HadoopDB Project
HadoopDB An Architectural Hybrid of MapReduce and DBMS Technologies for Analytical Workloads. HadoopDB is: A hybrid of DBMS and MapReduce technologies that targets analytical workloads Designed to run on a shared-nothing cluster of commodity machines, or in the cloud An attempt to fill the gap in the market for a free and open source parallel DBMS Much more scalable than currently available parall
11 Common Web Use Cases Solved in Redis - High Scalability -
« Myth: Google Uses Server Farms So You Should Too - Resurrection of the Big-Ass Machines | Main | Sponsored Post: TripAdvisor, eHarmony, NoSQL Now!, Surge, BioWare, Tungsten, deviantART, Aconex, Hadapt, Mathworks, AppDynamics, ScaleOut, Membase, CloudSigma, ManageEngine, Site24x7 » In How to take advantage of Redis just adding it to your stack Salvatore 'antirez' Sanfilippo shows how to solve som
HadoopとRDBMSを統合し、真のリアルタイムビッグデータ分析を実現する「Hadapt」 – BI for everybody.
ビッグデータの分散処理技術の代表格と言えば、言わずもがなHadoopですが、弱点も多くあります。最大の弱点と言えば「リアルタイム処理には向かない」ということです。Hadoopはレイテンシ（データ転送などを要求してから結果が得られるまでの所要時間）が大きく、主にRDBMSでは取り扱いきれないような大容量データのバッチ処理に使われています。 ビッグデータのリアルタイム処理が必要な場合には、KVSなどのようなNoSQLや、SAP HANAやNetezzaなどのようなNoSQLやインメモリ処理技術を取り入れ、ソフトウェアとハードウェアを統合したDWHアプライアンスなどを導入しなければいけません。 DWHアプライアンスは高価なため大企業向きであり、NoSQLを扱える技術者のいない、または育てる余裕のない中小企業（SMB）はビッグデータのリアルタイム処理への対応がなかなか進みません。 今回ご紹介する「
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ビッグデータをドリルする
Hadoop関連のあらゆる技術が注目を集める現在、Hadoopのエコシステムの中から新しいプロジェクト/実装が生まれ続けているのは驚くべきことではない。Apache Drillは大規模なデータセットをインタラクティブに分析できる分散システムを開発するプロジェクトであり、GoogleのDremelから着想を得ている。Hadoop MapReduceのような既存のビッグデータバッチ処理フレームワークやS4やStormのようなストリームプロセスフレームワークの代替ではなく、大規模データのリアルタイムでインタラクティブな分析を実現する、今までなかった製品だ。 Dremelと同じようにDrillの実装は入れ子になっているツリー構造に似たデータの処理を基本にしている。Dremelでは、データは入れ子のスキーマベースデータモデルであるプロトコルバッファが基本になっている。Drillはこのデータモデルを拡
この記事はhadoopアドベントカレンダー2012の12月16日分です。 ぶっちゃけHadoopとかほとんど使ったこと無いし、word countすらしたことがないので恐縮至極な感じなのですが、色々と思うところはあるので思い切って書いてみることにしました。 現在自分が所属している喜連川研究室がデータベース技術の研究をしているということもあり、Hadoopに関して使わないなりに情報は耳に入りますし、Hadoopについて考えることも多少あります。 なので、Hadoopを具体的に現場でどう使うかみたいな知識はないのですが、一歩引いた目線からHadoopを見た人の意見として、最近のニュース等々を見ながら考えたこと、思ったことを書きたいと思います。 【宣伝】大晦日にデータベースの同人誌を売ります 本題に入る前にいきなり宣伝で恐縮ですが、来る2012年大晦日、コミックマーケット(コミケ)C83にてデー
マイケル・ストーンブレーカー - Wikipedia
マイケル・ストーンブレーカー（Michael Stonebraker, 1943年10月11日[1] - ）はデータベースの研究開発で知られた計算機科学者である。関係データベース業界に多大な影響を与えた。Ingres、Illustra、Cohera、StreamBaseといったシステム構築に携わり、かつてはInformixのCTOも務めた。また、Readings in Database Systemsの著者としても知られている。 経歴[編集] 1965年、プリンストン大学で学士号を取得し、ミシガン大学で修士号（1967年）と博士号（1971年）を取得した[2]。 1994年、Association for Computing Machinery（ACM）のフェローに選ばれた[3]。1997年、全米技術アカデミー会員となった。 29年間カリフォルニア大学バークレー校で計算機科学の教授を務め、
BigData using Erlang, C and Lisp to Fight the Tsunami of Mobile Data - High Scalability -
