Tokyo Cabinet
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Tokyo Cabinet is a key-value database manager that provides several database structures like hash, B-tree, fixed-length, and table. It runs quickly on Linux, Solaris, and Mac OS X and offers advantages like small database file sizes, fast processing speeds, high performance in multi-threaded environments, and simple APIs. Benchmark tests showed Tokyo Cabinet was 31 times faster than MySQL for writing and retrieving 10,000 records.
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SortaSQL is a proposal to add seamless horizontal scalability to SQL databases by using the filesystem to store and retrieve data. The SQL database would store metadata and handle queries, while an embedded key-value store manages record storage on files in the local or distributed filesystem. This allows queries to scale across many servers by letting the filesystem handle replication, performance and locking of distributed data files. The architecture involves an application communicating with PostgreSQL over SQL, which uses a SortaSQL plugin to retrieve rows from Kyoto Cabinet key-value files on the POSIX filesystem. Case studies at CloudFlare show how a 400GB per day dataset can be efficiently stored and queried at scale using this approach.
in-memory database system and low latency
This document discusses in-memory database systems and high performance computing. It begins with an overview of domestic and international in-memory databases like Altibase, Oracle TimesTen, McObject ExtremeDB, and KX Systems KDB+. It then discusses the advantages of in-memory architectures for achieving ultra-low latency. The rest of the document covers technologies that enable high performance like NUMA, SSDs, InfiniBand, message queues, and complex event processing. It concludes by discussing in-memory computing and high performance computing technologies.
Design Principles for a Modern Data Warehouse
This document discusses design principles for a modern data warehouse based on case studies from de Bijenkorf and Travelbird. It advocates for a scalable cloud-based architecture using a bus, lambda architecture to process both real-time and batch data, a federated data model to handle structured and unstructured data, massively parallel processing databases, an agile data model like Data Vault, code automation, and using ELT rather than ETL. Specific technologies used by de Bijenkorf include AWS services, Snowplow, Rundeck, Jenkins, Pentaho, Vertica, Tableau, and automated Data Vault loading. Travelbird additionally uses Hadoop for initial data processing before loading into Redshift
MySQL And Search At Craigslist
- Craigslist is a classified advertising website with over 500 cities worldwide and handles over 20 billion pageviews and 50 million users per month. It allows users to post free classified ads for jobs, housing, items for sale, and other services.
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This document summarizes a presentation on tier-1 business intelligence (BI) in the world of big data. The presentation will cover Microsoft's BI capabilities at large scales, big data workloads from Yahoo and investment banks, Hadoop and the MapReduce framework, and extracting data out of big data systems into BI tools. It also shares a case study on Yahoo's advertising analytics platform that processes billions of rows daily from terabytes of data.
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Unleash the Power of Redis with Amazon ElastiCache
1) Amazon ElastiCache is a fully managed in-memory data store that can be used with Redis or Memcached to improve performance for applications.
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1) Amazon ElastiCache provides a fully managed in-memory data store using Redis or Memcached.
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Most databases are based on architectures that pre-date advances to modern hardware. This results in performance issues, the need to overprovision, and a high total cost of ownership. In this webinar we will discuss the advances to modern server technology and take a deep dive into Scylla’s shard-per-core architecture and our asynchronous engine, the Seastar framework.
Join us to learn how Seastar (and Scylla):
Avoid locks and contention on the CPU level
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Implement its per-core shared-nothing autosharding mechanism
Utilize modern storage hardware
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Alluxio Community Office Hour
Apr 7, 2020
For more Alluxio events: https://www.alluxio.io/events/
Speaker: Bin Fan
Alluxio (alluxio.io) is an open-source data orchestration system that provides a single namespace federating multiple external distributed storage systems. It is critical for Alluxio to be able to store and serve the metadata of all files and directories from all mounted external storage both at scale and at speed.
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In this Office Hour, we will go over how to:
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Parquet Twitter Seattle open house
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JavaOne2016 - Microservices: Terabytes in Microseconds [CON4516]
Microservices can provide terabytes of data in microseconds by mapping data from SQL databases into in-memory key-value stores and column key stores within JVMs. This is done through periodic synchronization of changed data from databases into memory and mapping the in-memory data into fast access structures. The in-memory data is then exposed through Java Stream and REST APIs to microservices for high performance querying and analysis of large datasets. This architecture allows microservices to quickly share access to large datasets and restart rapidly by reloading from the synchronized persistent stores.
