Welcome to this week’s tips and tricks blog where we explore both beginner and advanced YugabyteDB topics for PostgreSQL and Oracle DBAs.
Please note that most examples in the post make use of the Northwind sample database. Instructions on how to get it installed are here.
Ok, let’s dive in…
In a nutshell,
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What a great KubeCon + CloudNativeCon Europe 2020 earlier this month! We were happy to participate, sponsor, and help #KeepCloudNativeConnected.
Thank you to everyone who stopped by the YugabyteDB booth, and a big thanks to all who redeemed your virtual swag of $5 to charity. Together, your swag redemptions ended up in more than $3,000 being donated across these three charities:
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Getting the total row counts of data in tables across various dimensions (per-table, per-schema, and in a given database) is a useful SQL technique to have in your toolkit. This blog post will guide you to obtain per-table row counts of all tables in PostgreSQL and YugabyteDB. This can serve as a first sanity check after migrating an application with pre-existing data from PostgreSQL to YugabyteDB.
This blog post also outlines how to get the following row counts broken down per table in a schema,
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Layer 7 proxies like NGINX and HAProxy have been popular since the mid-2000s. The term “proxy” refers to their role as an intermediary for the traffic between an application client and an application server. The “layer 7” classification comes from the fact that these proxies take routing decisions based on URLs, IPs, TCP/UDP ports, cookies, or any information present in messages sent over a layer 7 (aka application layer) networking protocol like HTTP and gRPC.
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For those of you who missed last week’s YugabyteDB Community Q&A session, which covered GraphQL fundamentals, here’s the playback:
If you are interested in further exploring the possibilities of Hasura GraphQL and Distributed SQL, check out these resources.
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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.
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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.
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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.
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It was late February, and I had spent the past several weeks learning everything I could about the distributed database ecosystem. As an intern on the Investment Team at 8VC, I had gotten the chance to work on technical due diligence under Partner & CTO Bhaskar Ghosh, taking a multitude of pitches every week and constantly shifting contexts. One of those companies speaking with us was Yugabyte,
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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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