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Vertica
Description de Vertica
La plateforme Vertica Analytics est conçue à partir de la toute première ligne de code pour l'analyse Big Data. Elle est conçue pour être utilisée dans les entrepôts de données et autres flux de travail Big Data pour lesquels la rapidité, la capacité d'évolution, la simplicité et l'ouverture sont essentielles au succès de l'analyse. Vertica s'appuie sur une architecture distribuée éprouvée et fiable ainsi que sur une compression en colonnes pour atteindre une vitesse extrêmement élevée. Une licence simplifiée et la possibilité de déploiement en tout lieu constituent la garantie des analyses Big Data.
Qui utilise Vertica ?
S'adresse à des utilisateurs de technologies existantes qui cherchent à améliorer capacité d'évolution et la performance de leur entrepôt de données.
Vertica ne vous convainc pas tout à fait ?
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Vertica
Alternatives à Vertica
Avis sur Vertica
Database Management tool
Avantages :
One of the best SQL database management tool. A good solution to store and manage data.
Inconvénients :
I have nothing particular to say against this tool.
Vertica - Fastest MPP database to build data warehouses !
Commentaires : MPP database to build good enterprise data warehouse.
Avantages :
The best MPP database one can get to build analytical data warehouses . The columnar database architecture helps to query the data from the databases very quickly and efficiently . The dimension modeling made easy with Vertica.
Inconvénients :
The GUI of the Vertica interface definitely needs improvement. The node manage can also be done better to perform snowflake architecture querying.
Alternatives envisagées précédemment :
Smart database management tool
Avantages :
The robustness we get by using Vertica over other database management tools is a real game changer. We get stream of high volume data and the data needs to be processed at a rapid rate to keep up with the processes in the pipeline. Here, Vertica delivers on the expectations.
Inconvénients :
While Vertica is robust, there are data size limitations. After a certain threshold, the software breaks! Although we are able to work around and make the floorplans such that this doesn't hamper live processes, but the data size limitations can kick-in.
Alternatives envisagées précédemment :
Best Analytical Database I have ever used
Commentaires : I'm using vertical as a analytical dB for twitter sentiment analysis. I have used Flume to get twitter data and use R to move the data from Hadoop to vertica DB and do analytical function and project the data in tableau.
Avantages :
Analytical features that is available with this DB. Ease of use with Text User Interface and UI. Deployment is very fast and easy to do. Integration support with almost all top ingress and egress platform like. Apache Kafka, Flume, Hadoop etc. Very efficient and easy to deploy multinode cluster.
Inconvénients :
Nothing I can think of, I was having node health issue alert even when the node was online. I need to upgrade to latest version and hope that issue has been addressed.
light weight platform that works very well
Commentaires : We were looking for an analytics platform that can work concurrently with hadoop clusters that was focused on performance and could also be inter-changeably used as a data processing engine.
Avantages :
It is light weight and nimble but at the same time is good on performance - the fact that it is column store without the real need for indexing makes it easier to get started and then the storage requirement is also much smaller thanks to coding schemas and algorithms.
Inconvénients :
for me, the biggest issue was the fact that it really affects performance when we try to run many large concurrent queries - I wish there was a solution to this. In addition, initial cost of investment to get started on Vertica may discourage SMB's.
