YugabyteDB for Python (Django) app can achieve high availability (HA) and handle a cloud outage. To demonstrate this, we will simulate an outage in Google Cloud Platform (GCP) on one of the Yugabyte database nodes to see how YugabyteDB handles the downtime.
Category: Google Cloud Platform
The evolution of “build once, run anywhere” containers and Kubernetes—a cloud-agnostic, declarative-driven orchestration API—have made a scalable, self-service platform layer a reality. Even though it is not a one size fits all solution, a majority of business and technical challenges are being addressed. Kubernetes as the common denominator gives scalability, resiliency, and agility to internet-scale applications on various clouds in a predictable, consistent manner. But what good is application layer scalability if the data is still confined to a single vertically scalable server that can’t exceed a predefined limit?
At the Distributed SQL Summit 2020, Travis Logan – CTO & Co-Founder at Justuno, presented the talk, “Evolve: A Database Journey from Ground to Cloud.”
With over 14 years of experience with Microsoft SQL Server, Travis is well-versed in the evolution of transactional databases. In this talk he summarizes his experiences with traditional RDBMS while trying to improve their redundancy, scaling characteristics, and performance.
At the Distributed SQL Summit 2020, James Hartig – Co-Founder at Admiral, presented the talk “How Admiral Scales Globally with YugabyteDB on Google Cloud While Maintaining Single-Digit Latency.”
Admiral’s Go application runs in Google Cloud across 5 regions in 3 continents. This geo-distributed architecture is powered by a single YugabyteDB cluster that delivers an average global read latency of 3ms! In this talk,
Justuno provides a Conversion Rate Optimization (CRO) Platform that enables e-commerce sites to turn visitors into customers through personalized onsite messaging, intelligent cross-selling, and upselling. More than 188,000 (and counting) industry leading brands improve sales and the customer experience at the same time.
At the heart of the Justuno platform is visitor intelligence data, and there’s a lot of it. Justuno tracks between 30 and 50 data points per visitor–such as time on site,
Remote Joins in Hasura GraphQL extend the concept of joining data across tables, to being able to join data across tables and remote data sources. In this blog post we are going to demonstrate this capability by configuring the following set up.
- A 3 node YugabyteDB cluster running on GKE with a Hasura GraphQL Engine attached
- A 3 node YugabyteDB cluster running on AKS with a Hasura GraphQL Engine attached
- A Remote Schema and Remote Relationship configured
- The ability to issue GraphQL queries that join data from two different databases,
Hasura is one of the leading vendors in the GraphQL ecosystem. They offer an open source engine that connects to your databases and microservices, and then auto-generates a production-ready GraphQL backend. GraphQL is a query language (more specifically a specification) for your API, and a server-side runtime for executing queries by using a type system you define for your data. GraphQL is often used for microservices, mobile apps, and as an alternative to REST.
Java developers know that Spring Data makes it easy to use data access technologies, relational and non-relational databases, map-reduce frameworks, and cloud-based data services. When YugabyteDB is combined with Spring, Java developers are able to leverage their familiarity with PostgreSQL while gaining the added benefits of Distributed SQL. These “out-of-the-box” benefits include geo-data distribution, high performance, and horizontal scalability, which are impossible or difficult to achieve with monolithic SQL databases. To demonstrate just how easy it is to get started with Spring and YugabyteDB,
Liquibase is an open source and extensible change management project that supports a variety of databases including Snowflake, MySQL, and PostgreSQL via JDBC. Liquibase allows users to easily define changes in SQL, XML, JSON, and YAML. These changes are then managed in a version control system so the changes can be documented, ordered, and standardized. For more information on the features and benefits of Liquibase, check out their documentation site.
SQLPad is an MIT licensed web app written in React and Node.js for writing and running SQL queries and visualizing the results. SQLPad supports PostgreSQL, MySQL, SQL Server, Crate, Vertica, Presto, SAP HANA, Cassandra, Snowflake, Google BigQuery, SQLite, and many more via ODBC. Because YugabyteDB is PostgreSQL compatible, most third-party tools and apps will work “out of the box.” SQLPad is no exception here.
In this blog post we’ll show you how to:
- Install a 3 node YugabyteDB cluster on Google Kubernetes Engine
- Build the sample Northwind database
- Build and configure SQLPad
- Start the required SQLPad processes
- Launch the SQLPad UI and issue a test query to validate the deployment
New to distributed SQL or YugabyteDB?