« Sponsored Post: Akiban, Booking, Teradata Aster, Hadapt, Zoosk, Aerospike, Server Stack, Wiredrive, NY Times, CouchConf, FiftyThree, Percona, ScaleOut, New Relic, NetDNA, GigaSpaces, AiCache, Logic Monitor, AppDynamics | Main | Gone Fishin': PlentyOfFish Architecture » This is a guest post by Jon Vlachogiannis. Jon is the founder and CTO of BugSense. BugSense, is an error-reporting and quality m
SQL is what’s next for Hadoop: Here’s who’s doing it – Old GigaOm
When we first began putting together the schedule for Structure: Data several months ago, we knew that running SQL queries on Hadoop would be a big deal — we just didn’t know how big a deal it would actually become. Fast-forward to today, a mere month away from the event (March 20-21 in New York), and the writing on the wall is a lot clearer. SQL support isn’t the end-game for Hadoop, but it’s the
ビッグデータ分野で相次ぐ買収--その背景を読み解く
Andrew Brust （Special to ZDNET.com） 翻訳校正： 石橋啓一郎 2015-10-21 06:00 ビジネスインテリジェンスを扱うフランスのスタートアップBIME Analyticsは10月13日、クラウドベースの顧客サービスプラットフォーム企業であるZendeskに買収されたと発表した。その1日後には、ビッグデータとメインフレーム技術を手掛けるSyncsortが、Clearlake Capitalに買収されたことを発表している。またその1週間前には、IBMがビッグデータストレージプロバイダーであるCleversafeを買収するという発表があった。 短期間に多くの買収が発表された形になったが、これらは2014年の初めからビッグデータ市場で進んでいる一連の買収劇のごく一部に過ぎない。この記事では、これらの買収を並べて分類し、整理してみたい。これは次に起きる買収を
Michael Ralph Stonebraker (born October 11, 1943[6]) is a computer scientist specializing in database systems. Through a series of academic prototypes and commercial startups, Stonebraker's research and products are central to many relational databases. He is also the founder of many database companies, including Ingres Corporation, Illustra, Paradigm4, StreamBase Systems, Tamr, Vertica and VoltDB
Qubole is offering Facebook’s Presto query engine as a service – Old GigaOm
Qubole, the cloud-based Hadoop service launched by Hive creators Ashish Thusoo and Joydeep Sen Sarma in 2012, is now offering users access to Presto, Facebook’s system interactive SQL queries on data stored in Hadoop. Facebook first announced it had created Presto in June, and then open sourced the technology in November. The type of capability Presto provides — fast, interactive SQL queries on Ha
Big Data Vendor Revenue And Market Forecast 2012-2017 - Wikibon
For a list of Wikibon clients, click here. Methodology Regarding methodology, the Big Data market size, forecast, and related market-share data was determined based on extensive research of public revenue figures, media reports, interviews with vendors, venture capitalists and resellers regarding customer pipelines, product roadmaps, and feedback from the Wikibon community of IT practitioners. Man
"Big data" has been broadly applied as a catch-all phrase for any company, and this gold rush has brought out the usual lineup of copycats and frauds. “Big data” is dead. Vendors killed it. Well, industry leaders helped, and the media got the ball rolling, but vendors hold the most responsibility for the painful, lingering death of one of the most overhyped and poorly understood terms since the ph
「Platfora」がHadoopとインメモリを組み合わせた次世代BIプラットフォームをローンチ – BI for everybody.
