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The Distributed SQL Blog

Thoughts on distributed databases, open source, and cloud native

Using Redis API as a True Distributed, Fault-Tolerant Database

YugabyteDB is an open source, transactional, high-performance database for your business-critical data —and it is compatible with the Redis API. Over the years, many of us fell in love with the simplicity and the intuitiveness of the various Redis commands and data structures. We are excited to share the same love with all the Redis developers out there.

When using your Redis application with YugabyteDB, your data is replicated and persisted with strong consistency.

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Scaling YugabyteDB to Millions of Reads and Writes

Here at YugaByte, we continuously push the limits of the systems we build. As a part of that, we ran some large cluster benchmarks to scale YugabyteDB to million of reads and writes per second while retaining low latencies. This post goes into the details about our 50 node cluster benchmark. We posted the results of the benchmark on a 25 node cluster in our community forum.

The graph above shows how you can achieve linear scalability with YugabyteDB.

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Extending Redis API with a Native Time Series Data Type

Defining time series data

We have spoken to several developers that have a need to model time series like data in Redis. A few examples of such applications are:

  • Stock quote feed.
  • Order history for a user in an online retailer.
  • User activity in any application.
  • Data gathered from IoT sensor devices.

In general time series data has the following characteristics:

  1. Each data point in a time series (e.g.

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Building a Strongly Consistent Cassandra with Better Performance

In an earlier blog on database consistency, we had a detailed discussion on the risks and challenges applications face in dealing with eventually consistent NoSQL databases. We also dispelled the myth that eventually consistent DBs perform better than strongly consistent DBs. In this blog, we will look more closely into how YugabyteDB provides strong consistency while outperforming an eventually consistent DB like Apache Cassandra. Note that YugabyteDB retains drop-in compatibility with the Cassandra Query Language (CQL) API.

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YugabyteDB Architecture: Diverse Workloads with Operational Simplicity

YugabyteDB is a transactional, high performance, geo-distributed operational database that converges multiple NoSQL and SQL interfaces into an unified solution. The v0.9 public beta of YugabyteDB includes the YCQL and YEDIS APIs that are compatible with Cassandra Query Language (CQL) and Redis APIs respectively. PostgreSQL-compatible YSQL API is under development. A fundamental design goal for YugabyteDB has been to provide the same transactional, performance and operational simplicity guarantees irrespective of the API used.

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Yugabyte Has Arrived!

Today, we are launching Yugabyte out of stealth and announcing the availability of YugabyteDB’s first public beta release. Yugabyte offers an open-source, cloud-native database for mission-critical applications. Yuga in Sanskrit represents an era or an epoch (about 4.32 million human years), a very long period of time. We picked the name Yugabyte to signify data that lives forever without limits. Our ultimate goal is to simplify data that is critical to businesses.

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A for apple, B for ball, C for “CAP theorem”

In the world of databases today, consistency is one of the most misunderstood concepts. It is also one of the big reasons NoSQL databases are difficult to reason about.

The CAP theorem states that “in the presence of a network partition, one has to choose between consistency and availability”. In order to provide higher write availability, some NoSQL databases implement a weaker form of consistency called eventual consistency.

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Facebook’s User DB — Is it SQL or NoSQL?

Updated March 2019.

Ever wondered which database Facebook (FB) uses to store the profiles of its 2.3B+ users? Is it SQL or NoSQL? How has FB database architecture evolved over the last 15+ years? As an engineer in FB database infrastructure team from 2007 to 2013, I had a front row seat in witnessing this evolution. There are invaluable lessons to be learned by better understanding the database evolution at the world’s largest social network,

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NoSQL vs SQL in 2017

Came across the image below here and this made me smile. Not because of the implied complexity of choosing a database, but the reality with which this flow chart captures the state of the database world today in 2017. Of course, running whatever database you end up choosing in production is a whole another order of complexity.

I have been working on distributed systems for the last 10+ years.

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