The YugaByte Database Blog

Thoughts on open source, cloud native and distributed databases

YugaByte Database Engineering Update – Nov 27, 2018

Lots has happened since our last engineering update about 3 months ago. Below are some of the highlights.

PostgreSQL API Updates & PostgresConf Silicon Valley Wrap-Up

We have made a lot of progress on YSQL, the PostgreSQL compatible distributed SQL API for YugaByte DB! You can also read about YSQL architecture which covers how distributed SQL is implemented in YugaByte DB.

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Distributed Backups in Multi-Region YugaByte DB Clusters

Our post Getting Started with Distributed Backups in YugaByte DB details the core architecture powering distributed backups in YugaByte DB. 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 YugaByte DB cluster and verify that we achieve performance characteristics similar to those observed in a single region cluster.

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Getting Started with Distributed Backups in YugaByte DB

YugaByte DB 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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Technical Deep Dive into YugaByte DB 1.1

We announced the general availability of YugaByte DB 1.1 earlier this week. You can download the latest version for your OS or use our default container image as documented in our Quick Start page.

YugaByte DB is an open source database for high performance applications that require ACID transactions and planet-scale data distribution.

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Benchmarking an 18 Terabyte YugaByte DB Cluster with High Density Data Nodes

For ever-growing data workloads such as time series metrics and IoT sensor events, running a highly dense database cluster where each node stores terabytes of data makes perfect sense from a cost efficiency standpoint. If we are spinning up new data nodes only to get more storage-per-node, then there is a significant wastage of expensive compute resources. However, running multi-terabyte data nodes with Apache Cassandra as well as other Cassandra-compatible databases (such as DataStax Enterprise) is not an option.

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YugaByte Company and Database Update – Aug 3, 2018

$16 Million Funding Round

In case you missed the news earlier this Summer, YugaByte raised an additional $16M of funding from Dell Technologies Capital and our previous investor Lightspeed Venture Partners. With the additional funding, we are accelerating investments in engineering, sales, and customer success to scale our support for enterprises building business-critical applications in the cloud.

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Yes We Can! Distributed ACID Transactions with High Performance

ACID transactions are a fundamental building block when developing business-critical, user-facing applications. They simplify the complex task of ensuring data integrity while supporting highly concurrent operations. While they are taken for granted in monolithic SQL/relational DBs, distributed NoSQL/non-relational DBs either forsake them completely or support only a highly restrictive single-row flavor (see sections below). This loss of ACID properties is usually justified with a gain in performance (measured in terms of low latency and/or high throughput).

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Achieving Sub-ms Latencies on Large Datasets in Public Clouds

One of our users was interested to learn more about YugaByte DB’s behavior for a random read workload where the data set does not fit in RAM and queries need to read data from disk (i.e. an uncached random read workload).

The intent was to verify if YugaByte DB was designed well to handle this case with the optimal number of IOs to the disk subsystem.

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Scaling YugaByte DB to Millions of Reads and Writes

Here at YugaByte, we continuously push the limits of the systems we build. As a part of that, we ran some large cluster benchmarks to scale YugaByte DB to million of reads and writes per second while retaining low latencies. This post goes into the details about our 50 node cluster benchmark. We posted the results of the benchmark on a 25 node cluster in our community forum.

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Building a Strongly Consistent Cassandra with Better Performance

In an earlier blog on database consistency, we had a detailed discussion on the risks and challenges applications face in dealing with eventually consistent NoSQL databases. We also dispelled the myth that eventually consistent DBs perform better than strongly consistent DBs. In this blog, we will look more closely into how YugaByte DB provides strong consistency while outperforming an eventually consistent DB like Apache Cassandra.

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