ビッグデータ関連のスタートアップとして注目されている「Platfora」が23日、ニューヨークで開催中のStrata Conferenceにおいて、これまでコンセプトのみ公表していた自社の製品を正式に発表しました。 この製品はHadoopとインメモリ技術を組み合わせ、DWHやETLツールを使わずにビッグデータをローデータのまま格納し、インタラクティブに分析・可視化することが可能となっています。 Cloudera、MapR、AWS、Hortonworksといった様々なHadoopディストリビューション上での動作がサポートされており、格納された様々なローデータをETLツールを使用せずに、データの正規化や集計、列の追加などはPlatfora上に用意されたインターフェイスで行うことが出来ます。 そのローデータをインメモリ上に構築された多次元データモデルから”Fractal Cache”と”Lenz
GitHub - zenkay/bigdata-ecosystem: BigData Ecosystem Dataset
Data Projects Frameworks Distributed Programming Distributed Filesystem Key-Map Data Model Document Data Model Key-value Data Model Graph Data Model NewSQL Databases Columnar Databases Time-Series Databases SQL-like processing Integrated Development Environments Data Ingestion Message-oriented middleware Service Programming Scheduling Machine Learning Benchmarking Security System Deployment Contai
Performance data for LevelDB, Berkley DB and BangDB for Random Operations - High Scalability -
« Stuff The Internet Says On Scalability For November 30, 2012 | Main | Sponsored Post: Akiban, Booking, Teradata Aster, Hadapt, Zoosk, Aerospike, Server Stack, Wiredrive, NY Times, CouchConf, FiftyThree, Percona, ScaleOut, New Relic, NetDNA, GigaSpaces, AiCache, Logic Monitor, AppDynamics » This is a guest post by Sachin Sinha, Founder of Iqlect and developer of BangDB. The goal for the paper is
Facebook: An Example Canonical Architecture for Scaling Billions of Messages - High Scalability -
« Zynga's Z Cloud - Scale Fast or Fail Fast by Merging Private and Public Clouds | Main | Sponsored Post: Animoto, deviantART, Hadapt, Clustrix, Percona, Mathworks, AppDynamics, ScaleOut, Cloudkick, Membase, CloudSigma, ManageEngine, Site24x7 » What should the architecture of your scalable, real-time, highly available service look like? There are as many options as there are developers, but if you
DBMS development and other subjects | DBMS 2 : DataBase Management System Services
The cardinal rules of DBMS development Rule 1: Developing a good DBMS requires 5-7 years and tens of millions of dollars. That’s if things go extremely well. Rule 2: You aren’t an exception to Rule 1. In particular: Concurrent workloads benchmarked in the lab are poor predictors of concurrent performance in real life. Mixed workload management is harder than you’re assuming it is. Those minor edge
Oracle is the clear market leader in the commercial database community, and therefore it is critical for any member of the database community to pay close attention to the new product announcements coming out of Oracle’s annual Open World conference. The sheer size of Oracle’s sales force, entrenched customer base, and third-party ecosystem instantly gives any new Oracle product the potential for
6 reasons why 2012 could be the year of Hadoop – Old GigaOm
Hadoop gets plenty of attention from investors and the IT press, but it’s very possible we haven’t seen anything yet. All the action of the last year has just set the stage for what should be a big year full of new companies, new users and new techniques for analyzing big data. That’s not to say there isn’t room for alternative platforms, but with even Microsoft abandoning its competitive effort a
A Yale computer science project has turned into a company that’s attempting to combine the scalability of Hadoop with an ability to perform analytics with both structured and unstructured data. Hadapt launches today at the Structure: Big Data conference in New York, with an undisclosed amount of seed funding and the goal of making Hadoop more broadly applicable for analytics. The company, which wa
In a conversation last year, Justin Sheehy, CTO of Basho, described NoSQL as a movement, rather than a technology. This description immediately felt right; I’ve never been comfortable talking about NoSQL, which when taken literally, extends from the minimalist Berkeley DB (commercialized as Sleepycat, now owned by Oracle) to the big iron HBase, with detours into software as fundamentally different
