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Netflix’s Distributed Counter Abstraction

The Netflix TechBlog

By: Rajiv Shringi , Oleksii Tkachuk , Kartik Sathyanarayanan Introduction In our previous blog post, we introduced Netflix’s TimeSeries Abstraction , a distributed service designed to store and query large volumes of temporal event data with low millisecond latencies. Today, we’re excited to present the Distributed Counter Abstraction.

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RabbitMQ vs. Kafka: Key Differences

Scalegrid

This decoupling simplifies system architecture and supports scalability in distributed environments. Kafka stores and distributes data through a partitioned log system, which spans multiple brokers to provide fault tolerance and scalability. Apache Kafka uses a custom TCP/IP protocol for high throughput and low latency.

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The Power of Caching: Boosting API Performance and Scalability

DZone

Benefits of Caching Improved performance: Caching eliminates the need to retrieve data from the original source every time, resulting in faster response times and reduced latency. Reduced server load: By serving cached content, the load on the server is reduced, allowing it to handle more requests and improving overall scalability.

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Amazon DynamoDB ? a Fast and Scalable NoSQL Database.

All Things Distributed

Werner Vogels weblog on building scalable and robust distributed systems. a Fast and Scalable NoSQL Database Service Designed for Internet Scale Applications. The original Dynamo design was based on a core set of strong distributed systems principles resulting in an ultra-scalable and highly reliable database system.

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Benchmark (YCSB) numbers for Redis, MongoDB, Couchbase2, Yugabyte and BangDB

High Scalability

Redis Server: 5.07, x86/64. MongoDB server: 4.4.2, BangDB server: 2.0.0, We note that for MongoDB update latency is really very low (low is better) compared to other dbs, however the read latency is on the higher side. Again Yugabyte latency is quite high. The latency table for test D is as below.

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Migrating Critical Traffic At Scale with No Downtime?—?Part 1

The Netflix TechBlog

The first phase involves validating functional correctness, scalability, and performance concerns and ensuring the new systems’ resilience before the migration. It provides a good read on the availability and latency ranges under different production conditions. We will examine these alternatives in the upcoming sections.

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Introducing Netflix’s Key-Value Data Abstraction Layer

The Netflix TechBlog

Central to this infrastructure is our use of multiple online distributed databases such as Apache Cassandra , a NoSQL database known for its high availability and scalability. It also serves as central configuration of access patterns such as consistency or latency targets. Useful for keeping “n-newest” or prefix path deletion.

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