Blogs by: Kannan Muthukkaruppan

Yugabyte Raises a $30 Million Series B

Yugabyte Raises a $30 Million Series B

It is my pleasure to announce that Yugabyte has raised $30 million in an oversubscribed Series B funding round led by 8VC, with participation from Wipro Ventures and existing investors, Lightspeed and Dell Technologies Capital. Bhaskar Ghosh from 8VC joins our board of directors along with Scott Yara, formerly of Greenplum and Pivotal Software. We are truly excited to partner with Bhaskar Ghosh and the dynamic team at 8VC,

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Welcome Bill Cook as Yugabyte’s New CEO

Welcome Bill Cook as Yugabyte’s New CEO

I’m excited to welcome Bill Cook to the team as the new CEO of Yugabyte! Bill is an extraordinary leader with an exemplary record of building and scaling enterprise infrastructure companies. Bill joins us from Pivotal Software where, as co-founder and President, he was part of the leadership team that helped solidify the company as the gold standard in cloud native software development and led Pivotal through its IPO and subsequent merger with VMware in 2019.

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Announcing YugabyteDB 1.2 and Company Update

Announcing YugabyteDB 1.2 and Company Update

The team at YugaByte is excited to announce that YugabyteDB 1.2 is officially GA! You can download the latest version from our Quick Start page.

New in 1.2: YugaByte SQL Beta 3

YugaByte SQL (YSQL) is our PostgreSQL v11 compatible, distributed SQL API. It is ideal for powering microservices that require low latency, internet scale, geographic data distribution and extreme resilience to failures but want the data modeling flexibility of SQL (joins,

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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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YugaByte Announces Kubernetes StatefulSets Support to Enable Scale-Out PostgreSQL Deployments

YugaByte Announces Kubernetes StatefulSets Support to Enable Scale-Out PostgreSQL Deployments

YugaByte is excited to be at KubeCon today to announce Kubernetes StatefulSets support for our distributed SQL API which complements the transactional NoSQL APIs already generally available. YSQL is YugabyteDB’s PostgreSQL-compatible Distributed SQL API (currently in Beta). This new feature, available in YugabyteDB 1.1.7, cloud-native applications and microservices can rely on SQL and NoSQL to take full advantage of Kubernetes StatefulSets to power horizontally scalable, highly fault-tolerant data services,

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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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Benchmarking an 18 Terabyte YugabyteDB Cluster with High Density Data Nodes

Benchmarking an 18 Terabyte YugabyteDB 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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