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Score 8.7 out of 101
19 Ratings
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Score 7.7 out of 101

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Likelihood to Recommend

Actian Matrix

Actian matrix is not good for small data sets. If you have a limited data pool, or do not plan on having multiple users/clients accessing a data source, stick with a more traditional relational database model - Access for the truly small user base, or a DB2 or Oracle back end if your going to have multiple users, and moderate sized data. Actian is for LARGE data sets (Big Data, in the industry parlance). Millions of rows of data from multiple sources with various down stream systems accessing the database. It is for data analytics of large data groups and intense data mining.
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Vertica

Vertica is not the silver bullet but based on my experience in 9/10 cases in which you need an analytical database, Vertica is probably the answer.Currently we're using Vertica more as a data processing engine in conjunction with a Hadoop cluster as some of the steps are way more efficient than doing them in Hadoop and easier to manage (e.g. iterative processing steps). We also had a pretty good experience using it with Storm and Hadoop.
At the same time, using Vertica as a traditional OLTP database, with many small transactions inserting/deleting/updating data is not going to take you very far so that’s an obvious case where Vertica is not recommended.
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Pros

  • Handles Various data types from multiple sources.
  • Indexing speed - using the Actian platform as a back end database greatly improved processing time.
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  • Analytical querying due to built in analytical functions that actually perform across TB of data.
  • Ingestion of data. We can send billions of rows to Vertica easily via the WOS system and it is ready for use immediately.
  • Efficient storage of data. What raw is TB of data, once ingested into Vertica only takes up GB of disk space.
  • Management! The management console is intuitive and useful making keeping an eye on your cluster easier than any other product like this I have used.
Eva Donaldson profile photo

Cons

  • Its a new product, there are plenty of bugs to work out with regards to converting special reserve characters that might crop up in data.
  • The Matrix 2 Matrix database port tool needs some ironing out.
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  • Deletion is tough in Vertica. Because one of our larger fact tables is rapidly changing we have a need to run purges on a regular basis. Those purges can take a day and delays the other processes while that is happening. It would be nice if when I hit delete, it really deleted.
  • Permissions on table manipulation is a bit lacking. In order to edit a table structure you have to be the owner, ie the creator, of the table. It means setting up true administrators who can maintain each other's work is tough.
Eva Donaldson profile photo

Usability

Actian Matrix6.0
Based on 1 answer
I wish to give higher rating for the speed and efficiency in handling the queries, but only 6 because of consistent bugs we encounter
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No score
No answers yet
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Support

Actian Matrix8.0
Based on 1 answer
  • Faster initial response
  • Trained professionals
  • Very helpful in resolving issues
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No score
No answers yet
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Implementation

Actian Matrix6.0
Based on 1 answer
Leader failover setup is the toughest and lack of proper documentation is making things tough.
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No score
No answers yet
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Alternatives Considered

Actian Matrix is our first big data analytics storage platform, and as I was not involved in the POC process to compare it to other products out on the market, unfortunately I cannot say if it is better than other Big Data storage options. I can say that it out performs products such as Oracle or UDB in regards to the volume of data it can easily index and handle.
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Vertica is much easier to manage; is just software (i.e. vs. Netezza), easier to scale and extend, with a very powerful query execution engine and storage layer. While other solutions (e.g. Greenplum) are just postgres clones that were extended to run at scale but still keep their traditional database features (e.g. indexes, materialized views, etc), Vertica has been built from scratch with performance in mind. Five years ago Vertica's storage layer was pretty advanced with very few contenders. Currently more are copying it and lately you can find features like RLE (run length encoding), etc., even in open source columnar formats like Parquet, ORC. So in order to keep up, Vertica has been extended with Hadoop, Kafka, unstructured data (FlexTables) support, etc.
Traian Antonescu profile photo

Return on Investment

  • I cannot comment on the specific numbers, all I can say is that switching to the backend greatly improved our processing speed. The more we process through our systems, the more clients we can serve. Which should bump ROI.
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  • For our internal business we have insights we could never have had without Vertica. We can actually see where our money is coming from and point our marketing and sales strategies in the correct direction thereby returning far more than we pay.
  • For our customers we can offer services they had been begging for. Before implementing Vertica we had no insight on a client's marketing across all their activities because the data was just too large. Now, there is no question we can't answer.
Eva Donaldson profile photo

Pricing Details

Actian Matrix

General
Free Trial
Free/Freemium Version
Premium Consulting/Integration Services
Entry-level set up fee?
No
Additional Pricing Details

Vertica

General
Free Trial
Free/Freemium Version
Premium Consulting/Integration Services
Entry-level set up fee?
No
Additional Pricing Details