Ask HS: What will programming and architecture look like in 2020? - High Scalability -
« Stuff The Internet Says On Scalability For December 28, 2012 | Main | Sponsored Post: Flurry, Rumble Games, Duolingo, Booking, aiCache, Teradata Aster, Hadapt, Aerospike, Percona, ScaleOut, New Relic, NetDNA, GigaSpaces, Logic Monitor, AppDynamics, ManageEngine, Site24x7 » This topic has been ripped directly from Lambda the Ultimate's What will programming look like in 2020? post. They are havin
Daniel Abadi
Darnell-Kanal Professor of Computer Science University of Maryland, College Park 8125 Paint Branch Drive College Park, MD 20742 Send Daniel Abadi an email Bio Prof. Abadi performs research on database system architecture and implementation, especially at the intersection with scalable and distributed systems. He is best-known for the development of the storage and query execution engines of the C-
Teradata Blogs When big data becomes vast, what's your data dropping strategy? Read more Support Teradata at Your Service (TAYS) Simple, secure customer access to products, services, education, and support function information. Read more Certifications Teradata Certified Professional Program (TCPP) Management, development, and oversight of the premiere Teradata Certification Program. Read more Con
ImpalaとHiveの戦略について
投稿日: 2014/01/07新年明けましておめでとうございます。皆様のおかげで今年も無事に新しい年を迎えることができました。 さて、新年最初の記事は、昨年暮れに CSO (Chief Strategy Officer) である Mike Olson (@mikeolson) が公開したブログポスト、Impala v Hive を紹介したいと思います。2014 年も Cloudera をよろしくお願い致します。 3日間でImpalaマスターに！ 弊社は一年以上前に Cloudera Impala を公開しました。このローンチは弊社にとって好ましいものであり、弊社のプラットフォームはいくつかの点で良好なものとなりました。つまりそれは弊社のお客様にとって重要なことでした。また、弊社は従来は勝つことができなかったビジネスで勝利をおさめることができるようになりました。以前の製品はインタラクティブな
Can Yahoo, Cloudera and IBM Split the Hadoop Pot? – Old GigaOm
The Wall Street Journal (s nws) appears to have confirmed what we reported last month, which is that Yahoo intends to spin off its Hadoop engineering team into a separate business unit that would compete directly with Cloudera around optimizing and servicing the open-source Apache Hadoop tools. If true, the move almost certainly would be a moneymaker for Yahoo — Hadoop is white-hot right now and v
Pinterest Cut Costs from $54 to $20 Per Hour by Automatically Shutting Down Systems - High Scalability -
« Stuff The Internet Says On Scalability For December 14, 2012 | Main | Sponsored Post: Rumble Games, Duolingo, Booking, aiCache, Teradata Aster, Hadapt, Aerospike, Percona, ScaleOut, New Relic, NetDNA, GigaSpaces, Logic Monitor, AppDynamics, ManageEngine, Site24x7 » We've long known one of the virtues of the cloud is, through the magic of services and automation, that systems can be shut or tuned
Presto (including PrestoDB, and PrestoSQL which was re-branded to Trino) is a distributed query engine for big data using the SQL query language. Its architecture allows users to query data sources such as Hadoop, Cassandra, Kafka, AWS S3, Alluxio, MySQL, MongoDB and Teradata,[1] and allows use of multiple data sources within a query. Presto is community-driven open-source software released under
Teradata Blogs When big data becomes vast, what's your data dropping strategy? Read more Support Teradata at Your Service (TAYS) Simple, secure customer access to products, services, education, and support function information. Read more Certifications Teradata Certified Professional Program (TCPP) Management, development, and oversight of the premiere Teradata Certification Program. Read more Con
Shark: Real-time queries and analytics for big data - O'Reilly Media
Shark: Real-time queries and analytics for big data Shark is 100X faster than Hive for SQL, and 100X faster than Hadoop for machine-learning Hadoop’s strength is in batch processing, MapReduce isn’t particularly suited for interactive/adhoc queries. Real-time1 SQL queries (on Hadoop data) are usually performed using custom connectors to MPP databases. In practice this means having connectors betwe
