Apache Airflow DAGs for Migrating PostgreSQL Data to YugabyteDB
In this blog, we’ll build an Apache Airflow workflow that will migrate data between PostgreSQL and YugabyteDB.
In this blog, we’ll build an Apache Airflow workflow that will migrate data between PostgreSQL and YugabyteDB.
Choosing YugabyteDB for Apache Airflow deployments streamlines database management and enhances system reliability. Its high availability and fault tolerance features negate the need for complex failover strategies associated with PostgreSQ. In this blog you will lean how to configure Airflow to use YugabyteDB.
Team Yugabyte is excited to announce the general availability of YugabyteDB 2.1! The highlight of this release is that Yugabyte SQL (YSQL), YugabyteDB’s PostgreSQL-compatible API, has not only improved performance 10x since the 2.0 release in September 2019 but is also production ready for multiple geo-distributed deployment scenarios. For those of you who are new to distributed SQL, YugabyteDB is a Google Spanner-inspired, cloud native distributed SQL database that is 100% open source.
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When starting the YugabyteDB project, our founding thesis was to build a high-performance distributed SQL database for the cloud native era. Achieving high performance will always remain an ongoing initiative, especially when additional optimizations are required to support new features and new use cases. We are excited that the current YugabyteDB 2.1 release has a number of improvements that make Yugabyte SQL’s performance 10x better on average than the previous 2.0 release (from September 2019).
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Welcome to this week’s tips and tricks blog where we recap some distributed SQL questions from around the Internet. We’ll also review upcoming events, new documentation, and blogs that have been published since the last post. Got questions? Make sure to ask them on our YugabyteDB Slack channel, Forum, GitHub, or Stackoverflow. Ok, let’s dive right in:
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Welcome to this week’s tips and tricks blog where we recap some distributed SQL questions from around the Internet. We’ll also review upcoming events, new documentation and blogs that have been published since the last post. Got questions? Make sure to ask them on our YugabyteDB Slack channel, Forum, GitHub or Stackoverflow. Ok, let’s dive right in:
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Welcome to this week’s tips and tricks blog where we recap some distributed SQL questions from around the Internet. We’ll also review upcoming events, new documentation and blogs that have been published since the last post. Got questions? Make sure to ask them on our YugabyteDB Slack channel, Forum, GitHub or Stackoverflow. Ok, let’s dive right in:
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We are pleased to announce that YugabyteDB 2.0.11 is now live! You can read the official release notes of this and previous versions here. These two releases shipped with a combined 30+ new enhancements and fixes.
What’s YugabyteDB? It is an open source, high-performance distributed SQL database built on a scalable and fault-tolerant design inspired by Google Spanner. Yugabyte’s SQL API (YSQL) is PostgreSQL wire compatible.
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A distributed SQL database needs to automatically partition the data in a table and distribute it across nodes. This is known as data sharding and it can be achieved through different strategies, each with its own tradeoffs. In this post, we will examine various data sharding strategies for a distributed SQL database, analyze the tradeoffs, explain the rationale for which of these strategies YugabyteDB supports and what we picked as the default sharding strategy.
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If you’re a database developer, you know the time saving value of being able to visually design, document and query SQL and NoSQL databases from a single UI. DbSchema is a well-rounded, visual database tool that supports over 40 databases from a single interface. Because YugabyteDB is PostgreSQL compatible, getting DBSchema to work with a distributed SQL database is relatively simple.
What’s YugabyteDB? 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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