January 2020 Summaries

YugabyteDB is a distributed SQL database that supports both hash and range partitioning schemes for its primary key columns. It allows users to specify the number of tablets they want a table to have, which can be done using the SPLIT INTO clause in the CREATE TABLE statement. The database also supports row-level locking options on SELECT statements, including FOR UPDATE, FOR SHARE, and FOR KEY SHARE, which can be used to lock rows retrieved by the SELECT statement. Additionally, YugabyteDB has new documentation, blogs, tutorials, and videos available, covering topics such as data sharding strategies, operational best practices, and getting started with local installs. The database is also hiring for various positions, including frontend engineers, software engineers, developer advocates, and more.

YugabyteDB 2.0.11 has been released, offering over 30 new enhancements and fixes across its YSQL API and YCQL API, as well as system improvements and platform updates, including UI changes and bug fixes for the YugabyteDB Platform. The release also includes new documentation, blogs, tutorials, and videos, showcasing the database's features and capabilities. Additionally, the company is hiring software engineers and developer advocates to join its growing team.

Distributed SQL databases were introduced in response to the limitations of NoSQL databases, which failed to provide relational data modeling with support for single-row consistency and multi-row ACID transactions. NewSQL databases were developed to address this issue, offering two distinct flavors: automated sharding on top of monolithic SQL databases and new distributed storage engines that maintain a single logical SQL database concept. Distributed SQL databases like Google Spanner and YugabyteDB are built from the ground up to exploit cloud elasticity and work on unreliable infrastructure, whereas NewSQL databases struggled with scalability and consistency in multi-zone, multi-region, and multi-cloud deployments.

The performance impact of deleting tombstones in YugabyteDB is minimal due to its LSM engine, which performs logical merges of memtables/SSTables sorted by timestamp order, and flushes only retain the latest deleted or overwritten value. YugabyteDB achieves high data density per node by using a customized RocksDB instance with block-based splitting of bloom/index data, size-tiered compactions, smart load balancing across multiple disks, efficient C++ implementation, on-disk block compression, and globally throttled compaction queues. The maximum number of rows in YugabyteDB is theoretically limited to 2^64 - 1, but a real-world limit of 20 billion rows has been achieved. New documentation, blogs, tutorials, and videos have been published, including guides for migrating databases from MongoDB to YugabyteDB and implementing PostgreSQL table functions. The company is hiring software engineers with expertise in cloud infrastructure, core database, full-stack development, and developer advocacy.

Migrating the Sakila database from MongoDB to YugabyteDB using Studio 3T involves several steps, including creating the necessary collections in MongoDB, unpacking and importing the Sakila sample database into MongoDB, setting up a local 3-node YugabyteDB cluster, exporting the data from MongoDB using Studio 3T, and executing the SQL files against YugabyteDB to rebuild the collections. The process leverages the capabilities of Studio 3T as an ETL tool, allowing for efficient migration of data between MongoDB and YugabyteDB. This approach enables developers to take advantage of the features and benefits offered by distributed SQL databases like YugabyteDB, such as auto-sharding, synchronous data replication, durable and fast writes, linearizable reads, and strongly consistent global secondary indexes.

YugabyteDB is an open source, high-performance distributed SQL database built on a scalable and fault-tolerant design inspired by Google Spanner. It's wire compatible with PostgreSQL's SQL API. YugabyteDB can be used to migrate large tables from PostgreSQL using the COPY command, which provides better performance when enabled. The durable_wal_write flag can be used to enable fsync, guaranteeing every transaction is synced to disk before considering it successful, but this comes at a performance hit. Replacing a "dead" YugabyteDB node with a new one while keeping the same IP address is possible after 15 minutes of unavailability. The yugabyted server can be used to extract dates from timestamps using functions like date() and substring(). New documentation, blogs, tutorials, and videos have been published, including guides on sharding strategies, PostgreSQL table functions, and getting started with DbSchema. YugabyteDB is hiring software engineers, developers advocates, and other roles. The database can be explored locally on a laptop and compared to other databases like CockroachDB, Google Cloud Spanner, and MongoDB.

YugabyteDB uses various data sharding strategies including algorithmic, linear hash, consistent hash, and range sharding. Algorithmic and linear hash sharding are not recommended due to their limitations and potential performance issues. Consistent hash sharding is ideal for massively scalable workloads as it distributes data evenly across nodes while maintaining an explicit mapping table. Range sharding is useful for performing range searches but can lead to scalability bottlenecks if not implemented correctly. YugabyteDB supports both consistent hash and range sharding, with hash sharding as the default, allowing users full control over how to shard their data. The choice of sharding strategy depends on the specific use case and requirements of the application.

Here is a 1-paragraph summary of the text: YugabyteDB is an open-source, high-performance distributed SQL database inspired by Google Spanner, with a PostgreSQL wire-compatible API. Users can connect to YugabyteDB from outside a Kubernetes cluster using the load balancer IP address of the corresponding service, and the database supports user-defined PostgreSQL functions. The database generates its performance graphs in Prometheus format, and users can track progress on issues like automatically splitting tablets after table creation. New documentation, blogs, tutorials, and videos have been added, including guides for getting started with DbSchema, Kafka Connect, and PostgreSQL's authentication and authorization features. Upcoming meetups and conferences include PostgreSQL Meetups and Distributed SQL Webinars.

YugabyteDB has released two new versions, 2.0.9 and 2.0.10, which together include 36 enhancements and fixes, covering improvements in both YSQL and YCQL APIs, as well as system improvements such as improved error logging and transactional DDL. The database is built on a scalable and fault-tolerant design inspired by Google Spanner and is PostgreSQL wire compatible. New documentation, blogs, tutorials, and videos have also been added, including guides for implementing PostgreSQL table functions and getting started with DbSchema and Kafka Connect YugabyteDB. Additionally, YugaByte is hiring and invites potential candidates to join their team of domain experts from leading software companies.

DbSchema is a visual database tool that supports over 40 databases from a single interface, making it an ideal choice for database developers who want to design, document, and query SQL and NoSQL databases efficiently. YugabyteDB, an open-source, high-performance distributed SQL database, can be used with DbSchema to reverse-engineer schemas, edit ER diagrams, browse data, and build queries visually without writing any code. To get started, a local YugabyteDB cluster needs to be installed and set up, followed by downloading and installing DbSchema. Once connected, users can explore the tool's features, including interactive layouts, relational data browse, random data generator, visual query builder, schema synchronization, and more. With its user-friendly interface and robust features, DbSchema offers a 15-day free trial, making it an attractive option for developers who want to streamline their database development process.

The Apache Kafka Connect Sink plugin is designed to handle the delivery of specific topic data from a Kafka instance to a YugabyteDB instance. YugabyteDB is a high-performance, distributed SQL database that supports most of PostgreSQL's functionality and is wire-protocol compatible with PostgreSQL drivers. The integration allows for simple data abstraction, flexible and scalable interactions between multiple topics and instances, and re-use customization for individual customer use cases. To get started, users can follow the provided quick start guide, prepare their environment, download the connector, configure it, and test its functionality in a distributed environment.