The 2011 ACM SIGMOD/PODS Conference: Athens, Greece - Conference Program: SIGMOD Sessions
SIGMOD Program Schedule at a Glance SIGMOD Program -Printable Version Keynote 1: J. Hamilton Keynote 2: A. Ailamaki Industry Keynotes Research Papers Industry Papers Demo Papers Undergraduate Posters Tutorials Awards PODS Program Schedule at a Glance PODS Program -Printable Version Keynote: T. Milo Tutorial 1: S. Muthukrishnan Tutorial 2: M. Arenas and J. Perez Research Papers Invited Talks Awards
Teradata doubles down on Hadoop again, this time in the cloud and with Cloudera – Old GigaOm
Data warehouse specialist Teradata is ramping up its Hadoop business again, announcing the company’s Hadoop cloud service as well as a new, tight partnership with Cloudera on Thursday. For a couple of years, analysts have been claiming — and Teradata has been disputing — that the open source Hadoop platform and its expanding set of capabilities could pose a risk to Teradata’s multibillion-dollar b
Teradata Blogs When big data becomes vast, what's your data dropping strategy? Read more Support Teradata at Your Service (TAYS) Simple, secure customer access to products, services, education, and support function information. Read more Certifications Teradata Certified Professional Program (TCPP) Management, development, and oversight of the premiere Teradata Certification Program. Read more Con
Schema-on-need | DBMS 2 : DataBase Management System Services
Two years ago I wrote about how Zynga managed analytic data: Data is divided into two parts. One part has a pretty ordinary schema; the other is just stored as a huge list of name-value pairs. (This is much like eBay‘s approach with its Teradata-based Singularity, except that eBay puts the name-value pairs into long character strings.) … Zynga adds data into the real schema when it’s clear it will
Andrew Brust （Special to ZDNET.com） 翻訳校正： 川村インターナショナル 2015-04-14 06:45 約1年間の不在、そして、今は無きGigaom Researchでリサーチディレクターを務めた期間を経て、筆者はビッグデータ関連の記事を執筆するために米ZDNetに戻ってきた。この1年はあっと言う間に過ぎ去ったが、かなりの変化も起こった。 「SQL-on-Hadoop」が普及し、「Hadoop」とリレーショナルデータベースを扱うほぼすべてのベンダーが独自のソリューションを提供するまでになった。 業界の整理統合が始まった。JaspersoftやPentaho、Hadapt、RainStor、Revolution Analyticsといった企業が既に買収されたか、近いうちに買収される予定だ。 現在、「YARN」と「Hadoop 2.x」が多くのマインドシェ
Google+ is Built Using Tools You Can Use Too: Closure, Java Servlets, JavaScript, BigTable, Colossus, Quick Turnaround - High Scalability -
« Stuff The Internet Says On Scalability For July 15, 2011 | Main | Sponsored Post: New Relic, eHarmony, TripAdvisor, NoSQL Now!, Surge, BioWare, Tungsten, deviantART, Aconex, Hadapt, Mathworks, AppDynamics, ScaleOut, Membase, CloudSigma, ManageEngine, Site24x7 » Joseph Smarr, former CTO of Plaxo (which explains why I recognized his picture), in I'm a technical lead on the Google+ team. Ask me any
Big Data Manifesto | Hadoop, Business Analytics and Beyond - Wikibon
A Big Data Manifesto from the Wikibon Community Providing effective business analytics tools and technologies to the enterprise is a top priority of CIOs and for good reason. Effective business analytics – from basic reporting to advanced data mining and predictive analytics — allows data analysts and business users alike to extract insights from corporate data that, when translated into action, d
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TERADATA - PartnerIntelligence
https://www.americaninno.com/boston
これはHadoopですか？ | Everyday Deadlock
Michael Stonebraker - Wikipedia
‘Big data’ is dead. What’s next?
Overview of the Oracle NoSQL Database
Making Hadoop Work in More Places With Hadapt – Old GigaOm
The NoSQL movement - O'Reilly Radar
Teradata Presto | Product Details | Open Source
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Presto (SQL query engine) - Wikipedia
Teradata Presto | Product Details | Open Source
Teradata Presto | Product Details | Open Source
大きな注目を集める「Apache Spark」--その実力は？