July 2020 Summaries

Liquibase is an open-source change management project that supports various databases, including Snowflake, MySQL, and PostgreSQL via JDBC. It allows users to easily define changes in SQL, XML, JSON, and YAML formats, which are then managed in a version control system for documentation, ordering, and standardization. In this tutorial, we'll demonstrate how to install YugabyteDB on Google Kubernetes Engine (GKE), create a sample Northwind database, install and configure Liquibase, create a simple changeset, verify the results, manage changes, and issue a second changeset. Distributed SQL databases are becoming popular for their ability to reduce TCO or move away from horizontal scaling limitations of monolithic RDBMS. YugabyteDB is an open-source, high-performance distributed SQL database built on Google Spanner's scalable and fault-tolerant design. It provides automatic distributed query execution, strongly consistent replication, and distributed ACID transactions. With Liquibase, changes to the Northwind database can be easily managed, tracked, and deployed, ensuring data consistency and integrity.

SQLPad is an open-source web application that allows users to write, run, and visualize SQL queries on various databases, including YugabyteDB, PostgreSQL, and others. This tutorial guides readers through setting up a 3-node YugabyteDB cluster on Google Kubernetes Engine (GKE), building the Northwind database, configuring SQLPad, and connecting to the YugabyteDB cluster using the SQLPad UI. The tutorial covers the basics of Distributed SQL databases, which are becoming popular for cloud-native environments, and introduces readers to YugabyteDB, a PostgreSQL-compatible distributed SQL database built on Google Spanner's design principles. By following this tutorial, users can gain hands-on experience with SQLPad and YugabyteDB, exploring their capabilities and potential applications in various industries.

The TPC-C benchmark has been implemented for YugabyteDB, a distributed relational database, allowing users to test its performance when handling transactions generated by real-world OLTP applications. The results show that YugabyteDB demonstrates linear scalability in terms of support for larger numbers of warehouses without compromising high efficiency. The benchmark was run with 10, 100, 1000, and 10,000 warehouses on a single zone of AWS, achieving tpmC values of 12,590 and 125,194 respectively. This is equivalent to 97.90% and 97.35% of the theoretical maximum tpmC value. The benchmark also highlights the importance of sharding and connection pooling in scaling the tool to handle larger numbers of warehouses.

Distributed SQL databases are becoming popular with organizations interested in moving data infrastructure to the cloud or cloud native environments, motivated by reducing TCO or moving away from horizontal scaling limitations of monolithic RDBMS. YugabyteDB is an open source, high-performance distributed SQL database built on a scalable and fault-tolerant design inspired by Google Spanner, offering deep integration with GraphQL projects and advanced RDBMS features like stored procedures, triggers, and UDFs. YugabyteDB provides equivalents to Oracle's IDENTITY and PostgreSQL's SERIAL columns, handling Oracle's NUMBER and PostgreSQL's DECIMAL and NUMERIC data types, and converting Oracle's TIMESTAMP WITH TIME ZONE datatype to UTC, all while maintaining permissive licenses under Apache 2.0 for itself and similar licenses for PostgreSQL. New documentation, blogs, tutorials, and videos have been published to support the release of YugabyteDB 2.2, covering topics such as transactional distributed backups, online index builds, deferred constraints, colocated tables, and benchmarking using TPC-C. Upcoming events include webinars and a conference on cloud native databases.

Porting the Oracle Tutorial sample database to YugabyteDB involves running a series of scripts that create the necessary schema and populate it with data. The process requires modifications to the original Oracle script to accommodate YugabyteDB's differences, including changes to user roles, schema references, data types, and constraints. The scripts are run in a specific sequence, starting with creating the user, then the schema, followed by loading the data, and finally creating the constraints. After running the scripts, the database can be tested using SQL commands, such as listing tables, describing a table, and executing queries to verify that the data has been successfully loaded. The process requires attention to detail and an understanding of YugabyteDB's features and limitations compared to Oracle.

YugabyteDB provides a distributed SQL database that allows users to identify colocated databases, increment counters in MAP collections, and manage limits in YCQL collections. To export data from a table that is still receiving inserts, users can use `ysql_dump` with the `--serializable-deferrable` option. YugabyteDB has also released new documentation, blogs, tutorials, and videos to support its version 2.2 release. Upcoming events include webinars on what's new in YugabyteDB 2.2, SQL basics, cloud-native topics, geo-distributed SQL databases, and KubeCon + CloudNativeCon Europe 2020 Virtual. The database allows users to get started quickly with a local installation by visiting the quickstart page.

YugabyteDB 2.2 is now generally available, offering several new features to improve its usability and performance. The release includes fully-transactional distributed backups, online index builds, deferred constraints for foreign keys, colocated tables for reducing JOIN latency, TPC-C results, yugabyted server for single-node clusters, and more. These features aim to make distributed SQL easy to use even in demanding enterprise environments. Additionally, the release is a significant step forward for YugabyteDB's community engagement, with over 1300 Slack users, 4100+ GitHub stars, and a 6x increase in clusters created in the last year. The new features are designed to improve developer productivity, data resilience, geographic distribution, and performance while ensuring PostgreSQL wire compatibility.

Here's a neutral, objective, and interesting summary of the text in one paragraph: Combining GraphQL and YugabyteDB can help develop scalable APIs and services. GraphQL is a query language that allows for flexible data retrieval, while YugabyteDB is an open-source, high-performance distributed SQL database built on a scalable and fault-tolerant design inspired by Google Spanner. To set up a YugabyteDB and GraphQL environment, users can deploy a GKE cluster, create a 3-node YugabyteDB cluster, build the Northwind sample database, install Hasura GraphQL, and connect to it. Other tools like Apollo and Postgraphile can also be used with YugabyteDB for building GraphQL APIs. Users can query multiple tables in the same GraphQL query using joins, and there are three types of queries: Query, Mutation, and Subscription. Additionally, users can spin up a GraphQL API server from an existing YugabyteDB or PostgreSQL server using tools like Hasura and Postgraphile, and can access new documentation, blogs, tutorials, and videos on various platforms.

Yugabyte has recently raised $30 million in Series B funding and welcomed two new board members, marking a significant milestone in the company's growth and momentum. The company has also achieved notable community milestones, including 4,000+ GitHub stars and 100+ open source contributors. YugabyteDB Operator is now certified and available as a Beta release on Red Hat OpenShift, further solidifying its position in the market. To support this growth, Yugabyte is actively hiring for various engineering positions, with opportunities to join a talented team working towards an ambitious mission. The company values individuality, work-life balance, and inclusivity, making it an attractive option for those looking to join a dynamic and passionate organization.