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Category: How It Works

Basic Introduction to YugabyteDB Components

Basic Introduction to YugabyteDB Components

In this short blog post we are going to give you a quick overview of the components that make up a YugabyteDB universe.

Universe

YugabyteDB is composed of nodes. We collectively refer to this collection of all nodes as a universe. These nodes can be physical machines, virtual machines or containers (e.g. Kubernetes).

Clusters

A YugabyteDB universe is made up of one or more clusters.

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How to Migrate Data from Cassandra or MySQL to YugabyteDB?

How to Migrate Data from Cassandra or MySQL to YugabyteDB?

If you work with databases, at some point you are going to need to get data in and out them using a format that can be consumed by a completely different system. YugabyteDB makes use of CSV files to make this as easy as possible. The CSV format is arguably the most universally portable way to get data migrations accomplished.

TL;DR – YugabyteDB makes use of Cassandra’s COPY FROM command and a forked version of Cassandra’s Bulk Loader to get data into the system.

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Getting Started with YugabyteDB’s Security Features

Getting Started with YugabyteDB’s Security Features

In this blog post we are going to give you a quick overview of YugabyteDB’s security features . We’ll cover authentication, authorization, encryption, plus a simple security checklist to help lock down your install. For the purposes of this walk-through, we are going to use the Cassandra-compatible, flexible-schema YCQL API as an example.

Authentication

First things first, authentication is not enabled by default. So, once you are through experimenting with YugabyteDB on your laptop and are ready to start development in earnest,

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YugaByte Database Engineering Update – Nov 27, 2018

YugaByte Database Engineering Update – Nov 27, 2018

Lots has happened since our last engineering update about 3 months ago. Below are some of the highlights.

PostgreSQL API Updates & PostgresConf Silicon Valley Wrap-Up

We have made a lot of progress on YSQL, the PostgreSQL compatible distributed SQL API for YugabyteDB! You can also read about YSQL architecture which covers how distributed SQL is implemented in YugabyteDB.

We were at the first ever PostgresConf Silicon Valley in October 2018.

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Data Modeling Basics – PostgreSQL vs. Cassandra vs. MongoDB

Data Modeling Basics – PostgreSQL vs. Cassandra vs. MongoDB

Application developers usually spend considerable time evaluating multiple operational databases to find that one database that’s best fit for their workload needs. These needs include simplified data modeling, transactional guarantees, read/write performance, horizontal scaling and fault tolerance. Traditionally, this selection starts out with the SQL vs. NoSQL database categories because each category presents a clear set of trade-offs. High performance in terms of low latency and high throughput is usually treated as a mandatory requirement and hence is expected in any database chosen.

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Distributed Backups in Multi-Region YugabyteDB Clusters

Distributed Backups in Multi-Region YugabyteDB Clusters

Our post Getting Started with Distributed Backups in YugabyteDB details the core architecture powering distributed backups in YugabyteDB. It also highlights a few backup/restore operations in a single region, multi-AZ cluster. In this post, we perform distributed backups in a multi-region YugabyteDB cluster and verify that we achieve performance characteristics similar to those observed in a single region cluster.

We configured a 9 node cluster with 3 availability zones across 2 regions and repeated the benchmark introduced in the post.

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Getting Started with Distributed Backups in YugabyteDB

Getting Started with Distributed Backups in YugabyteDB

YugabyteDB is a distributed database with a Google Spanner-inspired strongly consistent replication architecture that is purpose-built for high availability and high performance. This architecture allows administrators to place replicas in independent fault domains, which can be either availability zones or racks in a single region or different regions altogether. These types of multi-AZ or multi-region deployments have the immediate advantage of guaranteeing organizations a higher order of resilience in the event of a zone or region failure.

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YSQL Architecture: Implementing Distributed SQL in YugabyteDB

YSQL Architecture: Implementing Distributed SQL in YugabyteDB

In this post, we will look at the architecture of YSQL, the PostgreSQL-compatible distributed SQL API in YugabyteDB. We will also touch on the current state of the project and the next steps in progress. Here is a quick overview:

  • YugabyteDB has a common distributed storage engine that powers both SQL and NoSQL
  • For supporting NoSQL apps, YugabyteDB is designed for low latency, sub-millisecond reads and massive write scalability. It can handle millions of requests and many TBs of data per node with linear scalability and high resilience.

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Apache Cassandra: The Truth Behind Tunable Consistency, Lightweight Transactions & Secondary Indexes

Apache Cassandra: The Truth Behind Tunable Consistency, Lightweight Transactions & Secondary Indexes

ACID transactions were a big deal when first introduced formally in the 1980s in monolithic SQL databases such as Oracle and IBM DB2. Popular distributed NoSQL databases of the past decade including Apache Cassandra initially focused on “big data” use cases that did not require such guarantees and hence avoided implementing them altogether. Our post, “A Primer on ACID Transactions: The Basics Every Cloud App Developer Must Know” details the various types of ACID transactions (single key,

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Google Spanner vs. Calvin: Is There a Clear Winner in the Battle for Global Consistency at Scale?

Google Spanner vs. Calvin: Is There a Clear Winner in the Battle for Global Consistency at Scale?

Prof. Daniel Abadi, lead inventor of the Calvin transaction management protocol and the PACELC theorem, wrote a thought-provoking post last month titled “NewSQL database systems are failing to guarantee consistency, and I blame Spanner”. The post takes a negative view of software-only Google Spanner derivative databases such as YugabyteDB and CockroachDB that use Spanner-like partitioned consensus for single shard transactions and a two phase commit (2PC) protocol for multi-shard (aka distributed) ACID transactions.

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