JavaOne2016 - Microservices: Terabytes in Microseconds [CON4516]
By leveraging memory-mapped files, Speedment and the Chronicle Engine supports large Java maps that easily can exceed the size of your server’s RAM.Because the Java maps are mapped onto files, these maps can be shared instantly between several microservice JVMs and new microservice instances can be added, removed, or restarted very quickly. Data can be retrieved with predictable ultralow latency for a wide range of operations. The solution can be synchronized with an underlying database so that your in-memory maps will be consistently “alive.” The mapped files can be tens of terabytes, which has been done in real-world deployment cases, and a large number of micro services can share these maps simultaneously. Learn more in this session.
Red Hat Storage Server For AWS
The ability to create global namespace, high availability, and volume economics enables unique capabilities when Red Hat Storage Server is used on Amazon Web Services (AWS). In this session, you’ll learn about the capabilities and the potential of using AWS ephemeral storage, availability zones, and regions to deliver a truly distributed cloud storage solution that is geographically diverse, cost effective, and highly available.
SQL Server In-Memory OLTP introduction (Hekaton)
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Google Go! language
Go is a general-purpose, compiled language that is strongly typed, garbage-collected, and has explicit support for concurrent programming through goroutines and channels. Programs in Go are constructed using packages and the language provides standard types while also allowing functions to return multiple values.
Orient db
An open source NoSQL database that provides 150,000 inserts per second and has no dependencies. It supports document, graph and native JSON data structures and RESTful APIs. It offers ACID transactions with roles and security. It has four storage modes - embedded, client/server, distributed, and in-memory - with embedded mode being very fast by running in the same JVM as the application and in-memory mode keeping the database only in memory for increased speed but losing data at shutdown.
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This document discusses the Racket programming language, which originated from Lisp and Scheme. Racket aims to provide flexibility for creating domain-specific languages and running on any platform, with features including macros, modules, lexical closures, pattern matching, and tools for graphics, GUI, and web application development. Racket also includes a just-in-time compiler, garbage collector written in C, and IDE called DrRacket that supports multiple operating systems.
Flask - Python microframework
Flask is a simple and small Python web framework created by Armin Ronacher. It is inspired by the Ruby framework Sinatra and focuses on keeping a small core while allowing extensions to add additional functionality through a plug-and-play approach. Flask uses Jinja2 as its templating engine and the WSGI interface to handle HTTP requests and responses and route URLs.
clj http
Clj-http is a Clojure HTTP library that provides functions to execute HTTP operations like GET, HEAD, PUT, POST and DELETE using Ring-style middleware. It is inspired by Ring and designed for simplicity and testability, with support provided by the creator Mark McGranaghan through examples on hands-on usage with Leiningen and project.clj files.
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Jav ate
JavATE is a set of Java libraries that enable application development using domain-driven design principles. It is based on the ZK framework for building web applications and works well with ORM technologies like Hibernate. The core libraries include DominATE for domain modeling, ApplicATE for application services, and GuidATE for graphical user interfaces.
javATE
JavATE is a set of Java libraries that enable application development using domain-driven design principles. It is based on the ZK framework for building web applications and works well with ORM technologies like Hibernate. The core libraries include DominATE for domain modeling, ApplicATE for application services, and GuidATE for graphical user interfaces.
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This document contains examples of functions in Clojure for working with characters, strings, and arrays. It shows using char? to check if a value is a character, format to format output as hexadecimal, char-array to create a character array, chars and doubles to print the contents of character and double arrays respectively.
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Tokyo Cabinet
- 1. or LOL
- 2. Tokyo
- 3. Cabinet
- 5. Runs in... Runs on Linux, Solaris, Mac OS X
- 15. Advantages Disadvantages NO-SQL Windows platform is not supported Speed not durable (isn’t crash safe) high scalability: No actual limit size of a database file (to 8 exabytes) LOCK ( only one transaction can be activated with the database at the same time) Tokyo Cabinet is written in the C language, and provided as API of C, Perl, Ruby, Java, and Lua. high concurrency Write-ahead logging: (log transaction status-> succeeded, half-succeeded, or failed)
- 16. Thank You!