Optimizing SQL indexing involves carefully considering the column order, understanding index scan ranges, and leveraging the index scan capabilities of your database to ensure efficient query performance. Discover how you can do this effectively by following the steps laid out in this new ‘How to’ guide.
DBAs often need to generate SQL statements using SQL queries and then execute them. PostgreSQL has many features that can help. Let’s walk through an example using YugabyteDB, which is Postgres-compatible and provides the same SQL language and catalog views.
It’s a common misconception that NewSQL and distributed SQL databases are the same. They’re not. Even though they’re both an evolution in the transactional database, there are significant differences. Distributed SQL adoption is growing because companies face new challenges that cannot be easily addressed with NoSQL, SQL, or NewSQL databases. Let’s look at five of them.
We are excited to announce that Yugabyte has closed $188 million in oversubscribed Series C funding. Sapphire Ventures led the round with participation from Alkeon Capital, Meritech Capital, and Wells Fargo Strategic Capital, as well as existing investors Lightspeed Venture Partners, 8VC, Dell Technologies Capital, Wipro Ventures, and others. This round comes seven months after our previous round in March 2021,
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In this blog post, you’ll learn how to implement a timer for multi-statement operations using SQL with YugabyteDB or PostgreSQL. These tools are commonly used for various tasks, but their native timing feature only times individual SQL statements and doesn’t support end-to-end timing or output to spool files.
Triggers are a basic feature that all monolithic SQL systems like Oracle, SQL Server and PostgreSQL have supported for many years. They are very useful in a variety of scenarios ranging from simple audit logging, to advanced tasks like updating remote databases in a federated cluster. In this blog, we’ll look at examples of INSERT, UPDATE and INSTEAD OF triggers in Yugabyte DB.
What’s Yugabyte DB? It is an open source, high-performance distributed SQL database built on a scalable and fault-tolerant design inspired by Google Spanner.
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At last month’s KubeCon + CloudNativeCon in Seattle, the single biggest change from previous container-related conferences was the excitement among the end user companies around their adoption of Kubernetes and the associated cloud native infrastructure ecosystem. The CNCF End User Community page today lists 50+ enterprises and 21+ case studies including those from industry bellwethers such as Capital One, Netflix, Nordstrom and Pinterest. There is a common adoption pattern among all these case studies —
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This post aims to help application developers understand the choice of SQL vs. NoSQL in the context of the data modeling needs of an application.
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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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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