The Distributed SQL Blog

Thoughts on distributed databases, open source and cloud native

YugaByte DB 1.1 New Feature: Speeding Up Queries with Secondary Indexes

Welcome to another post from our ongoing series where we highlight a new feature from the latest 1.1 release! Today we are going to look at secondary indexes.

Defining Secondary Indexes

A database index is a data structure that improves the speed of data retrieval operations on a database table. Typically, databases are very efficient at looking up data by the primary key.

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Jepsen Testing on YugaByte DB

At YugaByte, our mission is to build a robust, reliable, distributed OLTP database. Needless to say, we take correctness and technical accuracy of our claims very seriously. Therefore, we absolutely love a testing framework like Jepsen which helps verify correctness and are fans of Kyle Kingsbury’s work!

Here is a summary of what we have done so far in regards to Jepsen:

  • We have performed our own DIY style Jepsen testing
  • The YugaByte DB Jepsen testing repository is open source
  • For the current suite of Jepsen tests for YugaByte DB that we have tested in a loop,

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How Does the Raft Consensus-Based Replication Protocol Work in YugabyteDB?

As we saw in ”How Does Consensus-Based Replication Work in Distributed Databases?”, Raft has become the consensus replication algorithm of choice when it comes to building resilient, strongly consistent systems. YugabyteDB uses Raft for both leader election and data replication. Instead of having a single Raft group for the entire dataset in the cluster, YugabyteDB applies Raft replication at an individual shard level where each shard has a Raft group of its own.

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How Does Consensus-Based Replication Work in Distributed Databases?

Whether it be a WordPress website’s MySQL backend or Dropbox’s multi-exabyte storage system, data replication is at the heart of making data durable and available in the presence of hardware failures such as machine crashes, disk failures, network partitions and clock skews. The basic idea behind replication is very simple: keep multiple copies of data on physically isolated hardware so that the failure in one does not impact the others and as a result,

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A Quick Guide to Secondary Indexes in YugaByte DB

When creating a Cassandra-compatible YCQL table in YugaByte DB, you are required to create a primary key consisting of one or more columns of the table. Primary key based retrievals are efficient because YugaByte DB automatically indexes/organizes the data by the primary key. However, there are many use-cases where you may need to retrieve data using columns that are not a part of the primary key.

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6 Signs You Might be Misunderstanding ACID Transactions in Distributed Databases

As described in A Primer on ACID Transactions, first generation NoSQL databases dropped ACID guarantees with the rationale that such guarantees are needed only by old school enterprises running monolithic, relational applications in a single private datacenter. And the premise was that modern distributed apps should instead focus on linear database scalability along with low latency, mostly-accurate,

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A Primer on ACID Transactions: The Basics Every Cloud App Developer Must Know

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 Amazon DynamoDB and Apache Cassandra initially focused on “big data” use cases that did not require such guarantees and hence avoided implementing them altogether. However, ACID transactions are making a strong comeback in the last 2 years with the launch of next-generation distributed databases that have built-in support for them.

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A Busy Developer’s Guide to Database Storage Engines — The Basics

When evaluating operational databases, developers building distributed cloud apps tend to focus on data modeling flexibility, consistency guarantees, linear scalability, fault tolerance, low latency, high throughput and easy manageability as high priority concerns. However, it is essential to have a good understanding of the underlying storage engine to reason about how the database actually delivers on these core promises. This post aims to help busy developers make informed choices in the context of database storage engines.

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A Busy Developer’s Guide to Database Storage Engines — Advanced Topics

In the first post of this series, we learnt about the B-Tree vs LSM approach to index management in operational databases. While the indexing algorithm plays a fundamental role in determining the type of storage engine needed, advanced considerations highlighted below are equally important to take into account.

Consistency, Transactions & Concurrency Control

Monolithic databases,

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