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Displaying posts with tag: cassandra (reset)
Netflix Data Benchmark: Benchmarking Cloud Data Stores

The Netflix member experience is offered to 83+ million global members, and delivered using thousands of microservices. These services are owned by multiple teams, each having their own build and release lifecycles, generating a variety of data that is stored in different types of data store systems. The Cloud Database Engineering (CDE) team manages those data store systems, so we run benchmarks to validate updates to these systems, perform capacity planning, and test our cloud instances with multiple workloads and under different failure scenarios. We were also interested in a tool that could evaluate and compare new data store systems as they appear in the market or in the open source domain, determine their performance characteristics and limitations, and gauge whether they could be used in production for relevant use cases. For these purposes, we wrote Netflix Data Benchmark

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The Uber Engineering Tech Stack, Part II: The Edge and Beyond

The end of a two-part series on the tech stack that Uber Engineering uses to make transportation as reliable as running water, everywhere, for everyone, as of spring 2016.

The post The Uber Engineering Tech Stack, Part II: The Edge and Beyond appeared first on Uber Engineering Blog.

Utilizing OpenStack Trove DBaaS for deployment management

Trove is used for self service provisioning and lifecycle management for relational and non-relational databases in an OpenStack cloud. Trove provides a RESTful API interface that is same regardless of the type of database. CLI tools and a web UI via Horizon are also provided wrapping Trove API requests.

In simple terms. You are a …

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Log Buffer #433: A Carnival of the Vanities for DBAs

This Log Buffer Edition covers Oracle, SQL Server and MySQL blogs of the running week.

Oracle:

  • While checking the sources of the Cassandra/NetBeans integration into GitHub yesterday, something went very badly wrong and ALL the source files in my Maven project that disappeared!
  • AWR Reports, Performance Hub, historisches SQL Monitoring in 12c
  • Oracle Database Mobile Server 12c: Advanced data synchronization engine
  • ORA-39001, ORA-39000 and …
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Pythian’s New Apache Cassandra & DataStax Services

Addition of support for Apache Cassandra and DataStax Enterprise extends Pythian’s leadership in extreme-scale database deployments and big data services

OTTAWA, Canada – July 8, 2015 – Pythian, a global IT services company specializing in helping companies leverage disruptive technologies to optimize revenue-generating systems, today announced the general availability of its consulting and follow-the-sun managed services support for both Apache™ Cassandra™ and DataStax®, the company that delivers Apache Cassandra to the enterprise. Cassandra is an open-source, distributed database management system designed to handle large amounts of data across many commodity servers, providing high availability with no single point of failure.

Pythian leverages an extensive suite of managed services, tools, and database experience to get organizations up and running in their Cassandra and …

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Yelp IT! A talk with 3 Yelp MySQL DBAs on Percona Live & more

Founded in 2004 to help people find great local businesses, Yelp has some 135 million monthly unique visitors. With those traffic volumes Yelp’s 300+ engineers are constantly working to keep things moving smoothly – and when you move that fast you learn many things.

Fortunately for the global MySQL community, three Yelp DBAs will be sharing what they’ve learned at the annual Percona Live MySQL Conference and Expo this April 13-16 in Santa Clara, California.

Say “hello” to Susanne Lehmann, Jenni Snyder and Josh Snyder! I chatted with them over email about their presentations, on how MySQL is used at Yelp, and about the shortage of women in MySQL.

***

Tom: Jenni, you and Josh will be co-presenting “ …

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Some Videos from 2010 OpenSQL Camp Boston

OpenSQLCamp Boston has only been over for a week, but I already have about 2/3 of the videos uploaded to YouTube.  I have updated the schedule page with all the videos and slides I knew about.  I welcome comments with more information (e.g. links to slides, or tag or description suggestions for the YouTube videos).

Here’s the list of videos and slides so far (also linked at http://opensqlcamp.org/Events/Boston2010/Schedule):

Adventures in Alternative Energy “Data Monitoring” with MySQL — architecture and design case study – Matt Yonkovit, Percona – video

Cassandra and Lucene – Jake Luciani, Riptano –  …

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Real-Time Replication from MySQL to Cassandra

Earlier this month I blogged about our new Hadoop applier, I published the docs for that this week (http://docs.continuent.com/tungsten-replicator-3.0/deployment-hadoop.html) as part of the Tungsten Replicator 3.0 documentation (http://docs.continuent.com/tungsten-replicator-3.0/index.html). It contains some additional interesting nuggets that will appear in future blog posts.

The main part of that functionality that performs the actual applier for Hadoop is based around a JavaScript applier engine – there will eventually be docs for that as part of the Batch Applier content ( …

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New MySQL features, related technologies at Percona Live London

The upcoming Percona Live London conference, November 11-12, features quite a number of talks about the latest MySQL features and related technologies. There will be a lots of talks about the new MySQL 5.6 features:

  • Opening keynote highlights MySQL 5.6 new features.
  • New InnoDB Compression talk will cover the new compression algorithm, implemented by Facebook and included in MySQL 5.6.
  • New  …
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Sending the query to the data

It’s common wisdom that large-scale database systems require distributing the data across machines. But what seems to be missing in a lot of discussions is distributing the query processing too. By this I mean the actual computation that’s performed on the data.

I just had a conversation with Peter Zaitsev yesterday that helped make concrete some thoughts I’ve been having about Cassandra for a while. Because Cassandra doesn’t allow you to really do any computation in the data (aggregating, evaluating expressions, and so on), if you’re going to use it for truly Big data, you’re going to fetch enormous amounts of data across the network. Sure, you’re distributing the storage and retrieval across many machines — but you’re locating your data far from your processing. You have a distant low-level key-value store, in essence, and you have to write a database wrapper on top of it if you’re going to use it for anything …

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