB is a distributed database with a Google Spanner-inspired strongly consistent replication architecture that is purpose-built for high availability and high performance. This architecture allows administrators to place replicas in independent fault domains, which can be either availability zones or racks in a single region or different regions altogether. These types of multi-AZ or multi-region deployments have the immediate advantage of guaranteeing organizations a higher order of resilience in the event of a zone or region failure.

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Are MongoDB’s ACID Transactions Ready for High-Performance Applications?

Are MongoDB’s ACID Transactions Ready for High-Performance Applications?

MongoDB’s “schemaless” JSON data modeling was initially attractive to web app developers looking to escape the constraints of traditional relational databases, but issues with data durability and ACID transactions have been a consistent challenge. While the recent MongoDB 4.0 release includes multi-document transaction support, this post explores where the platform falls short for transactional, high performance apps.

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YSQL Architecture: Implementing Distributed SQL in YugabyteDB

YSQL Architecture: Implementing Distributed SQL in YugabyteDB

In this post, we will look at the architecture of YSQL, the PostgreSQL-compatible distributed SQL API in YugabyteDB. We will also touch on the current state of the project and the next steps in progress. Here is a quick overview:

  • YugabyteDB has a common distributed storage engine that powers both SQL and NoSQL
  • For supporting NoSQL apps, YugabyteDB is designed for low latency, sub-millisecond reads and massive write scalability. It can handle millions of requests and many TBs of data per node with linear scalability and high resilience.

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