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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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
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
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
From HadoopDB to Hadapt: A Case Study of Transitioning a VLDB paper into Real World Deployments
HadoopWorld 2011 Presentation by Daniel Abadi As Hadoop rapidly becomes the universal standard for scalable data analysis and processing, it is increasingly important to understand its strengths and weaknesses for particular application scenarios in order to avoid inefficiency pitfalls. For example, Hadoop has great potential to perform scalable graph analysis if it is used correctly. Recent bench
Hadapt has closed a Series A funding round of $9.5 million for its Hadoop-based software that handles structured and unstructured data in a single system. Norwest Venture Partners and Bessemer Venture Partners led the round, which comes about seven months after Hadapt’s launch in March 2011. Hadapt, Cambridge, Mass., is in a good position if it can deliver on its promise of letting organizations p
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
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Making Hadoop Work in More Places With Hadapt – Old GigaOm
Teradata Presto | Product Details | Open Source
Teradata Presto | Product Details | Open Source
Hadapt raises $9.5M for Hadoop data warehouse – Old GigaOm
Teradata Presto | Product Details | Open Source