YugaByte DB

The YugaByte Database Blog

Thoughts on open source, cloud native and distributed databases

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 YugaByte DB and CockroachDB that use Spanner-like partitioned consensus for single shard transactions and a two phase commit (2PC) protocol for multi-shard (aka distributed) transactions.

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YugaByte DB 1.1 New Feature: Document Data Modeling with the JSON Data Type

Welcome to another post in our ongoing series that highlights new features from the latest 1.1 release announced last week. Today we are going to look at document data modeling using the native JSON data type available in YugaByte DB’s Cassandra compatible YCQL API. Note that this data type is specific to YugaByte DB and is not part of the standard Cassandra Query Language (CQL).

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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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New to Google Cloud Databases? 5 Areas of Confusion That You Better Be Aware of

After billions of dollars in capital expenditure and reference customers in every major vertical, Google Cloud Platform has finally emerged as a credible competitor to Amazon Web Services and Microsoft Azure when it comes to enterprise-ready cloud infrastructure. While Google Cloud’s compute and storage offerings are easier to understand, making sense of its various managed database offerings is not for the faint-hearted.

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Implementing Distributed Transactions the Google Way: Percolator vs. Spanner

Our post 6 Signs You Might be Misunderstanding ACID Transactions in Distributed Databases describes the key challenges involved in building high performance distributed transactions. Multiple open source ACID-compliant distributed databases have started building such transactions by taking inspiration from research papers published by Google. In this post, we dive deeper into Percolator and Spanner, the two Google systems behind those papers,

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How DynamoDB’s Pricing Works, Gets Expensive Quickly and the Best Alternatives

DynamoDB is AWS’s NoSQL alternative to Cassandra, primarily marketed to mid-sized and large enterprises. The uses cases best suited for DynamoDB include those that require a flexible data model, reliable performance, and the automatic scaling of throughput capacity. DynamoDB’s landing page points out that mobile, web, gaming, ad tech, and IoT are all good application types for DynamoDB.

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11 Things You Wish You Knew Before Starting with DynamoDB

DynamoDB is a fully managed NoSQL database offered by Amazon Web Services. While it works great for smaller scale applications, the limitations it poses in the context of larger scale applications are not well understood. This post aims to help developers and operations engineers understand the precise strengths and weaknesses of DynamoDB, especially when it powers a complex large-scale application.

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DynamoDB vs MongoDB vs Cassandra for Fast Growing Geo-Distributed Apps

Amazon DynamoDB is a popular NoSQL database choice for mid-to-large enterprises. In this post, we look beyond Amazon’s marketing claims to explore how well DynamoDB satisfies the core technical requirements of fast growing geo-distributed apps with low latency reads, a common use case found in today’s enterprises. We examine the development, operational and financial consequences of working around the limitations of DynamoDB when attempting to “force-fit” for this use case.

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Polyglot Persistence vs. Multi-API/Multi-Model: Which One For Multi-Cloud?

Modern app architectures rely on data with different models and access patterns. Polyglot persistence, first introduced in 2011, states that each such data model should be powered by an independent database that is purpose-built for that model. The original intent was to look beyond relational/SQL databases to the emerging world of NoSQL.


Polyglot Persistence in Action at an E-Commerce App (Source: Martin Fowler)

The Messy Reality of Polyglot Persistence

Polyglot persistence is not free of costs — it leads to increased complexity across the board.

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